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A computer simulation of the admissions and scheduling system at St. Paul’s hospital 1977

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A COMPOTES SIMULATION OF THE ADMISSIONS AND SCHEDULING SYSTEM AT ST. PAUL'S HOSPITAL by MARK GORDON CHASE B.Sc.,Mount A l l i s o n U n i v e rsity,1975 A THESIS SUBMITTED IN PABTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE i n THE FACULTY OF GRADUATE STUDIES I n s t i t u t e o f A p p l i e d Mathematics and S t a t i s t i c s We accept t h i s t h e s i s as conforming to the r e q u i r e d standard THE UNIVERSITY OF BRITISH COLUMBIA September,1977 <£) Mark Gordon Chase, 1977 In present ing th is thes is in p a r t i a l fu l f i lment of the requirements for an advanced degree at the Un ivers i ty of B r i t i s h Columbia, I agree that the L ibrary shal l make it f ree ly ava i l ab le for reference and study. I fur ther agree that permission for extensive copying of th is thes is for scho la r ly purposes may be granted by the Head of my Department or by his representa t ives . It is understood that copying or pub l i ca t ion of th is thes is fo r f i n a n c i a l gain sha l l not be allowed without my writ ten pe rm i ss i on . Department of J^t^La^L'.y & £ t U ^ j £ j £ <2a*^£<S The Un ivers i ty of B r i t i s h Columbia 2075 Wesbrook Place Vancouver, Canada V6T 1W5 Date Z3. /P77 i i i ABSTRACT I E t h i s work, the admissions and s c h e d u l i n g system at St. Paul's H o s p i t a l was examined by means of modelling and computer s i m u l a t i o n . The H o s p i t a l i s an acute-care f a c i l i t y with very high occupancy and a p o l i c y of admitting a l l of the emergency p a t i e n t s who r e q u i r e h o s p i t a l i z a t i o n . I t now f a c e s the problem of p r o v i d i n g space f o r these p a t i e n t s without s e r i o u s l y d i s r u p t i n g scheduled admissions. A f t e r i n v e s t i g a t i o n of the l i t e r a t u r e , i t was decided to model the H o s p i t a l ' s admissions and s c h e d u l i n g system and use computer s i m u l a t i o n to i n v e s t i g a t e i t s behaviour. P a t i e n t s , o p e r a t i n g rooms, and bed areas were c l a s s i f i e d by " h o s p i t a l s e r v i c e " . , A GPSS s i m u l a t i o n model which uses e m p i r i c a l data and a one-day time u n i t was developed. The model was v e r i f i e d and v a l i d a t e d . S e v e r a l experiments were performed to suggest d i f f e r e n t methods to r e g u l a t e occupancy i n the v a r i o u s h o s p i t a l areas, and to a l l e v i a t e s u r g i c a l s l a t e d i s r u p t i o n s , under e x i s t i n g or h y p o t h e t i c a l a r r i v a l p a t t e r n s f o r p a t i e n t s . These experiments were only a sample of those f o r which the model may be used. Suggestions f o r extensions of t h i s p r o j e c t are i n c l u d e d . In c o n c l u s i o n , two p o i n t s are made: f i r s t , t h e r e are s e v e r a l c o n t r a s t s between formal h o s p i t a l p o l i c y and a c t u a l p r a c t i c e as re v e a l e d by the data; second, i t appears that s i m u l a t i o n can be u s e f u l i n a h o s p i t a l c ontext. V TABLE OF CONTENTS A b s t r a c t i i i T a b l e o f Contents v L i s t of T a b l e s v i i i L i s t o f F i g u r e s i x acknowledgement x i i A b b r e v i a t i o n s x i v 1. INTRODUCTION 1 1.1 What Was t h e Problem? 1 1.2 C h a p t e r O u t l i n e s 1 2. PROJECT BACKGROUND INFORMATION 4 2.1 C o n c e p t i o n 4 2.2 I n i t i a t i o n 5 2.3 I n i t i a l F a m i l i a r i z a t i o n 6 2.4 P r a c t i c a l A p p l i c a t i o n s o f the Model 6 3. LITERATURE REVIEW 8 4. INTERPRETATION AND METHODOLOGY 27 4.1 B a s i c M e t h o d o l o g i c a l D e c i s i o n s 27 4.1.1 M a t h e m a t i c a l Method 27 4.1.2 Language 29 4.1.3 Time U n i t 3 0 4.1.4 L e v e l of A g g r e g a t i o n 31 4.1.5 E x t e n t of t h e Model 32 4.2 D i s t i n c t i v e F e a t u r e s o f t h i s P r o j e c t 33 5. THE HOSPITAL AND THE MODEL 35 5.1 D e f i n i t i o n o f Subsystems 35 5.1.1 H o s p i t a l S e r v i c e s 36 5.1.2 H o s p i t a l U n i t s 42 5.1.3 Bed Groups 45 5.2 A d m i t t i n g C o n s i d e r a t i o n s 47 5.2.1 Bed Usage 47 5.2.2 Sequence o f C l a i m s on Beds 48 5.2.3 "No Bed" S i t u a t i o n s 50 5.2.4 P a t i e n t A d m i s s i o n D i a g n o s t i c C a t e g o r i e s 51 v i 5.2.5 C o n t r o l of Medical Beds 53 5.2.6 S u r g i c a l Non-Operative admissions 54 5.2.7 General 55 5.3 S u r g i c a l Scheduling C o n s i d e r a t i o n s 55 5.3.1 Operating Rooms 56 5.3.2 Use of Information on the ad m i t t i n g Forms 56 5.3.3 Pre-Operative Stay 58 5.3.4 Block Booking 58 5.3.5 S e r v i c e C h a r a c t e r i s t i c s 59 5.3.6 L i m i t a t i o n s on Scheduling 60 5.3.7 C o n s i d e r a t i o n s of a u x i l i a r y S t a f f 62 5.3.8 I n - H o s p i t a l Demands 63 5.3.9 Handling of Emergencies 64 5.3.10 Timing of S l a t e C o n s t r u c t i o n 65 5.3. 11 General 6 5 6. MaJOB FLOW PATTERNS 67 6.1 Purpose and Form 67 6.2 Overview Flowchart 68 6.3 D e t a i l Flowcharts 71 7., THE DATA AND INFORMATION USE 87 7.1 D e s c r i p t i o n of Data-Sets 87 7.1.1 Waiting L i s t s 87 7.1.2 Operations 88 7.1.3 Length of Stay 91 7.1.4 Emergency Admissions 91 7.2 The S p e c i f i c a t i o n of Data and Information 92 7.3 Comments 100 8. THE MODEL IMPLEMENTATION 102 8.1 General Features 102 8.2 The Program Segments 106 8.2.1 Housekeeping Segments 106 8.2.2 P a t i e n t Generation 107 8.2.3 S u r g i c a l Request Handling 108 8.2.4 Medical Reguest Handling 112 8.2.5 S u r g i c a l admissions 112 8.2.6 Medical Admissions 114 8.2.7 Emergency Admissions 115 8.2.8 I n - H o s p i t a l T r a n s f e r s 117 8.2.9 Discharges 117 8.2.10 Operating Room Data 117 v i i 9. EVALUATION OF THE SIMULATION MODEL 119 9.1 Form of the Re s u l t s 119 9.2 V e r i f i c a t i o n 129 9.3 V a l i d a t i o n 133 10. EXPERIMENTS 146 10.1 Admission Strategy 146 10.2 Bed A l l o c a t i o n 148 10.3 Combining Bed Areas 149 10.4 Bequests f o r S p e c i f i c Surgery Dates 153 10.5 C l a s s i f i c a t i o n of P a t i e n t s 156 10.6 Number of P a t i e n t s 157 11. PROPOSALS FOR FOTURE CONSIDERATION 161 11.1 Data 161 11.2 Model M o d i f i c a t i o n and Expansion 163 11.3 Experiments 164 12. DISCUSSION 167 12 .1 System Lapses Revealed by Data 167 12.2 Value of S i m u l a t i o n i n a H o s p i t a l Context 169 - A Pe r s o n a l View L i s t o f References 172 Appendices 1.1 E a r l y S p e c i f i c a t i o n s f o r the Model 178 1.2 The B a s i c Information Flow 180 1.3 The P r o p o s a l t o St. Paul's H o s p i t a l 181 1.4 "Questions" t o Ask of the Model 184 2.1 Admitting O f f i c e Report 1976 185 2.2 P a t i e n t D i a g n o s t i c C a t e g o r i e s 187 2.3 P a t i e n t A r r i v a l D i s t r i b u t i o n s 189 2.4 P a t i e n t Sex and Age Groups 191 2.5 P a t i e n t Length of Stay 193 2.6 Length of Surgery 199 3 Program L i s t i n g 202 v i i i LIST OF TABLES I. Nursing U n i t s (June 1976) 37 I I . D a i l y S l a t e S u b d i v i s i o n s 38 I I I . H o s p i t a l S e r v i c e s 39 IV.. Beds by Sex 46 V. Operating Rooms 57 VI. Bed L i m i t G u i d e l i n e s 61 VII. I n - H o s p i t a l Demands f o r Surgery 61 V I I I . Data C o l l e c t i o n Groups 89 IX. Data and Information Used 93 X. User Chains 122 XI. Storages 123 XII. Queues 123 X I I I . Output Tables 125 XIV. Model Output Tables L i s t 126 XV. Halfword Matrices 128 XVI. T y p i c a l C r o s s - s e c t i o n of Waiting Times 168 XVII. Orthopedic P a t i e n t s 188 XVIII. Orthopedic A r r i v a l s 190 XIX. Sex of Orthopedics 191 XX. Orthopedic Male Age Groups 192 XXI. Orthopedic Female Age Groups 192 XXII. PAS LOS T a b u l a t i o n 194 XXIII. E m p i r i c a l LOS : Age 35-54 o r t h o p e d i c s 195 XXIV. Processed LOS : Age 35-54 Orthopedics 197 XXV. Orthopedic Length of Surgery 199 XXVI. Length of Surgery : Age 15-34 Orthopedics 201 i x LIST OF FIGUSES 6.1 Admission and OB Scheduling Information Flowchart CI) 69 6.2 Admission Requests Flowchart (IIA) 72 6.3 S u r g i c a l S e r v i c e s and Operating Rooms Flowchart <IIIA) 75 6.4 Medical S e r v i c e Flowchart (IVA) 79 6.5 Emergency Unit Flowchart (VA) 81 6.6 I n - H o s p i t a l V a r i a t i o n s Flowchart (VIA) 84 8.1 Flowchart f o r D a i l y Time Stream 105 8.2 Flowchart f o r F i r s t Desired Surgery Date 109 8.3 Flowchart f o r P l a c i n g Schedulable S u r g i c a l P a t i e n t s on the S l a t e 110 8.4 Flowchart f o r Admitting S u r g i c a l P a t i e n t s 113 8.5 Flowchart f o r Emergency Admissions 116 9.1 Medical "Immediate" P a t i e n t s (per 3 months) as a Function of Time 140 9.2 Medical Schedulable P a t i e n t Requests (per 3 months) as a Function of Time 140 9.3 Medical Area Discharges (per 3 months) as a Function of Time 141 9.4 Average Medical Queue Length (over 3 months) as a Function of Time 141 9.5 Medical P a t i e n t s Placed O f f - S e r v i c e (per 3 months) as a Function of Time 142 9.6 S u r g i c a l "No Bed" C a n c e l l a t i o n s (per 3 months) as a Function of Time 142 X 9.7 Medical "Immediate" P a t i e n t s (per 4 weeks) as a Function of Time 143 9.8 Medical Schedulable P a t i e n t Heguests (per 4 seeks) as a Function of Time 143 9.9 Medical Area Discharges (per 4 weeks) as a Function of Time 144 9.10 Average Medical Queue Length (over 4 weeks) as a Function of Time 144 9.11 Medical P a t i e n t s Placed O f f - S e r v i c e (per 4 weeks) as a Function of Time 145 9.12 S u r g i c a l "No Bed" C a n c e l l a t i o n s (per 4 weeks) as a Function o f Time 145 10.1 Average Medical Queue Length (over 4 weeks) as a Function o f Time : O r i g i n a l x ; Experiment o 150 10.2 S u r g i c a l "No Bed" C a n c e l l a t i o n s (per 4 weeks) as a Function o f Time : O r i g i n a l x ; Experiment o 150 10.3 S u r g i c a l "No Bed" C a n c e l l a t i o n s (per 4 weeks) as a Function of Time : O r i g i n a l x ; Experiment o 152 10.4 Average Use of "Overflow" Beds (over 4 weeks) as a Function of Time : O r i g i n a l x ; Experiment o 152 10.5 EENT S u r g i c a l Procedures (per 4 weeks) as a Function of Time : O r i g i n a l x ; Experiment o 154 10.6 Orthopedic S u r g i c a l Procedures (per 4 weeks) as a Function o f Time : O r i g i n a l x ; Experiment o 154 10.7 Average S u r g i c a l Queue Length (over 4 weeks) as a Function of Time : O r i g i n a l x ; Experiment o 155 10.8 Medical P a t i e n t s Placed O f f - S e r v i c e (per 4 weeks) x i as a Function of Time : O r i g i n a l x ; Experiment o 158 10.9 S u r g i c a l "No Bed" C a n c e l l a t i o n s (per 4 weeks) as a Function o f Time : O r i g i n a l x ; Experiment o 158 10.10 Average Use of "Overflow" Beds (over 4 weeks) as a Function of Time : O r i g i n a l x ; Experiment o 160 10.11 S u r g i c a l "No Bed" C a n c e l l a t i o n s {per 4 weeks) as a Function o f Time : o r i g i n a l x ; Experiment o 160 A 1.1 The Basi c Flowchart of i n f o r m a t i o n 180 A 2.1 Admitting O f f i c e Report 1976 186 A 2.2 Logarithmic P r o b a b i l i t y P l o t of LOS f o r Age 35-54 Orthopedics 196 x i i ACKNOWLEDGEMENT I wish t o express my a p p r e c i a t i o n to Drs. C h a r l e s A. L a s z l o and Dean H. Oyeno f o r p r o v i d i n g guidance i n t h i s undertaking. Dr. L a s z l o d i r e c t e d the approach, development, and p r e s e n t a t i o n of the p r o j e c t . In a d d i t i o n to p a r t i c i p a t i n g i n the gene r a l d i r e c t i o n of the p r o j e c t . Dr. Uyeno s u p e r v i s e d p a r t i c u l a r l y the computer modelling and s i m u l a t i o n a s p e c t s . A d d i t i o n a l advice on the p r o j e c t and on i t s p r e s e n t a t i o n i n t h i s t h e s i s came from Dr. R., A. Restrepo of the I n s t i t u t e of Applied Mathematics and S t a t i s t i c s , and Dr., J . H. Milsum of the D i v i s i o n of Health Systems. I am very g r a t e f u l t o Mr. Brian C u r t i s , Head of the Management Engineering Unit of the Greater Vancouver Region a l H o s p i t a l s f o r h i s e f f o r t s i n i n t r o d u c i n g me t o the St. Paul's H o s p i t a l system and to the personnel who would be of a s s i s t a n c e t h e r e , and f o r h i s c o n t i n u i n g i n t e r e s t i n the p r o j e c t . I am indebted to Dr. H. D. MacDonald, the Exe c u t i v e D i r e c t o r of S t . Pa u l ' s H o s p i t a l , Dr. E. G. Q. Van T i l b e r g , the Medical D i r e c t o r , and Mr. E. C. Emery, the D i r e c t o r of A d m i n i s t r a t i v e S e r v i c e s , f o r a c c e p t i n g our p r o j e c t proposal and f o r p r o v i d i n g me with access to the personnel and rec o r d s which would be of a s s i s t a n c e . A s p e c i a l word of thanks goes to the f o l l o w i n g people a t the h o s p i t a l , who generously provided o f t h e i r time and resources to answer my many guest i o n s : Miss Molly Smith, x i i i S u p e r v i s o r (Admitting Department); Miss Sandi Bruce, A d m i n i s t r a t i v e S u p e r v i s o r (OR); S i s t e r K. S t r a i n , S u r g i c a l Booking C l e r k ; Miss G a b r i e l l e Cornner, Unit Manager (Emergency U n i t ) ; and Miss P a t r i c i a Knight, C h i e f Medical Record L i b r a r i a n . Other people, too numerous to mention, provided a d d i t i o n a l a s s i s t a n c e at the h o s p i t a l and at the u n i v e r s i t y . I must express my g r a t i t u d e t o Miss Faye T a y l o r f o r t y p i n g the f i r s t d r a f t of the t h e s i s onto the computer. The s t a f f of the D i v i s i o n of Health Systems a l s o provided t e c h n i c a l a s s i s t a n c e i n the p r o d u c t i o n of the t h e s i s . F i n a l l y , I wish to thank Karen f o r being so w i l l i n g to share i n t h i s part of my l i f e t h a t she became my wife before the t h e s i s was complete. x i v ABBREVIATIONS CPHA Commission on P r o f e s s i o n a l and H o s p i t a l A c t i v i t i e s BO D i r e c t Urgent EENT Eye, Ear, Nose, and Throat E l E l e c t i v e ENT Ear, Nose, and Throat FIFO F i r s t I n , F i r s t Out GPSS General Purpose S i m u l a t i o n System H-ICDA I n t e r n a t i o n a l C l a s s i f i c a t i o n of Diseases - Appended ( H o s p i t a l Version) ICN I n t e n s i v e Care Nursery ICU I n t e n s i v e Care Unit LOS Length of Stay OR Operating Room PAR P o s t - A n a e s t h e t i c Recovery Room PAS P r o f e s s i o n a l A c t i v i t y Study (of CPHA) SU Semi-Urgent U Urgent 1 CHAPTEfi 1 INTRODUCTION 1.1 What Was the Problem? St. Paul's H o s p i t a l i n Vancouver, B r i t i s h Columbia i s an acute-care h o s p i t a l with a high occupancy l e v e l (an average of 93% o v e r a l l , but near c a p a c i t y i n most of the Medical / s u r g i c a l areas on weekdays). There i s a shortage of beds, but the h o s p i t a l admits a l l emergency p a t i e n t s who need to enter - although they must o f t e n be placed i n " o f f - s e r v i c e " beds. Unless these p a t i e n t s are t r a n s f e r r e d out o f the " o f f - s e r v i c e " beds, they o f t e n cause the c a n c e l l a t i o n s of s c h e d u l a b l e p a t i e n t s who should have been placed t h e r e . On the other hand, St. Paul's has more o p e r a t i n g rooms than i t needs. T h i s t h e s i s d i s c u s s e s a study of the p a t i e n t admissions and s c h e d u l i n g system at St. P a u l ' s H o s p i t a l . A computer model of the system was designed f o r experimentation with d i f f e r e n t methods to r e g u l a t e occupancy i n the v a r i o u s h o s p i t a l areas, and to a l l e v i a t e s u r g i c a l s l a t e d i s r u p t i o n s , under e x i s t i n g or h y p o t h e t i c a l a r r i v a l p a t t e r n s f o r p a t i e n t s . 1.2 Chapter O u t l i n e s Chapter 2 d i s c u s s e s the background of the p r o j e c t . By p r o v i d i n g d e t a i l s of the purpose and motivation f o r the p r o j e c t , i t demonstrates t h a t the undertaking was intended t o be p r a c t i c a l r a t h e r than t h e o r e t i c a l . 2 Chapter 3 i s an overview of the l i t e r a t u r e which was p e r t i n e n t to the development of t h i s p r o j e c t . Most of the chapter d e s c r i b e s e x i s t i n g mathematical models of v a r i o u s h o s p i t a l f a c i l i t i e s , with a p a r t i c u l a r emphasis on computer s i m u l a t i o n models. , Chapter 4 d i s c u s s e s the i n t e r p r e t a t i o n of the St. Paul's H o s p i t a l problem and the methodology which was used to i n v e s t i g a t e i t . B a s i c m e t h o d o l o g i c a l d e c i s i o n s which were made are presented, together with an e x p l a n a t i o n of those f e a t u r e s which d i f f e r e n t i a t e t h i s p r o j e c t from those d e s c r i b e d i n the l i t e r a t u r e . Chapter 5 i s an i n - d e p t h e x p l a n a t i o n of those f a c i l i t i e s and processes i n St. Paul's H o s p i t a l which are r e l e v a n t to the development of the model. P a r t i c u l a r a t t e n t i o n i s paid to the admission and s u r g i c a l s c h e d u l i n g processes. Chapter 6 presents the major i n f o r m a t i o n p a t t e r n s i n the h o s p i t a l , by means of a s e t of f l o w c h a r t s . Chapter 7 i s a d i s c u s s i o n of the data and i n f o r m a t i o n from St. Paul's which were used i n the model. a s p e c t s of both the c o l l e c t i o n and analyses of these data are pointed out. Chapter 8 d e s c r i b e s the a c t u a l computer implementation of the model. Noteworthy concepts are e x p l a i n e d , and t h e r e i s a b r i e f summary of the d e t a i l s of the model. Chapter 9 i s an e v a l u a t i o n of the s i m u l a t i o n model., F i r s t , the form of the output of the model i s e x p l a i n e d . Then, d e t a i l s of the v e r i f i c a t i o n and v a l i d a t i o n of the model are provided. Chapter 10 d e s c r i b e s s e v e r a l experiments which were 3 performed with the model, and analyzes t h e i r r e s u l t s . The s e l e c t i o n of these experiments was intended t o demonstrate p a r t of the range of s i t u a t i o n s which the model may be used to i n v e s t i g a t e . Chapter 11 suggests s e v e r a l i d e a s t o update, extend, and experiment with the model i n the f u t u r e . In p a r t i c u l a r , the model may be improved and made more p r a c t i c a l l y u s e f u l by means of newer data and renewed d i s c u s s i o n s with St. Paul's a d m i n i s t r a t i o n . Chapter 12 i s a c o n c l u d i n g d i s c u s s i o n . Two p o i n t s are made: f i r s t , the data r e v e a l a few l a p s e s i n the h o s p i t a l system between formal h o s p i t a l p o l i c y and a c t u a l p r a c t i c e ; second, from my vantage p o i n t i t appears that s i m u l a t i o n can be u s e f u l i n a h o s p i t a l context. 4 CHAPTER 2 PROJECT BACKGROUND INFORMATION T h i s chapter b r i e f l y d e s c r i b e s the e a r l y h i s t o r y o f the St. Paul*s s i m u l a t i o n p r o j e c t . T h i s background demonstrates t h a t the basi c m o t i v a t i o n behind t h i s undertaking was p r a c t i c a l r a t h e r than t h e o r e t i c a l . 2. 1 Conception The i d e a o f a p p l y i n g the techniques of modelling and computer s i m u l a t i o n to problems of S t . Paul's H o s p i t a l arose from d i s c u s s i o n s between Mr. B r i a n C u r t i s (Head of the Management Engineering Unit o f the Greater Vancouver Regional H o s p i t a l s ) and Dr. C h a r l e s L a s z l o ( A s s o c i a t e D i r e c t o r of the D i v i s i o n of Health Systems at UBC). Mr., C u r t i s l i s t e d s e v e r a l o b j e c t i v e s and data requirements of such a model. A general flow diagram was a l s o produced. The s p i r i t of these suggestions was maintained i n b u i l d i n g the a c t u a l model, and t h e r e f o r e they are i n c l u d e d i n Appendix 1 . 1 . The main o b j e c t i v e was t o model p a t i e n t flow i n and through the h o s p i t a l . Experiments with the model would serve as guides f o r c o n t r o l l i n g the admission r a t e and placement of p a t i e n t s i n order to r e g u l a t e occupancy and to a l l e v i a t e s u r g i c a l s l a t e d i s r u p t i o n s . 5 2.2 I n i t i a t i o n A f t e r the i n i t i a l d i s c u s s i o n s , the p r o j e c t was not pursued f u r t h e r f o r about a year because manpower with s u i t a b l e t e c h n i c a l a b i l i t y was not a v a i l a b l e . In Hay 1976, I became f a m i l i a r with the p r o j e c t and decided to undertake i t s development w i t h i n the framework of a Master's T h e s i s program i n Ap p l i e d Mathematics. The f i r s t task was t o c l a r i f y the i n t e r a c t i o n between ad m i t t i n g p h y s i c i a n s {and the Emergency U n i t ) , the Admitting O f f i c e , the Operating Room (OR) Booking O f f i c e , and the bed areas. A r e v i s e d v e r s i o n of the o r i g i n a l g e n e r a l i n f o r m a t i o n flow diagram, which connects these e n t i t i e s , appears i n Appendix 1.2. The second task was to e s t a b l i s h the terms of r e f e r e n c e of the working r e l a t i o n s h i p with S t . Paul's H o s p i t a l . T h e r e f o r e a proposal was submitted t o Dr. Van T i l b e r g , Medical D i r e c t o r of the h o s p i t a l (Appendix 1.3) , suggesting i n v e s t i g a t i o n of problems of a l l o c a t i o n and u t i l i z a t i o n of o p e r a t i n g rooms, beds, and Medical personnel, and s c h e d u l i n g of s u r g i c a l p a t i e n t s . The a c t u a l development of the p r o j e c t c l o s e l y f o l l o w e d t h i s p roposal. Ready support, s p r i n k l e d with some s k e p t i c i s m , was forthcoming from s e v e r a l a d m i n i s t r a t i v e l e v e l s . We were given permission t o proceed with the p r o j e c t , and were assured of access to key personnel and data. 6 2.3 I n i t i a l F a m i l i a r i z a t i o n The rough d r a f t of a working paper on a d m i t t i n g a t St. Paul's {Brian C u r t i s , May 1976) and s t u d i e s done on OB s t a t i s t i c s {Lee and westerheim 1974), on bed a l l o c a t i o n and booking (Gallager 1973), and on t r a n s f e r s (Scroggs 1970) served as the s t a r t i n g p o i n t s f o r understanding the system a t St. Paul's. There was a l s o a l a r g e data f i l e drawn from p a t i e n t case a b s t r a c t s (see S e c t i o n 7.1.3), which was t o prove v a l u a b l e i n p r o v i d i n g l e n g t h - o f - s t a y (LOS) i n f o r m a t i o n . Furthermore, I was i n t r o d u c e d to knowledgeable personnel i n the Admitting O f f i c e , OB s u p e r v i s i o n and booking, the Emergency Department, and the M e d i c a l Records L i b r a r y . 2.4 P r a c t i c a l a p p l i c a t i o n s of the Model From the p r a c t i c a l point of view, the model i s intended to produce a r e a l i s t i c s i m u l a t i o n of events i n the h o s p i t a l as c e r t a i n system parameters vary. These v a r i a t i o n s may a r i s e e i t h e r i n a c o n t r o l l e d manner due t o m o d i f i c a t i o n s i n h o s p i t a l p o l i c y or s t r u c t u r e , or i n an unexpected f a s h i o n due to changes o u t s i d e the h o s p i t a l environment. Thus, the model i s expected to produce responses to v a r i o u s " q u e s t i o n s " which might be imposed by such s i t u a t i o n s . For example: - Can the a l l o c a t i o n of beds to s e r v i c e s be a l t e r e d to i n c r e a s e the throughput of p a t i e n t s ? - I f the number of p a t i e n t s i n c r e a s e s , what happens to the 7 w a i t i n g l i s t ? - What happens i f some o f the OR's are c l o s e d ? - What impact would an i n c r e a s e d number of p a t i e n t s have on the volume o f s u r g e r i e s per room and number of "No Bed" occurrences? - What happens i f emergency admissions vary i n number? - What happens i f i n - p a t i e n t t r a n s f e r s vary i n number? A more d e t a i l e d l i s t of q u e s t i o n s may be found i n Appendix 1.4.. 8 CHAPTER 3 LITERATURE REVIEW Extensive l i t e r a t u r e e x i s t s on a l l a s p e c t s o f the a p p l i c a t i o n of o p e r a t i o n s r e s e a r c h techniques i n h o s p i t a l s . For example, i n t h e i r book, QEerat i o n s Research i n H o s p i t a l s ; Diagnosis and P r o g n o s i s , David and Ruth Stimson i n c l u d e over 500 b i b l i o g r a p h i c c i t a t i o n s . To review the s t u d i e s done, they i d e n t i f y seven c a t e g o r i e s . One of these: "admission, d i s c h a r g e , and u t i l i z a t i o n of i n p a t i e n t f a c i l i t i e s " i s of p a r t i c u l a r r e l e v a n c e to t h i s p r o j e c t . A more r e c e n t study i s Operations Research In Health Care: A C r i t i c a l A£££oach, (19 75) e d i t e d by Shuman e t a l . I t i n c l u d e s a set o f l i t e r a t u r e reviews which, without i n t e n d i n g to be complete, i n c l u d e over 1000 b i b l i o g r a p h i c c i t a t i o n s . The chapters on " s i m u l a t i o n " and " s t o c h a s t i c processes" are p a r t i c u l a r l y p e r t i n e n t to t h i s p r o j e c t . Anyone wishing to search beyond the range of t h i s p a r t i c u l a r t h e s i s i s l i k e l y t o f i n d each of these books q u i t e h e l p f u l . Two other a r t i c l e s of a general or r e f e r e n c e nature should a l s o be mentioned. Milsum et a l (1973) present a h o l i s t i c a n a l y s i s of h o s p i t a l management admission systems. The authors i n c l u d e a u s e f u l t a b u l a r d i s p l a y of the c h a r a c t e r i s t i c f e a t u r e s of eleven of the major m o d e l l i n g and s i m u l a t i o n developments p e r t i n e n t t o t h e i r d i s c u s s i o n . The most r e c e n t b i b l i o g r a p h y t o appear on " p a t i e n t s c h e d u l i n g " i s t h a t by Kohler et a l (1977) which l i s t s 163 papers r e l e v a n t to the problem of w a i t i n g l i n e s i n h o s p i t a l s . 9 T h i s review i s limited, to those groups of a r t i c l e s which are s p e c i f i c a l l y r e l e v a n t to the development of t h i s t h e s i s . The f i r s t group i s on h o s p i t a l data and t h e i r a n a l y s e s . The second group of a r t i c l e s provides e a r l y d i s c u s s i o n s on " f o r e c a s t i n g bed needs". The t h i r d group i s devoted to r e l a t i v e l y s o p h i s t i c a t e d models of v a r i o u s a s p e c t s of h o s p i t a l care. I t i n c l u d e s s t o c h a s t i c models, a h o s p i t a l - b a s e d study model. Young's queuing theory models, and models employing Markov processes. V a r i o u s computer models are a l s o reviewed i n some d e t a i l . B a l i n t f y (196 0) p u b l i s h e d one of the f i r s t d i s c u s s i o n s on the s t o c h a s t i c d i s t r i b u t i o n s r e l a t e d to h o s p i t a l admissions and d i s c h a r g e s . He argued on t h e o r e t i c a l and e m p i r i c a l grounds t h a t the d i s t r i b u t i o n of d a i l y a r r i v a l s , which c o u l d be c o n s i d e r e d a Poisson process, i s more a c c u r a t e l y d e s c r i b e d by the negative b i n o m i a l d i s t r i b u t i o n . He reasoned t h a t the d i s t r i b u t i o n of LOS should be lognormal, which compares w e l l with h i s observed data. F i n a l l y , he suggested the negative binomial d i s t r i b u t i o n f o r d a i l y d i s c h a r g e s . From these, he d e s c r i b e d the p o s s i b i l i t y of p r e d i c t i n g changes i n the system. Admissions t o a c a s u a l t y ward were analyzed by P i k e et a l (1963). They noted t r a n s f e r s and s h o r t - s t a y p a t i e n t s and analyzed admission numbers by day-of-the-week and by month. They found t h a t a good " f i t " t o e m p i r i c a l data was obtained with a Poisson d i s t r i b u t i o n f o r d a i l y a r r i v a l s and a geometric d i s t r i b u t i o n f o r LOS. A Poisson d i s t r i b u t i o n then r e s u l t e d f o r the number of beds occupied. 10 McCorkle (1966) d i d an e x t e n s i v e g r a p h i c a l p r e s e n t a t i o n of i n - p a t i e n t LOS i n v a r i o u s h o s p i t a l departments. Besides the v a r i o u s Medical and s u r g i c a l s p e c i a l t i e s , groups were subd i v i d e d according to treatment by a s t a f f or p r i v a t e p h y s i c i a n . , Lew (1966) t e s t e d the s t a t i s t i c a l s i g n i f i c a n c e of c e r t a i n v a r i a b l e s which r e l a t e to admissions, d i s c h a r g e s , and LOS, and might seem unimportant t o a p a t i e n t ' s h e a l t h c a r e . For example, he found t h a t the day-of-the-week of admission had a s i g n i f i c a n t e f f e c t on LOS, that the admission d i a g n o s t i c category of a p a t i e n t had a s m a l l e f f e c t , and t h a t the type of accommodation had very l i t t l e e f f e c t . Dunn (1967) repo r t e d on an admission s c h e d u l i n g procedure. The procedure accounted f o r such t h i n g s as what the admission type (urgency) of the p a t i e n t was, and which h o s p i t a l s e r v i c e s (such as OE procedures) were r e q u i r e d . The computerized a n a l y s i s produced graphs of t h e number o f beds a v a i l a b l e over a two-year p e r i o d . In an e f f i c i e n t h o s p i t a l i t i s d e s i r a b l e t o have high average occupancy and i n f r e q u e n t o v e r l o a d or "No Bed" s i t u a t i o n s , , Drosness et a l (1967) considered the use of the d a i l y census to o p t i m i z e c a p a c i t y . T h e i r work was on a s m a l l h o s p i t a l , but they suggested t h a t f o r a l a r g e h o s p i t a l t h e d a i l y census data would change from f i t t i n g a normal d i s t r i b u t i o n t o f i t t i n g a t r u n c a t e d Poisson d i s t r i b u t i o n . LOS i s one of the main v a r i a b l e s a f f e c t i n g occupancy. A d m i n i s t r a t o r s who can p r e d i c t LOS f a i r l y a c c u r a t e l y can do a more e f f e c t i v e admission s c h e d u l i n g job. In 1968, David 11 Gustafson d i d a s m a l l comparative study on f i v e methods of e s t i m a t i n g p a t i e n t LOS, These were d i r e c t estimates by the p h y s i c i a n s , r e g r e s s i o n a n a l y s i s , h i s t o r i c a l average, d i r e c t p o s t e r i o r odds e s t i m a t i o n , and Bayes* Theorem with three v a r i a t i o n s . The l a s t method was the best. I n i t , the p h y s i c i a n estimated the p r o b a b i l i t y t h a t a p a t i e n t would be discharged on a c e r t a i n day, given demographic and symptomatic c h a r a c t e r i s t i c s . He d i d so by su g g e s t i n g the l i k e l i h o o d s of these "independent" c h a r a c t e r i s t i c f e a t u r e s , supposing that the LOS was al r e a d y known, T h i s p r e d i c t i o n method r e q u i r e d some t r a i n i n g and took time f o r the p h y s i c i a n . Gustafson e x p l a i n e d why the s u b j e c t i v e methods were b e t t e r . T r a i n i n g and o n - l i n e computer f a c i l i t i e s c o u l d s u b s t a n t i a l l y reduce the p h y s i c i a n time i n v o l v e d . A l s o i n 1968, B i t h e l l and D e v l i n presented a study on p r e d i c t i o n of d i s c h a r g e s . They d i s c u s s e d the accuracy of i n i t i a l LOS estimates by the p h y s i c i a n , and the improvement caused by r e v i s i o n of these estimates p e r i o d i c a l l y d u r i n g the p a t i e n t ' s s t a y . LOS i n a mental h o s p i t a l was the s u b j e c t of Hanson's model i n 1973. He found the LOS d i s t r i b u t i o n t o be lognormal, and used separate means and v a r i a n c e s a s s o c i a t e d with d i f f e r e n t diagnoses. F o r e c a s t i n g of bed needs i s the s o l e t o p i c of the f o l l o w i n g three e a r l y papers. Most of the subseguent papers a l s o i n c l u d e t h a t concern w i t h i n t h e i r scope. In 1963, Johnson was pleased with a 90% accurate p r e d i c t i v e method based on area p o p u l a t i o n 12 and h i s t o r i c a l p a t t e r n s . Beenhakker and Brooks (1964) developed a much more powerful method f o r p r e d i c t i n g bed needs i n seventeen c l a s s i f i c a t i o n s , by r e g r e s s i o n a n a l y s i s on 117 f a c t o r s ! In a study of the demand f o r h o s p i t a l beds i n v a r i o u s r e g i o n s of England, Newell (1964) d i s c o v e r e d that the supply of h o s p i t a l beds a f f e c t s the demand f o r them. I t has been suggested t h a t the adjustment i s e f f e c t e d v i a p a t i e n t LOS. As a r e s u l t , Newell doubted the a b i l i t y of queuing t h e o r y models t o y i e l d u s e f u l e stimates of bed requirements. There have been many models developed f o r d i f f e r e n t aspects of a h o s p i t a l ' s o p e r a t i o n . T h i s t h e s i s i s concerned p r i m a r i l y the a n a l y s i s of a p a r t i c u l a r h o s p i t a l . The work of Shonick, however, deserves mention f o r i t s g e n e r a l l y a p p l i c a b l e c a l c u l a t i o n s o r i e n t e d t o area-wide p l a n n i n g . His models co n s i d e r e d emergency and e l e c t i v e a r r i v a l s at a Poisson r a t e . LOS was taken from a n e g a t i v e e x p o n e n t i a l d i s t r i b u t i o n . O p t i m i z a t i o n of the bed complement was with r e s p e c t to percentage occupancy, o v e r f i l l , and queue s i z e . Shonick (1970) used t h i s model to develop census, queue l e n g t h , and waiting-time d i s t r i b u t i o n s . , In 1973 Shonick and Jackson improved the model by i n c o r p o r a t i n g a c u t - o f f p o i n t f o r a s p e c i f i c number of beds above which e l e c t i v e s would be made to wait and only emergencies would be admitted, and by adding a v a r i a t i o n wich permitted emergency overflow to an u n l i m i t e d number of "non-approved" beds. In t h e i r book Computing and Q E e r a t i o n a l Research at The London H o s p i t a l (1972), Barber and Abbott i n c l u d e a chapter on 13 o p e r a t i o n a l r e s e a r c h s t u d i e s of which one i s an "admission-discharge study". A m u l t i - d i s c i p l i n a r y group w i t h i n the h o s p i t a l worked from 1966 t o 1969 to d e f i n e a model and t o a l l e v i a t e problems r e l a t e d t o high occupancy. The group a c t u a l l y implemented s e v e r a l system m o d i f i c a t i o n s , and examined the r e s u l t s . They found that the b e s t measure of the s t r a i n on the system was the number o f a v o i d a b l e t r a n s f e r s . The study concluded that "the r e d u c t i o n of the l e v e l of acceptance of waiting l i s t admissions i s the only o v e r a l l c o n t r o l open to the a d m i n i s t r a t i o n " . (Page 40, Barber and Abbott, 1972) Young was probably the f i r s t t o apply formal mathematical a n a l y s i s t o the problem of occupancy s t a b i l i z a t i o n given e l e c t i v e and emergent p a t i e n t streams. In 1965 and 1966 he presented a queuing theory model with p a r a l l e l s e r v i c e f a c i l i t i e s (beds) and two p a r a l l e l input streams, one corresponding t o emergency a r r i v a l s (at a P o i s s o n r a t e ) , the other to e l e c t i v e (scheduled) admissions i n an L-phase Erlang process - which may r e p r e s e n t d e t e r m i n i s t i c or P o i s s o n r a t e a r r i v a l s . The LOS i s taken to be d i s t r i b u t e d as a gamma v a r i a b l e . Young compared a r a t e - c o n t r o l model and an a d a p t i v e c o n t r o l model. In the f i r s t , the i n p u t r a t e of scheduled admissions was s e t . Standard methods of a n a l y s i s y i e l d e d overflow and turnaway p r o b a b i l i t i e s . In the feedback c o n t r o l model, scheduled a r r i v a l s c o n s t i t u t e d a d e t e r m i n i s t i c stream which depended on the occupancy. Scheduled admissions were brought i n t o keep the h o s p i t a l a t a c e r t a i n occupancy l e v e l , but above t h a t c u t - o f f p o i n t no scheduled admissions were 14 allowed. Again, s t a n d a r d queuing theory equations f o r " b i r t h and death processes" y i e l d e d s t e a d y - s t a t e p r o b a b i l i t i e s . U n f o r t u n a t e l y , Young's assumption of e x p o n e n t i a l l y - d i s t r i b u t e d LOS ( s e r v i c e time) and i n t e r - a r r i v a l times are u s u a l l y u n s a t i s f a c t o r y r e p r e s e n t a t i o n s of r e a l i t y . , B i t h e l l (1969 a S b) used Markov processes to study the same s i t u a t i o n as Young had. His f i r s t paper developed p e r t i n e n t s t a t i s t i c s to a i d i n a n a l y s i s . He found t h a t f o r d e t e r m i n i s t i c admissions, the v a r i a n c e of the occupancy was p r o p o r t i o n a l t o the standard d e v i a t i o n of the LOS. For e l e c t i v e admissions based on a continuous a p p r a i s a l of the c u r r e n t bed-state, the occupancy vari a n c e equals the emergency admissions v a r i a n c e p l u s a f a c t o r depending on the v a r i a b i l i t y of d i s charge. In the second paper, he d i s c u s s e d the advantages of using d i s c r e t e - t i m e (Markov) processes, and t a i l o r e d the two models to p a r t i c u l a r week-day events. The "adaptive c o n t r o l " model was found to reduce the occupancy v a r i a n c e s i g n i f i c a n t l y , c o n t r i b u t i n g t o improved e f f i c i e n c y . In 1970, Kolesar f u r t h e r r e f i n e d Young's model, with a Markov d e c i s i o n aspect and a l i n e a r program. He f i r s t pointed out t h a t i f Young's Poisson processes are r e p l a c e d by more general ones, and i f the c o n t r o l r u l e s are made more complex, queuing theory a n a l y s i s c o l l a p s e s . Kolesar s t e e r e d c l e a r of computer s i m u l a t i o n , s i n c e he c o n s i d e r e d them t o be very d i f f i c u l t and o f t e n only s p e c i f i c a l l y a p p l i c a b l e t o the s i t u a t i o n s t u d i e d . (He admitted s i m u l a t i o n was p o t e n t i a l l y f r u i t f u l - c i t i n g F e t t e r and Thompson's work.) He p r e f e r r e d a 15 Harrovian model f o r i t s f l e x i b i l i t y i n the use of d i s t r i b u t i o n s and d e c i s i o n r u l e s . That method can obtain "good" r u l e s e f f i c i e n t l y . I n c o r p o r a t i n g a l i n e a r programming problem, he posed such problems as: How many p a t i e n t s should be scheduled f o r admission each day i n order to: i . , maximize average occupancy with an overflow c o n s t r a i n t , and i i . minimize overflow with u t i l i z a t i o n c o n s t r a i n t s ? K o l e s a r even mentioned the minor v a r i a t i o n s necessary to s i m u l t a n e o u s l y schedule f o r s e v e r a l s e r v i c e s . R e s u l t s could be l i s t e d i n a d e c i s i o n t a b l e as an a d m i n i s t r a t i v e a i d . Markovian a n a l y s i s has a l s o been a p p l i e d to other r e l a t e d f i e l d s . Thomas (1968) a p p l i e d Markovian a n a l y s i s t o coronary p a t i e n t recovery, i d e n t i f y i n g f o u r recovery s t a t e s each s u b d i v i d e d i n t o t h r e e phases to account f o r the time i n each s t a t e ( s i n c e Markov processes are memory-less). From h i s LOS a n a l y s i s he found t h a t p a t i e n t s who recover have a lognormal s t a y d i s t r i b u t i o n , while t h o s e who d i e have a negative e x p o n e n t i a l one. Kao (1972) decided that Thomas's model with i t s awkward "phases" should be r e f i n e d . He added a h o l d i n g time a c c o r d i n g to the LOS d i s t r i b u t i o n i n the f o u r s t a t e s , y i e l d i n g a t r a n s i e n t semi-Markov process model. His model even p r e d i c t e d the census mix. In 1973, Kao c o n s i d e r e d the p a t i e n t ' s path of movement w i t h i n a u n i t . In a 1974 paper, Kao used both a Markov renewal process and s i m u l a t i o n to decide whether to admit a p a t i e n t to a 16 coronary care u n i t or t o t r e a t him elsewhere i n the h o s p i t a l , with the o b j e c t i v e of minimizing m o r t a l i t y . Another Markovian a n a l y s i s , i n t e r e s t i n g f o r i t s output v a r i a b l e s , d e a l t with a g e r i a t r i c ward. Meredith (1973) developed a simple model c o n s i d e r i n g f i v e main s t a t e s , with t h e i r t r a n s i t i o n p r o b a b i l i t i e s and c o s t s . Some of the output v a r i a b l e s were r e c u r r e n c e time, cost u n t i l death, and expected stay. The remainder of t h i s review i s devoted to computer models which are s i m u l a t i o n s f o r the most p a r t , but some which are designed f o r a d a p t a t i o n or d i r e c t use o n - l i n e i n an Admitting O f f i c e environment. I t i s i n t e r e s t i n g t o note t h a t , of the s i m u l a t i o n s f o r which the language used was noted, GPSS, SIMSCRI.PT and FORTRAN had roughly egual usage. The most f r e q u e n t l y c i t e d s t u d i e s are those by F e t t e r and Thompson, who i n 1965 presented a t h r e e - p a r t SIMSCRIPT s i m u l a t i o n of a maternity s u i t e , a s u r g i c a l p a v i l i o n and an o u t p a t i e n t c l i n i c . In the maternity s u i t e they found t h a t i f a p r o p o r t i o n of the admissions c o u l d be scheduled, i t would smooth occupancy and reduce bed requirements. In 1969, they proposed a model of an e n t i r e p r o g r e s s i v e care h o s p i t a l i n which the p a t i e n t moved through d i f f e r e n t zones depending on h i s s t a t e of h e a l t h . They argued that i f the p r o b a b i l i t y f o r changinq zones depended only on the present zone occupied, Markovian a n a l y s i s would s u f f i c e . However, s i n c e i t a l s o depends on the admission zone and the h i s t o r y of zones occupied, s i m u l a t i o n was necessary. One output of t h i s GPSS s i m u l a t i o n was a set of 17 p r o b a b i l i t i e s f o r v a r i o u s l e v e l s of bed u t i l i z a t i o n i n each zone. The r e s u l t s of the s i m u l a t i o n d e f i n e d parameters f o r a budget-constrained l i n e a r programming model designed t o optimize o v e r a l l bed u t i l i z a t i o n . The OS N a t i o n a l Center f o r Health S t a t i s t i c s produced a computer s i m u l a t i o n of h o s p i t a l discharges i n 1966. The Center had p r e v i o u s l y s t a r t e d a Health I n t e r v i e w Survey used to estimate the number of annual h o s p i t a l - d i s c h a r g e s , and wished to use the s i m u l a t i o n to examine the f a c t o r s c a using d i s c r e p a n c i e s between the response and r e a l i t y i n order t o improve the survey. The choice of s t o c h a s t i c d i s t r i b u t i o n s may be of i n t e r e s t . . The annual number of h o s p i t a l i z a t i o n s f o r an i n d i v i d u a l was taken t o be the outcome of a Poisson p r o c e s s , whose parameter was c o n s i d e r e d to vary over the p o p u l a t i o n as a gamma v a r i a b l e . Hence, the p o p u l a t i o n ' s number of h o s p i t a l episodes per year was negative b i n o m i a l i n d i s t r i b u t i o n . LOS was found to be lognormal, with the d i s c h a r g e p r o b a b i l i t y c o n d i t i o n a l on the time already spent i n the h o s p i t a l . Handyside and Morris (1967) simulated an emergency department. , They were s a t i s f i e d with a Poisson a r r i v a l r a t e , but f e l t t h a t e m p i r i c a l LOS data d i d not f i t d i s t r i b u t i o n s proposed i n the l i t e r a t u r e . The department being c o n s i d e r e d had operated only when i t was needed. The authors examined the e f f e c t s of v a r i o u s p o l i c i e s which d e f i n e d the sequence o f days of use on the s t a b i l i z a t i o n of bed occupancy. A SIMSCRIPT s i m u l a t i o n of a m u l t i p l e OR system, by Barnoon and Wolfe, appeared i n 1968. T h e i r h o s p i t a l had l i m i t e d beds 18 but excess o p e r a t i n g rooms. They assigned an OR, an a n a e s t h e t i s t and nurses to cases ( a f t e r bed s e l e c t i o n ) . By p l a c i n g values on each of these s e r v i c e s they examined the c o s t s of v a r i o u s a l t e r n a t i v e s . Robinson e t a l (1968) e v a l u a t e d three s c h e d u l i n g systems with a t o t a l of s i x v a r i a t i o n s and compared the average d a i l y c o s t s of o p e r a t i o n ( i n terms of empty beds, overflow and turnaway) at t h e i r o p t i m a l o p e r a t i n g l e v e l s . , The s i m u l a t i o n c o n s i s t e d of three phases: a reguest generator to produce p a t i e n t s and t h e i r a t t r i b u t e s , a s e c t i o n to schedule these p a t i e n t s , and an e v a l u a t i o n s e c t i o n to f i n d the optimal o p e r a t i n g l e v e l f o r given c o s t s and a g i v e n s c h e d u l i n g r u l e . The f i r s t two s e c t i o n s were w r i t t e n i n SIMSCRIPT and the l a s t i n FORTRAN. Only e l e c t i v e p a t i e n t s were co n s i d e r e d . The authors thought t h a t a reasonable p o l i c y to account f o r emergency p a t i e n t s would be to merely a l l o c a t e them a f i x e d block of beds and to proceed as b e f o r e . The number o f beds was taken to be the only s c h e d u l i n g c o n s t r a i n t . I t was suggested that OR booking could be implemented by using a v a i l a b l e o p e r a t i n g time to d e f i n e or modify the p a t i e n t ' s d e s i r e d admission day. Each p a t i e n t was "generated" with an e a r l i e s t p o s s i b l e a r r i v a l date and l a t e s t p o s s i b l e a r r i v a l date assigned on a f a i r l y a r b i t r a r y b a s i s , s i n c e no data were a v a i l a b l e . The t h r e e b a s i c scheduling a l t e r n a t i v e s were: i . " F i l l e d page", which i s analogous to using a book to r e c o r d scheduled admissions, by w r i t i n g a p a t i e n t ' s name i n t o the f i r s t requested day t h a t has an open e n t r y . 19 i i . A method which used an estimated LOS as i f i t were exact, and p r o j e c t e d the census. The p a t i e n t was scheduled f o r the e a r l i e s t requested day f o r which h i s a d d i t i o n would not overload the h o s p i t a l census. i i i . A method which had a p r o b a b i l i t y t a b l e to i n c o r p o r a t e c o n d i t i o n a l p r o b a b i l i t i e s of a c t u a l LOS given the estimated value. I t was an e x t e n s i o n of the above method, a d m i t t i n g the p a t i e n t a c c o r d i n g to "expected census" f i g u r e s . V a r i a t i o n s i n the s c h e d u l i n g system allowed f o r d i f f e r e n t l e v e l s of accuracy i n the e s t i m a t i o n of LOS. The second method with good e s t i m a t e s , or r e v i s i o n s allowed, performed best. I t was noted t h a t p a t i e n t s d e s i r i n g admission q u i c k l y were o f t e n turned away. I t was suggested that the scheduler program could be the core of a r e a l - t i m e p a t i e n t s c h e d u l i n g system. Goldman et a l (1968) s t u d i e d v a r i o u s bed a l l o c a t i o n p o l i c i e s i n r e l a t i o n t o u t i l i z a t i o n l e v e l s , using FORTRAN IV. They begin t h e i r d i s c u s s i o n with the f o l l o w i n g noteworthy comments: " I t can be mathematically shown that the p o l i c y of a l l o c a t i n g beds i n any manner leads to a degradation i n o v e r a l l u t i l i z a t i o n . . Why, then, a l l o c a t e beds? The p r i n c i p a l advantage of bed a l l o c a t i o n i s the p o t e n t i a l e f f i c i e n c y t o be d e r i v e d from grouping p a t i e n t s with s i m i l a r h e a l t h problems i n the same p h y s i c a l area, convenient to the f a c i l i t i e s and s e r v i c e s they r e q u i r e . P a t i e n t grouping a l s o a l l o w s h o s p i t a l personnel to develop s p e c i a l i z e d s k i l l s i n the performance of t h e i r p a t i e n t care f u n c t i o n s ; and s i n c e the p r a c t i c e of Medicine i s s u b d i v i d e d i n the same manner, the p h y s i c i a n can decrease h i s t r a v e l time between p a t i e n t s by c o n c e n t r a t i n g h i s p a t i e n t s i n one p h y s i c a l area." "In some circumstances, the Medical c o n d i t i o n of the p a t i e n t d i c t a t e s i s o l a t i o n i n a p r i v a t e 20 room; and s o c i a l custom d i c t a t e s t h e s e p a r a t i o n of p a t i e n t s by sex and p o s s i b l y by age. P a t i e n t p r e f e r e n c e s and f i n a n c i a l c o n s i d e r a t i o n s may a l s o be i n v o l v e d . , Some o b v i o u s d i s a d v a n t a g e s a r e a s s o c i a t e d w i t h any a l l o c a t i o n p o l i c y . . Among th e s e a r e (1) a p o s s i b l e r e d u c t i o n i n t o t a l bed u t i l i z a t i o n ; (2) a p o t e n t i a l i n c r e a s e i n p a t i e n t s w a i t i n g f o r a d m i s s i o n ; (3) t r a n s f e r problems c r e a t e d by t h e attempt t o m a i n t a i n any t y p e of p a t i e n t s e g r e g a t i o n ; (4) a p o t e n t i a l i n c r e a s e i n the number o f emergency p a t i e n t s p l a c e d i n temporary beds ( o v e r - c a p a c i t y beds) owing t o e x t r e m e l y h i g h u t i l i z a t i o n i n any one s e r v i c e ; and (5) a p o t e n t i a l decrement i n p a t i e n t c a r e when a p a t i e n t i s p l a c e d i n another s e r v i c e because of h i g h u t i l i z a t i o n i n h i s proper s e r v i c e . " (Pages 119-120, Goldman e t a l , 1968) I n view of t h e s e c o n s i d e r a t i o n s , they c o n s i d e r e d t h r e e b e d s - t o - s e r v i c e p o l i c i e s and t h r e e beds-to-rooms p o l i c i e s . The b e d s — t o - s e r v i c e p o l i c i e s were based on some s e r v i c e s b e i n g " r e s t r i c t i v e " ( O b s t e t r i c s , I n t e n s i v e Care) and some " u n r e s t r i c t i v e " ( M e d i c a l , O r t h o p e d i c s ) i n the sense t h a t t h e y r e s p e c t i v e l y were o r were not a l l o w e d t h e use of beds i n o t h e r s e r v i c e a r e a s . The t h r e e p o l i c i e s were d i f f e r e n t i a t e d a c c o r d i n g t o the p r o p o r t i o n o f t i m e t h e a l l o c a t e d beds would meet the r e s t r i c t e d s e r v i c e s ' demand. , The t h r e e beds-to-rooms p o l i c i e s d e f i n e d ( i ) a l l beds t o be i n p r i v a t e rooms, ( i i ) beds t o be i n v a r i o u s t y p e s o f rooms as determined by average demand, and ( i i i ) as many beds to be i n wards as p o s s i b l e . Together t h e s e gave n i n e bed a l l o c a t i o n p o l i c i e s which were t e s t e d a t s e v e r a l l e v e l s of o v e r a l l bed u t i l i z a t i o n ^ Emergent, u r g e n t , and e l e c t i v e a d m i s s i o n s were a l l o w e d . Bed u t i l i z a t i o n , w a i t i n g t i m e s , o v e r l o a d , and t r a n s f e r s were r e c o r d e d . . G e n e r a l c o n c l u s i o n s were t h a t a t h i g h l e v e l s o f bed u t i l i z a t i o n (about 21 95%), any attempt t o s a t i s f y demand i n the r e s t r i c t e d s e r v i c e s r e s u l t e d i n extremely long w a i t i n g time, and a l a r g e number of p r i v a t e rooms would be d e s i r a b l e under cost parameters of the s o r t used i n the study. T h e i r study was c a r e f u l l y developed mathematically and warrants a t t e n t i o n by those i n t e r e s t e d i n the t o p i c . An e v a l u a t i o n of o p e r a t i n g room s c h e d u l i n g p o l i c y was p u b l i s h e d by Goldman e t a l (1969). S i m u l a t i o n was used so t h a t many p o l i c i e s could be examined q u i c k l y and without d i s r u p t i o n of the r e a l system. They considered three p o l i c i e s f o r d a i l y s c h e d u l i n g : (i) f i r s t - c o m e , f i r s t - s e r v e d ; ( i i ) l o n g e s t - c a s e s - f i r s t ; ( i i i ) s h o r t e s t - c a s e s - f i r s t . Two l e v e l s of e x p e d i t i n g (that i s , percentage o f cases capable of being moved to a somewhat e a r l i e r s t a r t i n g time) were i n c o r p o r a t e d . Data were from a 380-bed, 63% occupancy h o s p i t a l . The s i m u l a t i o n was i n FORTRAN IV, with a f i v e - m i n u t e time increment. The s i m u l a t i o n assumptions and a flow diagram were presented i n the paper, together with a u s e f u l t a b u l a r d i s c r i p t i o n of important i n p u t and output data. The authors used three l e v e l s of c a p a c i t y ( p o s s i b l e t o t a l time to schedule) and examined among other t h i n g s u t i l i z a t i o n , overtime, unused time, r e s c h e d u l i n g , and waits. The l o n g e s t - c a s e s - f i r s t p o l i c y gave highest u t i l i z a t i o n and lowest t o t a l d a i l y overtime f o r a l l l e v e l s of e x p e d i t i n g and c a p a c i t y . The ORSA B u l l e t i n a b s t r a c t e d a paper given by Shao and Thomas i n 1970, which may be o f i n t e r e s t . T h e i r model c o n s i d e r e d e l e c t i v e , urgent and emergent p a t i e n t s , and 22 recognized dependence of the a r r i v a l d i s t r i b u t i o n on the day-of-the-week, so the system was t r e a t e d as a s p e c i a l Markov process. The model co n s i d e r e d e f f e c t s of d i f f e r e n t admission s t r a t e g i e s ( i n c l u d i n g p r i o r i t y schemes) on non-emergent waiting times. A s i m u l a t i o n was performed. Hearn and Bishop produced a d i f f e r e n t s o r t of s i m u l a t i o n i n 1970. Using two wards, they considered 200 k i n d s of s e r v i c e items. They looked at v a r i a t i o n s p o s s i b l e under a no-delay system, s c h e d u l i n g , a seven-day week, and p r o g r e s s i v e care. Connors (1970) presented a s i m u l a t i o n model i n PL/1 which he intended f o r eve n t u a l use i n a r e a l - t i m e Admitting O f f i c e environment. The a l g o r i t h m f o r s c h e d u l i n g p a t i e n t s was q u i t e i n v o l v e d . , I t used d e t e r m i n i s t i c c o n s t r a i n t s a r i s i n g from the p a t i e n t ' s c h a r a c t e r i s t i c s and reguirements. A d d i t i o n a l p r o b a b i l i s t i c c o n s t r a i n t s were based on the h o s p i t a l ' s o p e r a t i n g requirements with the random processes of a r r i v a l s and occupancy. F e a s i b l e admission date and accommodation combinations were hence i d e n t i f i e d . The a l g o r i t h m chose from among these combinations i n order to minimize a composite f u n c t i o n , c a l l e d the f i g u r e of merit, based on p a t i e n t inconvenience and h o s p i t a l i n e f f i c i e n c y . For each p a t i e n t , only the a p p r o p r i a t e s e r v i c e was analysed. The p a t i e n t LOS assigned by the program was c a l c u l a t e d from a gamma d e n s i t y f u n c t i o n using Commission on P r o f e s s i o n a l and H o s p i t a l A c t i v i t i e s (CPHA)-supplied mean and standard d e v i a t i o n s . P r o v i s i o n was made f o r a l t e r n a t i v e s such as p h y s i c i a n estimates (with update c a p a b i l i t y ) or h o s p i t a l e m p i r i c a l data. Each admission request 23 had t o be accompanied by a l i s t of p a t i e n t s * p r e f e r r e d days f o r admission, and the type of accommodation d e s i r e d . The a l g o r i t h m c o a l d be run i n any of s e v e r a l modes. Under the ADMIT mode, i t entered the p a t i e n t i n the admissions l o g at the date f o r the lowest f i g u r e of merit ( i f s u i t a b l y s m a l l ) . Under the NO ADMIT op t i o n , i t l i s t e d up to t e n f e a s i b l e days which might then be o f f e r e d to the p a t i e n t f o r c h o i c e . Under the PRIORITY ADMIT mode, any a r b i t r a r y admission day co u l d be reserved. Once a day was s e l e c t e d , the program performed a p p r o p r i a t e updating c a l c u l a t i o n s , and awaited another reguest. A p a t i e n t MOVE cou l d a l s o be entered. The al g o r i t h m did not, when the a r t i c l e was w r i t t e n , i n c o r p o r a t e OR s c h e d u l i n g . T h i s s c h e d u l i n g d e c i s i o n was made independently, causing s u r g i c a l admissions t o be done by a NO ADMIT / PRIORITY ADMIT mode seguence. , S p e c i a l care u n i t s and a l a r g e number of t r a n s f e r s would complicate and reduce the e f f e c t i v e n e s s of the a l g o r i t h m . ft paper by Blewett et a l d e s c r i b i n g the j o i n t use of wards and an o p e r a t i n g t h e a t r e by ENT and Opthalmology c o n s u l t a n t s appeared i n 1972. Admissions were taken to f o l l o w an e m p i r i c a l s t a t i s t i c a l p a t t e r n and were u n c o n t r o l l a b l e . P a t i e n t s were c a t e g o r i z e d f o r homogeneity o f lengths of surgery and stay. Models were developed, and w r i t t e n i n FORTRAN, f o r Opthalmology alone, f o r ENT alone, and f o r the two s h a r i n g f a c i l i t i e s with one another. A v a l i d i t y comparison of the models and the r e a l system was t a b u l a t e d . Three experiments were performed with the v a l i d a t e d models. One experiment, with the Opthalmology model, checked the consequences o f a new minor o p e r a t i n g t h e a t r e on bed 24 use. The second experiment, with the cmbined model, examined the e f f e c t s of a change ( a c t u a l l y under c o n s i d e r a t i o n ) i n the o p e r a t i n g t i m e t a b l e . The t h i r d experiment concluded t h a t with combined r a t h e r than separated s p e c i a l t i e s , the use of temporary beds would be reduced without decreasing o v e r a l l throughput. An unusual c l a i m of t h i s study i s t h a t i t s c o n c l u s i o n s were co n s i d e r e d by management with f a v o u r a b l e r e s u l t s . Schmitz and Kwak have produced a s e r i e s of papers on the s i m u l a t i o n of s u r g i c a l u n i t s . In 1972 they used a manual s i m u l a t i o n to c o n s i d e r the e f f e c t of i n c r e a s e d beds on operating-room and recovery-room usage. They examined what the bed i n c r e a s e would mean i n terms of the number of procedures, and i n terms of time and c a p a c i t y i n the OS and recovery rooms. K u z d r a l l j o i n e d the authors, and i n 1974 a GPSS e x t e n s i o n of t h i s manual s i m u l a t i o n appeared. T h e i r most s o p h i s t i c a t e d work appeared i n 1976. . I t i n v o l v e d a comparison, v i a GPSS s i m u l a t i o n , of f i v e p o s s i b l e p a t i e n t flow s t r a t e g i e s , each with " r e a l - world" f o u n d a t i o n s . Again, a s u r g i c a l s u i t e and recovery s u i t e were the p h y s i c a l f a c i l i t i e s under c o n s i d e r a t i o n . E m p i r i c a l data were used to determine l e n g t h of s u r g e r y and LOS d i s t r i b u t i o n s . The s t r a t e g i e s compared were: i . random input t o surgery ( e x i s t i n g p o l i c y ) ; i i . preemptive p r i o r i t y f o r recovery-room u s e r s ; i i i . l o n g e s t surgery f i r s t w i t h i n recovery-room users, then w i t h i n non-recovery p a t i e n t s ; i v . l o n g e s t surgery f i r s t f o r recovery p a t i e n t s , others 25 random; v. longest surgery f i r s t w i t h i n major procedures, then others needing the recovery room, then the r e s t . . S u r g i c a l s u i t e s were t r e a t e d together as a s i n g l e f a c i l i t y r a t h e r than i n d i v i d u a l l y , to minimize ambiguity. I t was found t h a t u t i l i z a t i o n c o u l d be improved and t h a t the l e n g t h of the working day i n the recovery-room could be reduced (up to 21%) by using a new s t r a t e g y . The h o s p i t a l under c o n s i d e r a t i o n was i n c r e a s i n g i t s s u r g i c a l l o a d anyway, and s e r i o u s l y c o n s i d e r e d implementing s t r a t e g y (iv) to minimize the a d d i t i o n a l requirements of such an i n c r e a s e . However, another option beyond the range of the study appeared and was e v e n t u a l l y chosen. In the Computer Hedieine newsletter of A p r i l 1977 an e n t r y appears concerning a "Computer A i d i n g Surgery Schedule". I t s t a t e s that a new system ( f i r s t t e s t e d f o r two years) i s now implemented to a l i g n p a t i e n t s and personnel i n a 26 OR h o s p i t a l . The computerized s c h e d u l i n g system saves a c o n s i d e r a b l e amount of time, can be c o r r e c t e d or changed by s t a f f , and w i l l probably be expanded to r e t r i e v e some i n f o r m a t i o n . No f u r t h e r d e t a i l s of the system are p u b l i s h e d at present. The preceding review i s by no means exhaustive.,. O u t p a t i e n t departments and s c h e d u l i n g of nursing s t a f f , f o r example, have not been i n c l u d e d a t a l l . N e v e r t h e l e s s , the reviewed a r t i c l e s provide a f a i r overview of the l i t e r a t u r e which i s a p p l i c a b l e to the work presented i n t h i s t h e s i s . 26 I t may be of i n t e r e s t to point out the sources and range of dates of the a r t i c l e s presented here.. Of the 45 c i t e d , 12 were from Health S e r v i c e s Research, 6 more from Operations Research and 4 from Management Science. Twenty other sources y i e l d e d the remainder, with 12 a r t i c l e s from Medical areas, 7 from Management Science, Operations Research, or S t a t i s t i c s , and 4 from Computing or Eng i n e e r i n g r e f e r e n c e s . , 1970, 1972 and 1973 c o n t r i b u t e d 5 a r t i c l e s each, plus 6 from 196 8. There were 7 from 1960 through 1965, 7 from 1966-67, 4 from 1969, and 6 s i n c e 1973. In aggregate, over t w o - t h i r d s of the a r t i c l e s appeared from 1966 to 1973, i n c l u d i n g o n e - t h i r d from 1968 to 1970. at present, a great d e a l of a p p l i e d work i s being conducted by both h o s p i t a l - b a s e d and o u t s i d e c o n s u l t a t i o n groups who have l i t t l e i n c e n t i v e t o p u b l i s h . Furthermore i f , as suggested by Shuman et a l (1975), f u t u r e s t u d i e s are more l a r g e - s c a l e - i n c l u d i n g the problems of subsystems and t h e i r boundary i n t e r a c t i o n s - then new c o n t r i b u t i o n s to the l i t e r a t u r e can be expected to become more i n f r e g u e n t , but more s i g n i f i c a n t . 27 CHAPTER 4 INTERPRETATION AND METHODOLOGY The l i t e r a t u r e review of the preceding chapter demonstrates t h a t s e v e r a l d i f f e r e n t mathematical approaches have been used t o model problems s i m i l a r to ours. These approaches i n c l u d e s t o c h a s t i c , queuing t h e o r e t i c , Markovian and s i m u l a t i o n methods. Within each o f these, the model may be c o n s i d e r e d i n a v a r i e t y of ways. T h i s chapter presents the b a s i c methodological d e c i s i o n s made f o r the S t . Paul's H o s p i t a l p r o j e c t , and proceeds to d i s c u s s them i n the context of the a n a l y s e s j u s t reviewed. 4. 1 Basic Methodological D e c i s i o n s 4. 1. 1 Mathematical Method The g e n e r a l i z e d s t o c h a s t i c a n a l y s i s approach, as undertaken by Shonick (1970) and Shonick and Jackson (1973) was r e j e c t e d s i n c e , as they s t a t e d , i t i s o r i e n t e d towards area-wide p l a n n i n g f o r a community r a t h e r than f o r a s p e c i f i c h o s p i t a l . The r e s u l t s of the present work are intended to be of use to St. Paul's H o s p i t a l i n Vancouver with i t s p a r t i c u l a r c h a r a c t e r i s t i c s . , I f the model turns out to be more g e n e r a l l y a p p l i c a b l e , t h at i s an a d d i t i o n a l b e n e f i t . Queuing theory as used by Young (1965,1966) i s a l s o unacceptable s i n c e i t i s h i g h l y u n l i k e l y that a r r i v a l r a t e and 28 LOS d i s t r i b u t i o n s can j u s t i f i a b l y be represented by Poisson processes. (See K o l e s a r , 1970; Blewett e t a l , 19 72; Schmitz et a l , 1976.) Furthermore, the s c h e d u l i n g process a t S t . Paul's - which r e q u i r e s OS s l a t e s t o be planned ahead with some f l e x i b i l i t y and which has v a r i o u s deqrees of urgency f o r admission - i s r a t h e r complex, and not amenable to a gueuing model. Markovian a n a l y s i s seems more promising. I t maintains the convenience of a c l o s e d form s o l u t i o n while s t i l l being q u i t e f l e x i b l e . , E m p i r i c a l data can be used. Kol e s a r (1970) added an i n t e r e s t i n g i d e a i n i n c o r p o r a t i n g a l i n e a r program. Kao (1972) showed t h a t LOS could be accounted f o r r e a l i s t i c a l l y . However, the problem we have posed i s not s u i t a b l e f o r Markovian a n a l y s i s . We are not i n t e r e s t e d i n a number of c o n s e c u t i v e p a t i e n t s t a t e s - as i n a p r o g r e s s i v e care h o s p i t a l . Even i f p a t i e n t s t a t e s were d e f i n e d as, say, <i) a w a i t i n g admission, ( i i ) occupying a bed o f f - s e r v i c e , ( i i i ) occupying a proper bed, and (iv) discharged, problems would s t i l l remain. One i n t e n t of our p r o j e c t i s to d i s c o v e r the impact of c e r t a i n s c h e d u l i n g and bed-complement v a r i a t i o n s on the w a i t i n g l i n e . I t i s not c l e a r how to i n c l u d e OR s c h e d u l i n g , or any other s o r t of f l e x i b l e bed s c h e d u l i n g i n a Markovian model. I t would probably not be p o s s i b l e t o demonstrate the v i t a l i n t e r a c t i o n between OS s c h e d u l i n g and the Admitting O f f i c e , with i t s important "No Bed" v a r i a b l e as output. ( S i m u l a t i o n , on the other hand, can be used t o model very complex s i t u a t i o n s . I t s use i n t r a n s p o r t a t i o n , economic and 29 energy models i s q u i t e f a m i l i a r . Furthermore, i t s a p p l i c a t i o n t o h e a l t h care has been demonstrated to some extent (see Stimson and Stimson 1972, o r Shuman et a l 1975). S i m u l a t i o n can be used to model the p a t i e n t admissions and s c h e d u l i n g system at St. Paul's H o s p i t a l . ft.1.2 Language Having decided to use computer s i m u l a t i o n , one must choose among a number o f languages. .Reitman's a r t i c l e on s i m u l a t i o n languages (1967) g i v e s some u s e f u l p o i n t e r s . The p o s s i b i l i t i e s were a higher order language (FORTRAN) or a g e n e r a l l y a v a i l a b l e s i m u l a t i o n language (GPSS, SIMSCRIPT or SIMULA). FORTRAN was q u i c k l y e l i m i n a t e d from c o n s i d e r a t i o n . Since i t i s not a s p e c i a l i z e d language, i f FORTRAN were used the model would be expected to be cumbersome. L i s t p r o c e s s i n g i n the language i s weak - a d e f i n i t e disadvantage with d i v e r s e " l i n e s " of p a t i e n t s awaiting admission and o p e r a t i o n s . There i s no s t a t i s t i c a l p r o c e s s i n g b u i l t i n . I t seemed, then, t h a t one o f the m a i n - l i n e s i m u l a t i o n languages would be best. Of the t h r e e mentioned, SIMULA was suggested t o have the best c a p a b i l i t i e s . However, when t h i s p r o j e c t was being c o n s i d e r e d , i t seemed t h a t UBC was going to stop i t s support of t h a t language. SIMSCRIPT seems to be a good language f o r l a r g e models. I t s time-stream and e v e n t - o r i e n t e d s t r u c t u r e are convenient, as are language c o n s t r u c t s f o r data. However, t h e r e are 30 disadvantages. The amount of computer memory th a t the SIMSCSIPT processor w i l l make a v a i l a b l e i s u n c e r t a i n , and l a r g e models become i n e f f i c i e n t and r e g u i r e s k i l l i n programming. C o n s u l t a t i o n and support at UBC i s l i m i t e d . Furthermore, compared to GPSS i t tends to be expensive, and has poorer d i a g n o s t i c s . GPSS a l s o has pros and cons. On a s u r f a c e l e v e l , the block s t r u c t u r e suggests what i s happening. However, much of the i n t e r n a l working i s d i s g u i s e d . T h i s may be a l l e v i a t e d somewhat by the GPSS p r o v i s i o n f o r i n c o r p o r a t i n g documentation with each l i n e of code, to e x p l a i n the model. S t a t i s t i c s which are maintained i n t e r n a l l y cover a l l the usual output demands, and t a b l e s may be added c o n v e n i e n t l y . GPSS models can be very l a r g e - although they do get expensive. UBC gives GPSS "major" support with good c o n s u l t a t i o n , r e g u l a r updates, and guick a t t e n t i o n to system bugs. (This l a s t p o i n t d i d prove worthwhile.) The language processor tends to be f a i r l y e f f i c i e n t , and the language i s well-known. Such c o n s i d e r a t i o n s l e d to the c h o i c e of GPSS as the s i m u l a t i o n language f o r t h i s p r o j e c t . 4.1.3 Time Unit Depending on the l e v e l of d e t a i l i n v o l v e d i n the s i m u l a t i o n of each day's a c t i v i t e s , d i f f e r e n t time i n t e r v a l s may be d e s i r a b l e . (The s i m u l a t i o n languages which we considered use a d i s c r e t e r a t h e r than continuous time stream.) Goldman et a l 31 (1969) used a f i v e - m i n u t e time i n t e r v a l f o r t h e i r OB study. Our study, on the other hand, i s not intended to c o n s i d e r the minute processes of the OR. In f a c t , the OR i s mainly of i n t e r e s t f o r the number of p a t i e n t s scheduled there per day. S i m i l a r l y , bed turnovers are normally on a day-to-day b a s i s . As r e s u l t , the time u n i t chosen was one day. Although a number of events must happen i n seguence each day (eg. discharges and a d m i s s i o n s ) , t h i s can be simulated by a s s i g n i n g " p r i o r i t y l e v e l s " . 4.1.4 L e v e l of Aggregation One must decide which h o s p i t a l f a c i l i t i e s t o r e p r e s e n t and how completely to d i f f e r e n t i a t e p a t i e n t s a c c o r d i n g to t h e i r care needs. The problem as posed i n v o l v e d OR's and beds. These f a c i l i t i e s should be adequate for c o n s i d e r i n g most questions i n v o l v i n g p a t i e n t flow and s c h e d u l i n g . A c l a s s i f i c a t i o n system based on " h o s p i t a l s e r v i c e " can be s e t up to match p a t i e n t s to the a p p r o p r i a t e OR, bed area, and p h y s i c i a n s p e c i a l t y groups (see a l s o S e c t i o n 5.1.1). A f u r t h e r s u b d i v i s i o n of p a t i e n t types a c c o r d i n g to H-ICDA diagnoses and procedures may be p o s s i b l e . However, i t would r e q u i r e e x t e n s i v e c o n s u l t a t i o n with a group of experienced h o s p i t a l a d m i n i s t r a t o r s to group these codes i n t o a manageable number of homogeneous p a t i e n t groups. Furthermore, such s u b d i v i s i o n would complicate data c o l l e c t i o n . 32 4.1.5 Extent of the Model Should every h o s p i t a l u n i t be i n c l u d e d i n the model? How much s t a f f should be shown? These are other q u e s t i o n s which may be answered i n gen e r a l terms at the ou t s e t . I t i s q u i c k l y evident that the Day Care, P s y c h i a t r i c , Renal and Nursery u n i t s operate e f f e c t i v e l y independently of the b a s i c Medical / s u r g i c a l f u n c t i o n o f St. Paul ' s H o s p i t a l (see a l s o S e c t i o n 5.1.1). T h i s h i g h - l i g h t s the f a c t t h a t the e s s e n t i a l matter of i n t e r e s t i s the r a t e of p a t i e n t flow. Only u n i t s which are i n v o l v e d i n the c o n t r o l o f t h i s r a t e (as through o p e r a t i o n s , beds, and bed t r a n s f e r s ) need t o be co n s i d e r e d f o r i n c l u s i o n i n the model. I t should be s a f e to assume that the h o s p i t a l w i l l employ whatever nu r s i n g complement i s necessary t o handle the p a t i e n t s who a r r i v e there. As a r e s u l t , nurses are not i d e n t i f i e d as separate e n t i t i e s i n the model. T h i s merely suggests t h a t the s i z e of the nursing s t a f f does not determine the number of p a t i e n t s at an e s t a b l i s h e d h o s p i t a l , under normal labour c o n d i t i o n s , but v i c e versa. As i s noted i n S e c t i o n 5.3.7, nurs i n g c o n s i d e r a t i o n s do c o n t r i b u t e t o e x p l a i n i n g the e f f i c i e n c y of handl i n g o p e r a t i o n s , p a r t i c u l a r l y emergencies. With a b i t more h e s i t a t i o n i t was decided to exclude a n a e s t h e t i s t s from the model. The one-day time u n i t and the r e a l i s t i c assumption that the h o s p i t a l would ensure t h a t the number of a n a e s t h e t i s t s was a p p r o p r i a t e t o the s e r v i c e p a t t e r n , account f o r t h i s d e c i s i o n . 33 4.2 D i s t i n c t i v e Features of t h i s P r o j e c t St. Paul's d e s i r e d a model of i t s p a t i e n t admissions and s c h e d u l i n g , and the l i t e r a t u r e c o n tained s e v e r a l approaches to h o s p i t a l modelling. Would i t have been p o s s i b l e to adopt one of the e x i s t i n g models to the problem at hand? The answer i s no. The f o l l o w i n g s e c t i o n d i s c u s s e s f e a t u r e s of t h i s p r o j e c t which d i f f e r e n t i a t e i t from other r e l a t e d work pu b l i s h e d i n the l i t e r a t u r e . Probably the most ou t s t a n d i n g f e a t u r e o f our model i s that s e v e r a l " c h a r a c t e r i s t i c " h o s p i t a l s e r v i c e s are modelled simultaneously ( p r e s e n t l y Medicine, EENT, and Orthopedics are implemented). I t i s recognized t h a t when beds are not a v a i l a b l e i n the a p p r o p r i a t e s e r v i c e areas, emergency admissions may be placed i n a l t e r n a t e areas. T h i s becomes s i g n i f i c a n t when i t i s con s i d e r e d t h a t about 75% of the Med i c a l admissions to St. Paul's are on an immediate b a s i s . There are so many immediate Medical admissions t h a t about 30% of them must be admitted o f f - s e r v i c e . As a r e s u l t , t h e model must t r a n s f e r enough Medical p a t i e n t s out of s u r g i c a l s e r v i c e areas to minimize "No Bed" c a n c e l l a t i o n s (see S e c t i o n 5.2.3). Secondly, there are b a s i c a l l y two main groups of admissions, s c h e d u l a b l e and immediate (see S e c t i o n 5.2.4). The sche d u l a b l e cases form a waiting l i s t , and are c a t e g o r i z e d and handled according to urgent (0), semi-urgent (SU) and e l e c t i v e (El) c a t e g o r i e s . (Very few other models d i f f e r e n t i a t e d w i t h i n the s c h e d u l a b l e stream.) However, i n c o n t r a s t to most other 34 models, our model does not allow a t r a d e - o f f of the " p r o b a b i l i t y of being a b l e to handle a l l emergencies" a g a i n s t "occupancy". A l l emergency p a t i e n t s are admitted, with the r e s u l t t h a t immediate admissions account f o r 45$ of a l l admissions and 7 5 % of the Medical ones. S t i l l , occupancy i s very high - an average of 9 3 % f o r the whole h o s p i t a l , and higher f o r the s e r v i c e s d e s c r i b e d by our model. T h i r d l y , the h o s p i t a l modelled observes d i f f e r e n t admission methods f o r the d i f f e r e n t s e r v i c e s . A Medical p a t i e n t on the waiting l i s t i s admitted when a bed i s a v a i l a b l e . A s u r g i c a l p a t i e n t i s f i r s t scheduled f o r surgery, s u b j e c t to c e r t a i n l i m i t s , and i s then admitted on the a p p r o p r i a t e day i f a bed i s a v a i l a b l e . F o u r t h l y , we found t h a t while i n the past v a r i o u s parametric d i s t r i b u t i o n s have o f t e n been used t o d e s c r i b e p a t i e n t a r r i v a l s and LOS, such parametric d i s t r i b u t i o n s d i d not provide an adequate " f i t " . Thus, f o r added r e a l i s m , we use e m p i r i c a l data to d e s c r i b e these processes., F i n a l l y , t h i s study i s designed to i n d i c a t e what e f f e c t ( i n terms of occupancy, bed a v a i l a b i l i t y f o r scheduled s u r g i c a l p a t i e n t s , and w a i t i n g times) might be had by changes being c o n s i d e r e d at St. Paul's H o s p i t a l . Such changes i n c l u d e c l o s i n g under-used o p e r a t i n g rooms, r e s t r i c t i n g " a l t e r n a t e " placement of p a t i e n t s , and v a r y i n g bed numbers or a l l o c a t i o n . 35 CHAPTER 5 THE HOSPITAL AND THE MODEL T h i s chapter d i s c u s s e s those f a c i l i t i e s and processes i n St. Paul's H o s p i t a l which were examined i n developing the modeli The assumptions and d e t a i l e d c o n s i d e r a t i o n s of the h o s p i t a l ' s p h y s i c a l s t r u c t u r e and of d e c i s i o n processes p e r t a i n i n g to p a t i e n t flow are d e s c r i b e d . H o s p i t a l f u n c t i o n a l and l o c a t i o n a l s u b d i v i s i o n s depending on p a t i e n t c l a s s i f i c a t i o n and p reference w i l l be d i s c u s s e d f i r s t . T h i s w i l l be f o l l o w e d by the two p r i n c i p a l t o p i c s of i n t e r e s t , admitting and s u r g i c a l s c h e d u l i n g c o n s i d e r a t i o n s . These two, supplemented by i n - h o s p i t a l t r a n s f e r and LOS data, serve t o determine p a t i e n t flow through the h o s p i t a l . 5. 1 D e f i n i t i o n of Subsystems Obviously not a l l p a t i e n t s r e c e i v e i d e n t i c a l treatment at the h o s p i t a l . N e v e r t h e l e s s , f o r our purposes most d i f f e r e n c e s are not important and i t i s p r e f e r a b l e to c o n s i d e r r e l a t i v e l y homogeneous p a t i e n t groups i n the f o r m u l a t i o n of the model. There e x i s t n a t u r a l c l a s s i f i c a t i o n s c a l l e d " s e r v i c e s " which do t h i s f a i r l y w e l l . The word " s e r v i c e " may d e f i n e s l i g h t l y d i f f e r e n t groups, depending on whether i t i s used i n h o s p i t a l records, or to d e s c r i b e an OR d e s i g n a t i o n , a p h y s i c i a n s p e c i a l t y , or a h o s p i t a l area. From these c l a s s i f i c a t i o n s , I have developed a f u n c t i o n a l c l a s s i f i c a t i o n to be used i n the 36 model. We note t h a t t h e r e are some s p e c i a l - p u r p o s e h o s p i t a l u n i t s d e f i n e d a c c o r d i n g to the care they o f f e r r a t h e r than the p a t i e n t ' s " s e r v i c e " . Within a h o s p i t a l area, i t i s p o s s i b l e t o c h a r a c t e r i z e beds f u r t h e r as being p r i v a t e , s e m i - p r i v a t e , or i n a ward, and as being designated f o r a male or f o r a female, or f o r e i t h e r one. 5 . 1 . 1 H o s p i t a l S e r v i c e s When an admission request a r r i v e s at the h o s p i t a l , two th i n g s must be determined; where the p a t i e n t should be l o c a t e d and, i f a p p l i c a b l e , i n which 08 h i s surgery should be performed. The d a i l y census sheet d i v i d e s the h o s p i t a l i n t o i t s 2 1 nursing s t a t i o n s (Table I ) . The OR Booking O f f i c e v i s u a l f i l e and d a i l y s l a t e are subd i v i d e d i n t o eleven s e c t i o n s corresponding t o op e r a t i n g t h e a t r e s or groups of t h e a t r e s {Table I I ) . To schedule and place a p a r t i c u l a r p a t i e n t , a s i n g l e c l a s s i f i c a t i o n scheme i s most u s e f u l . There i s an item r e f e r r e d to as " h o s p i t a l s e r v i c e " on case a b s t r a c t s kept by the Medical Records L i b r a r y . (The coded a b s t r a c t s a r e submitted t o CPHA f o r a n a l y s i s . ) By regrouping the o r i g i n a l codes f o r t h i s item, we can o b t a i n f u n c t i o n a l p a t i e n t groups which we w i l l c a l l s e r v i c e s (Table III) . One pre c a u t i o n a r y note should be added here., One s e r v i c e , General Surgery, d i v i d e s i t s p h y s i c i a n s , bed areas, and OR usage acc o r d i n g t o s u b d i v i s i o n s "A", "B", and "C", which a r e r e f e r r e d to w i t h i n the h o s p i t a l as " s e r v i c e s " . The model does not 37 TABLE I NURSING UNITS 1JUNE 1976.1 Beds B a s s i - Rated Hard Use P r i v Semi Ward nets Capaci 6 South Maternity 19 2 10 31 6 South Nursery 35 35 5 North Gynecology 21 12 8 41 ICN Nursery 14 14 5 South Gen'l Surgery A 3 18 23 44 4 North EENT 3 14 18 35 4 North Orthopedics 10 16 26 4 East Orthopedics 1 2 41 44 4 South Urology 7 14 22 43 3 North Medicine 4 16 12 32 3 Neuro Neurology & Neurosurgery 3 4 16 23 3 East Gen'l Surgery B 1 6 24 31 3 Main Gen'1 Surgery C 8 24 32 3 South A c t i v a t i o n 16 16 2 North (20 semi Medicine - c l o s e d teaching) 20 20 40 2 East ICU 8 4 8 20 2 West Ca r d i a c Unit 1 10 4 15 2 South (18 semi A Medicine - c l o s e d teaching) 8 14 17 39 2 South B Medicine ( a l l c l o s e d teaching) 28 28 C2A P s y c h i a t r y 10 10 C2B P s y c h i a t r y 30 30 DAILY TABLE I I SLATE SUBDIVISIONS Gynecology Room 2 Urology ( i n c l . Day Care EE NT Room 1 General Surgery " s e r v i c e " A, B, or C {depending on day or need) Cystoscopy) Rooms 3 and 4, and perhaps 5 Room 7, and perhaps 5 Rooms 8 and 9 ENT M / H / F Rooms 10 and 11 Opthalmology T / Th Open Heart and V a s c u l a r Room 14 Orthopedics Room 17 Room 18 Room 19 Room 12 General Surgery " s e r v i c e " A, B, or C Room 16 General Surgery " s e r v i c e " B or C Neurosurgery M / W / Th am / F pm P l a s t i c Surgery T / Th pm / F am S p e c i a l X-rays {Pneumoencephalogram and C a r o t i d Angiogram) 39 TABLE I I I HOSPITAL SERVICES O r i g i n a l CPHA D i v i s i o n s New F u n c t i o n a l D i v i s i o n s Comme nts 10 Medicine 14 Communicable 18 Dermatology 32 Neurology 38 P s y c h i a t r y 40 General Surgery 48 Opthalmology 50 ENT 54 Dental 58 Orthopedics 62 Orology 56 Neurosurgery } } 60 P l a s t i c Surgery } 70 Gynecology 11 Renal 75 Abortion 76 O b s t e t r i c u n d e l i v e r e d 77 O b s t e t r i c d e l i v e r e d 80 Newborn 89 S t i l l b o r n Medicine Same EENT Same Same Neurosurgery and P l a s t i c Surgery Same Not Examined Not Examined I n c l u d e s Open Heart and V a s c u l a r cases Not Examined Not Examined Not Examined Not Examined Not Examined Not Examined 40 observe these s u b d i v i s i o n s per se. The reasons f o r the p a r t i c u l a r combinations y i e l d i n g new f u n c t i o n a l s e r v i c e s are as f o l l o w s . P a t i e n t s i d e n t i f i e d by "Medicine'*, "Communicable", and "Dermatology" a l l use the same o v e r a l l bed area, so are a l l i d e n t i f i e d by "Medicine". Open heart surgery (which has a separate o p e r a t i n g room) and v a s c u l a r surgery (which does not) are not d i f f e r e n t i a t e d i n the CPHA s e r v i c e s from General Surgery. I t would be i n c o n v e n i e n t , but perhaps advantageous, to sep a r a t e them i n the f u t u r e . The EENT subgroups share a common bed area and a common spot on the s l a t e . Furthermore, although t h e o r e t i c a l l y Opthalmology and ENT have i n d i v i d u a l OR's and d i f f e r e n t days, i n p r a c t i c e there i s some i n t e r m i n g l i n g . Neurosurgery and P l a s t i c Surgery share an OR and sometimes, s i n c e P l a s t i c Surgery does not have i t s own, a bed area., Some s e r v i c e s were not co n s i d e r e d i n the model, f o r the f o l l o w i n g reasons. Neurology c o u l d almost be termed " i n v e s t i g a t i v e Neurosurgery". Neurology and Neurosurgery do indeed share the same admission form (co l o u r coded f o r d i s t i n c t types) , a bed area (which i s o f t e n e n t i r e l y c a t e g o r i z e d as f o r Neurosurgery), and l a r g e l y the same p h y s i c i a n s . In any case, the Neurosurgery and P l a s t i c surgery s e r v i c e was not implemented i n the model, and thus the problem of c o n s i d e r i n g how to i n c l u d e Neurology was not faced. P s y c h i a t r y , which i s housed i n a separate b u i l d i n g , i s e f f e c t i v e l y independent., There i s no bed o v e r l a p with other 4 1 areas. I f one of the p a t i e n t s r e q u i r e s surgery or a d i f f e r e n t h o s p i t a l bed, he i s r e c l a s s i f i e d and recounted. Since the o r d i n a r y admission process w i l l not accommodate the v a r i a b i l i t y of the outset of labour i n pregnant women, maternity admissions are handled d i f f e r e n t l y . The case room keeps a p r e - n a t a l r e c o r d on p r o s p e c t i v e mothers, and each week informs the maternity ward what to expect. The d e l i v e r y room i s separate from the o p e r a t i n g rooms. There i s very o c c a s i o n a l l y a bed interchange with Gynecology. I f a p a t i e n t with a h i s t o r y of d i f f i c u l t b i r t h s , but p r e d i c t a b l e c a r r y i n g time, i s due t o come i n , an OR may be booked i n advance through the Gynecology s l o t . C a e s a r i a n s e c t i o n s , l i g a t i o n s , and b l e e d i n g cases may be sent to an OR on an emergency b a s i s . I t would be p o s s i b l e to have the Maternity s e r v i c e i n the model as a randomly-occurring exogenous demand on OR usage, but i t was f e l t t h a t t h i s e f f e c t was s u f f i c i e n t l y s m a l l to be excluded s a f e l y . . As a consequence, th e r e was no need to i n c l u d e n u r s e r i e s e i t h e r . S t . P a u l ' s H o s p i t a l used to have a P e d i a t r i c s e r v i c e , but no longer does. As a r e s u l t , LOS data was a d j u s t e d t o compensate f o r the tendency of young p a t i e n t s (who were i n c l u d e d i n the o r i g i n a l data sample) to have s h o r t s t a y s . For a more e x t e n s i v e p a t i e n t c l a s s i f i c a t i o n i t would have been necessary to examine groups of diagnoses which tend t o y i e l d groups of p a t i e n t s who are homogeneous i n terms of h o s p i t a l placement, LOS, l e n g t h (and other demands) of surgery, and s p e c i a l c a r e p a t t e r n s . Such an attempt, on the b a s i s of H-ICDA d i a g n o s i s and o p e r a t i v e groups, was c o n s i d e r e d . However, 42 t h i s was soon seen to be i n f e a s i b l e i n terms of the amount of time i t would have demanded from p r o f e s s i o n a l s capable of fo r m u l a t i n g such a c l a s s i f i c a t i o n , and the amount of f a m i l i a r i z a t i o n i t would have demanded of the modeller. Since the CpHA " h o s p i t a l s e r v i c e " i s g e n e r a l l y based on the "primary d i a g n o s i s e x p l a i n i n g admission", we c o n s i d e r e d i t t o be a good b a s i s f o r a s u b d i v i s i o n . In r e a l i t y , i t i s not always c l e a r which s e r v i c e a p a t i e n t should be c l a s s i f i e d under. ftn emergency p a t i e n t may be admitted t o the care of two d i f f e r e n t p h y s i c i a n s , and may t r a n s f e r from one area of the h o s p i t a l to another during h i s s t a y . Such ambiguity was not thought to be freguent or s e r i o u s . 5 .1.2 H o s p i t a l U n i t s There are s e v e r a l s p e c i a l u n i t s within St. Paul's H o s p i t a l which are d e f i n e d i n terms of the c a r e they o f f e r r a t h e r than i n terms of a p a t i e n t ' s " s e r v i c e " c l a s s i f i c a t i o n . The fienal U n i t , which used to d e f i n e a s e r v i c e category, now operates on an o u t p a t i e n t b a s i s . I t has only seven beds, each o f which may be used three times a day. I f one of the u n i t ' s p a t i e n t s r e q u i r e s admission to the main h o s p i t a l area o v e r n i g h t , he w i l l be r e - c l a s s i f i e d and counted as admitted to another s e r v i c e . A p a t i e n t being prepared f o r a d i a l y s i s setup would be c l a s s i f i e d under General Surgery. For a kidney removal, he would be i n Urology. Some minor flaws may be present i n the Medical LOS data due to u n c l e a r c l a s s i f i c a t i o n 43 p r i o r to and during the Renal U n i t ' s r e c l a s s i f i c a t i o n as o u t p a t i e n t . As noted on Table I I , one or two o p e r a t i n g rooms a r e used f o r Day. Care surgery, along with ten or so beds. T h i s s e r v i c e i s a l s o handled on an o u t p a t i e n t b a s i s , and does not o v e r l a p with the main h o s p i t a l ' s bed or OR use. Not even the PAR (Post-Anaesthetic Recovery room) i s used., As with Renal p a t i e n t s , a Day Care p a t i e n t s t a y i n g o v e r n i g h t i s r e c l a s s i f e d . Of course, t h e OR Booking O f f i c e may need to worry about s c h e d u l i n g a surgeon who i s to use both Day Care and other surgery time on a p a r t i c u l a r day, but t h i s l e v e l of d e t a i l was not observed i n the model. The Day Care surgery process was not i n c l u d e d . The most complex u n i t i n terms of i t s i n t e r a c t i o n s i n the h o s p i t a l set-up i s the I n t e n s i v e Care Unit Z C o r o n a r j Care U n i t ( r e f e r r e d to only as the ICU) , which has twenty beds. I t r e c e i v e s p a t i e n t s who have had myocardial i n f a r c t i o n s and w i l l r e c e i v e " c o n s e r v a t i v e " n o n - s u r g i c a l treatment. I t a l s o r e c e i v e s r e s p i r a t o r y p a t i e n t s r e q u i r i n g a s s i s t e d or mechanical v e n t i l a t i o n and vigorous physiotherapy. P a t i e n t s with acute r e n a l f a i l u r e or unconsciousness due t o poison or drug overdose may a r r i v e v i a the Emergency U n i t . Any Medical f a i l u r e or s u r g i c a l d i s a s t e r r e q u i r i n g i n t e n s i v e c a r e may r e s u l t i n a t r a n s f e r to the ICU. Many of the p a t i e n t s i n the ICU come from the Emergency U n i t , the next l a r g e s t number from the PAR ( N e u r o s u r g i c a l , thorax, h e a r t , and major v a s c u l a r cases go to the ICU a f t e r 24 hours of monitoring i n the PAR), and the r e s t 44 from the ward ca t a s t r o p h e s i n the whole h o s p i t a l . P a t i e n t s u s u a l l y r e t u r n to an a p p r o p r i a t e area a f t e r s t a b i l i z i n g and before being discharged. As a r e s u l t , the ICU i s r e s p o n s i b l e f o r a l a r g e number of i n - h o s p i t a l t r a n s f e r s . O r i g i n a l l y intended as an e n t i r e l y M edical u n i t , the ICU does handle some s u r g i c a l p a t i e n t s . A nearby u n i t which works c l o s e l y with ICU i s the f i f t e e n D e d c a r d i a c surgery, u n i t . T h i s i s the area to which o u t s i d e heart p a t i e n t s and i n - h o s p i t a l c a r d i a c a r r e s t s who w i l l be " a g g r e s s i v e l y " t r e a t e d are admitted b e f o r e surgery. A f t e r surgery they spend 24 hours i n the PAB and 2-3 days i n the ICU before r e t u r n i n g t o the c a r d i a c u n i t u n t i l d i s c h a r g e . There i s some o v e r l a p and i n t e r a c t i o n i n the use of ICU and c a r d i a c beds, but b a s i c a l l y the c a r d i a c u n i t i s the open heart surgery bed area. The a c t i v a t i o n area i s used t o s t a r t r e h a b i l i t a t i o n . I t has about f i f t e e n beds and processes 30-35 p a t i e n t s per month. P a t i e n t s being t r e a t e d here o r i g i n a t e about e q u a l l y from the Medicine, General Surgery, and Orthopedic areas. Most of the p a t i e n t s are sent home or f o r c a r e , with l e s s than 5% r e t u r n i n g to t h e i r p r e v i o u s h o s p i t a l area. S i n c e the p a t i e n t c l a s s i f i c a t i o n used was not s p e c i f i c enough to i d e n t i f y p a t i e n t s who would r e c e i v e c a r e i n the areas d i s c u s s e d i n t h i s s e c t i o n , they were not c o n s i d e r e d f o r i n c l u s i o n as separate u n i t s i n the model. However, i f i n d i c a t e d by t h e i r use, beds from these areas were added to the t o t a l number of beds "pooled" f o r the a p p r o p r i a t e s e r v i c e s . 45 5.1.3 Bed Groups As Table I i n d i c a t e s , a p a t i e n t d e s i r i n g admission to most h o s p i t a l s e r v i c e s can request p r i v a t e , s e m i - p r i v a t e or ward accommodation. I s o l a t i o n r e q u ests such as those f o r i n f e c t i o n r e q u i r e p r i v a t e rooms. The d i f f e r e n c e i n accommodation however, i s u s u a l l y a matter of p r e f e r e n c e and c o s t . Of the p a t i e n t s d e s i r i n g non-ward accommodation, some w i l l wait u n t i l i t becomes a v a i l a b l e , o t hers are admitted and t r a n s f e r when a vacancy appears. I f only p r i v a t e accommodation i s a v a i l a b l e , an e l e c t i v e p a t i e n t who d i d not s p e c i f y that type may be c a l l e d and o f f e r e d i t at the e x t r a c o s t . As Lew (1966) c a l c u l a t e d , type of accommodation i s not a s i g n i f i c a n t f a c t o r i n LOS., As i s i n d i c a t e d i n Ta b l e IV, some accommodation i s intended f o r males and some f o r females, as w e l l as some which may be used by e i t h e r sex. However, much j u g g l i n g i s done among small and l a r g e wards to maintain homogeneity by sex. In p r a c t i c e , a p a t i e n t i s seldom r e f u s e d admission ( f o r very long anyway) due to h i s or her sex. I t i s very d i f f i c u l t t o keep t r a c k of p a t i e n t movements i n the h o s p i t a l . No r e c o r d i s kept of l o c a t i o n (except perhaps f o r b i l l i n g purposes). The main bed board, the p a t i e n t f i l e , and the ward records show where a p a r t i c u l a r p a t i e n t i s , but i t would be d i f f i c u l t t o keep p r e c i s e r e c o r d s of the path through the h o s p i t a l f o r any l a r g e number of p a t i e n t s . As a r e s u l t , there have only been a few s m a l l s t u d i e s of p a t i e n t t r a n s f e r s done a t St. Paul's. 46 TABLE IV BEDS BY SEX S e r v i c e M F M or F Gynecology 20 21 EENT 6 12 17 Orthopedics 40 30 Urology 29 7 7 Neurology 6 6 6 11 Neurosurgery General Surgery 33 38 36 C a r d i a c Unit 4 11 47 As a r e s u l t of the c o n s i d e r a t i o n s mentioned above, the model we developed d i d not group beds by accommodation or sex. Each s e r v i c e was c o n s i d e r e d to have a " p o o l " of beds from which each p a t i e n t used one. 5.2 Admitting C o n s i d e r a t i o n s The Admitting O f f i c e i s r e s p o n s i b l e f o r placement of p a t i e n t s i n the h o s p i t a l . Medical booking forms and s u r g i c a l booking forms (once the date of surgery and hence of admission has been determined) are f i l e d there. Emergency p a t i e n t s are a l s o placed by t h i s o f f i c e . For s p e c i a l c a r e u n i t s or t e a c h i n g areas the r e s i d e n t p h y s i c i a n may c o n t r o l the beds, but f o r most areas, an admitting c l e r k decides who goes where. T r a n s f e r s are a l s o c o - o r d i n a t e d by the o f f i c e , and i t i s informed of d i s c h a r g e s . I t maintains the w a i t i n g f i l e s and the bed board. 5.2.1 Bed Usage Bed space i s the c r i t i c a l f a c t o r i n S t . Paul»s H o s p i t a l . The primary c o n s t r a i n t on s c h e d u l i n g surgery i s the number of beds a v a i l a b l e . Occupancy averages about 93%, and i s even higher i n mid week, T h e o r e t i c a l l y about eighteen beds are meant to be reserved f o r emergency p a t i e n t s , but t h i s i s not s t r i c t l y observed. As a r e s u l t , p a t i e n t s must sometimes be placed t e m p o r a r i l y i n TV rooms or a l c o v e s . About 25% of the Medical p a t i e n t s and 15% of the s u r g i c a l p a t i e n t s are i n i t i a l l y admitted 48 to the wrong area. Quite a few are never t r a n s f e r r e d to the proper area. In the nursing u n i t s d e s c r i b e d i n Table I , i t i s known t h a t many of the beds may be used f o r other s e r v i c e s . Of the 41 Gynecology beds, about ten are u s u a l l y f i l l e d with non-Gynecology p a t i e n t s . The same holds true f o r the 43 Urology beds, f o r which the ten o f f - s e r v i c e p a t i e n t s are o f t e n from General Surgery. Most of the General Surgery misplacements are among the A, B, and C areas. Orthopedic p a t i e n t s may be placed i n Neurosurgery beds.. ENT p a t i e n t s may go to Orthopedic beds. Though by no means an exhaustive or g u a n t i t a t i v e l i s t , the preceding statements are suggestions from the Admitting O f f i c e of probable v a r i a t i o n s . E l e c t i v e p a t i e n t s are seldom admitted to the wrong area. I t i s the emergency a r r i v a l s who r e g u i r e s h u f f l i n g . The f a c t that about 45% of t o t a l and 75% of Medical admissions are emergent or d i r e c t urgent (DU) u n d e r l i n e s the magnitude of the problem. When these p a t i e n t s a r r i v e , one cannot expect the a v a i l a b l e beds to be where one would l i k e them to be. 5.2.2 Seguence o f Claims on Beds Since i t i s c l e a r t h at the Admitting O f f i c e cannot always o f f e r the r i g h t bed, then some p a t t e r n i n handl i n g c l a i m s on beds must be f o l l o w e d . When new s t a f f a r r i v e s each morning, i t i s faced with a number of i n - h o s p i t a l p a t i e n t s who may e i t h e r r e g u i r e or d e s i r e t r a n s f e r and a number o f e l e c t i v e p a t i e n t s 49 d e s i r i n g admission. As has been i n d i c a t e d , the OR Booking O f f i c e schedules p a t i e n t s f o r surgery, then sends the Admitting O f f i c e a copy of the admission booking form with the date of d e s i r e d admission stamped on i t , to be f i l e d and arranged there. The Admitting o f f i c e t r i e s not to d i s r u p t t h i s process. F a i l u r e to admit a s u r g i c a l case when scheduled i s a "No Bed" s i t u a t i o n , to be d i s c u s s e d i n the next s e c t i o n . Thus the major concern of the Admitting O f f i c e i s i n the use of Medical beds. An approximate s e q u e n t i a l p a t t e r n which the Admitting O f f i c e uses i s as f o l l o w s . L a t e overnight admissions to the emergency u n i t must be placed i n the h o s p i t a l . A l s o , p a t i e n t s who had to be placed i n a Medical area " c l o s e d t e a c h i n g bed" (to be e x p l a i n e d i n S e c t i o n 5.2.5) a g a i n s t the w i l l of the r e s i d e n t should be moved. Next, p a t i e n t s who had to be placed i n a l c o v e s or TV rooms on previous s h i f t s should be moved t o proper areas.. The ICU should be emptied of p a t i e n t s no l o n g e r r e q u i r i n g i t s f a c i l i t i e s , p a r t i c u l a r l y i f i t i s a period o f high demand f o r i n t e n s i v e c a r e . . For those p a t i e n t s s t i l l i n the f i v e " e x t e n s i o n beds" of the PAR ( f o r up to 24 hours of p o s t - o p e r a t i v e monitoring) placement should be arranged elsewhere. Medical p a t i e n t s who have been found to need surgery should be t r a n s f e r r e d to an a p p r o p r i a t e s u r g i c a l area., A f t e r these, an attempt should be made t o move any other p a t i e n t s who are i n the wrong area, p a r t i c u l a r l y M edical emergency p a t i e n t s who had t o be put i n a s u r g i c a l area. A f t e r a l l these moves, and a f t e r some allowance f o r the day's emergencies, i f there are any beds l e f t then 50 s c h e d u l a b l e admissions may be considered, 5.2.3 "No Bed" S i t u a t i o n s The OR Booking O f f i c e schedules each p a t i e n t f o r surgery and, i n d i c a t i n g the necessary admission date a c c o r d i n g to the p r e - o p e r a t i v e stay s p e c i f i e d by the a d m i t t i n g p h y s i c i a n , sends a copy of the admission booking form to the Admitting O f f i c e w ell i n advance. I f when the admission date a r r i v e s , the Admitting O f f i c e cannot f i n d a bed to put the p a t i e n t i n , i t i s r e f e r r e d to as a "No Bed" s i t u a t i o n . The OR Booking O f f i c e must inform the surgeon, and t r y to reschedule h i s p a t i e n t w i t h i n two weeks ( u s u a l l y i t i s attempted one week l a t e r ) . They must t r y t o f i l l the vacant spot on the upcoming s l a t e . The p a t i e n t must be informed of the change. For obvious reasons, t h i s i s an u n d e s i r a b l e s i t u a t i o n . I t upsets the p a t i e n t , who probably had to arrange f o r time o f f from h i s or her job, and perhaps f o r a b a b y s i t t e r . , Such inconvenience, although i n a d v e r t e n t , r e f l e c t s badly on the h o s p i t a l . . Repeated d i f f i c u l t y of t h i s s o r t a t one h o s p i t a l w i l l cause a p h y s i c i a n to favour another. A l s o , i t d i s r u p t s the s l a t e . N evertheless, "No Bed" s i t u a t i o n s happen q u i t e o f t e n . Most of my data i s from 1974 when, i n 250 o p e r a t i n g days, only 160 were f r e e of "No Beds". There was an average of 39 "No Bed" cases per month, with up to twenty on a s i n g l e day. These c a n c e l l a t i o n s occur i n a l l s u r g i c a l s e r v i c e s . There has been 51 some improvement s i n c e 1974 {the 1976 average was 31 per month), but i t i s s t i l l a r e a l concern t o a d m i n i s t r a t i o n . 5.2.4 P a t i e n t Admission D i a g n o s t i c C a t e g o r i e s A l l f i v e p a t i e n t admission c a t e g o r i e s {based on d i a g n o s i s ) were c o n s i d e r e d . Three of these are s c h e d u l a b l e and are i n d i c a t e d by the p h y s i c i a n on the admission booking form which i s submitted f o r the p a t i e n t . They are urgent, semi-ur§ent and e l e c t i v e , There are a l s o the emergency and d i r e c t urgent c a t e g o r i e s , which r e q u i r e immediate-attention. Each of the c a t e g o r i e s except DU i s broadly d e f i n e d by h o s p i t a l p o l i c y . The e x c e r p t s which f o l l o w are from Appendix I of a d i r e c t i v e t o p h y s i c i a n s i n May 1973. An emergency c o n d i t i o n i s so severe that "death, severe p a i n , c h r o n i c i l l n e s s or permanent d i s a b i l i t y may r e s u l t i f h o s p i t a l treatment i s not given". Such p a t i e n t s should be admitted w i t h i n 24 hours. An urgent c o n d i t i o n i s "one of moderate s e v e r i t y which may develop i n t o a s t a t e of emergency or the p a t i e n t may s u f f e r s e r i o u s d e t e r i o r a t i o n i f h o s p i t a l treatment i s delayed f o r more than a maximum of f o u r t e e n days". A semi-urgent admission need not be w i t h i n two weeks, but should not be over two months. E l e c t i v e p a t i e n t s d e s i r e admission, but "a delay should not d i r e c t l y t h r e a t e n l i f e or h e a l t h " . In p r a c t i c e a p a t i e n t i s only c l a s s i f i e d t o be an emergency case i f he i s admitted v i a the emergency department. There i s a f u r t h e r c l a s s i f i c a t i o n used, c a l l e d " d i r e c t urgent", which 52 probably i n c l u d e s some p a t i e n t s who c o u l d be c l a s s i f i e d as emergent and some as urgent. These are p a t i e n t s f o r whom, when the p h y s i c i a n sees them at h i s o f f i c e o r elsewhere, he decides they should be admitted very g u i c k l y . He c o n t a c t s the admitting O f f i c e immediately to see i f there i s any room. I f so, the p a t i e n t goes d i r e c t l y to the a d m i t t i n g O f f i c e and i s admitted to the h o s p i t a l . I f there i s no room i n the immediately f o r e s e e a b l e f u t u r e , the p h y s i c i a n may f i l l out an admission booking form i n d i c a t i n g t h a t the p a t i e n t i s urgent and submit i t - with some added emphasis - to the admitting O f f i c e , or he may send the p a t i e n t to the emergency u n i t . When beds are f u l l , but the p h y s i c i a n f e e l s s t r o n g l y enough that he sends h i s p a t i e n t t o the emergency u n i t , h o s p i t a l s t a f f terms i t a "backdoor admission." I t i s c l a s s i f i e d as an emergency and i s not d i f f e r e n t i a t e d i n any r e c o r d s . O n f o r t u n a t e l y , the slow movement of the w a i t i n g gueue, p a r t i c u l a r l y f o r Medicine, o f t e n r e s u l t s i n such t a c t i c s (a device which c l e a r l y perpetuates i t s e l f ) . Of the scheduled admissions, t h e o r e t i c a l l y a l l urgent p a t i e n t s are handled f i r s t , than a l l semi-urgents, then the e l e c t i v e s . In p r a c t i c e , t h e r e i s a f a i r amount of judgment i n p r i o r i t y adherence. J The p h y s i c i a n may change the c l a s s i f i c a t i o n , or by communication with the a d m i t t i n g c l e r k s may i n f l u e n c e h i s p a t i e n t ' s p r i o r i t y . Furthermore, d e s p i t e the d e s c r i p t i o n given by the h o s p i t a l , the use of these d i a g n o s t i c c a t e g o r i e s d i f f e r s among p h y s i c i a n s . (See a l s o the comments i n S e c t i o n 12.1.) 53 5.2.5 C o n t r o l of Medical Beds St. Paul's i s a teaching h o s p i t a l . As a r e s u l t , the Admitting O f f i c e does not have complete freedom i n a s s i g n i n g beds to p a t i e n t s . For i n s t r u c t i o n a l purposes, t h e r e a r e some beds over which the r e s i d e n t has c o n t r o l . In n u r s i n g u n i t 2 South B, a l l of the beds are " c l o s e d teaching beds". , T h i s means that the r e s i d e n t has almost complete c o n t r o l . , In l a t e evening or a t n i g h t , the Admitting O f f i c e may place emergency p a t i e n t s t h e r e before f i l l i n g a l c o v e s . However, i f these p a t i e n t s are not t r a n s f e r r e d out the next day, the r e s i d e n t i n charge w i l l probably inform the Admitting O f f i c e of h i s d i s p l e a s u r e . There are e i g h t e e n semi-closed t e a c h i n g beds i n 2 South A and twenty more i n 2 North. I f these are r e g u i r e d f o r ICU or emergency p a t i e n t s , the Admitting O f f i c e may inform the r e s i d e n t r e s p o n s i b l e f o r the beds, and use them, The t e a c h i n g r e s i d e n t r e g u l a r l y l o o k s over the f i l e d admission forms and p i c k s out " i n t e r e s t i n g " ones. A c t i v e s t a f f members a l s o make arrangements with the r e s i d e n t s to admit t h e i r p a t i e n t s to t e a c h i n g beds. In f a c t , one of the few ways f o r an e l e c t i v e p a t i e n t to e n t e r a St. Paul's Medical bed e a s i l y i s to be chosen f o r a t e a c h i n g bed. H o s p i t a l g u i d e l i n e s - given the high demand f o r beds - suggest t h a t i f more than 20% of the p a t i e n t s i n t e a c h i n g beds are not those chosen by the r e s i d e n t , the Admitting O f f i c e should t r a n s f e r the wrong ones out. S t i l l , r e s i d e n t s c l a i m that 54 t h e r e are sometimes 25% or 50% "non-teaching" p a t i e n t s i n t h e i r beds. Due to the complexity of ga t h e r i n g data on who gets t e a c h i n g beds, the v a r i a t i o n of LOS between t e a c h i n g and non-teaching p a t i e n t s , and the l a c k of a c o n s i s t a n t p a t t e r n i n using the beds, t e a c h i n g beds have not been d i f f e r e n t i a t e d i n the model. A l l Medical beds are used i d e n t i c a l l y . 5.2.6 S u r g i c a l Non-Operative Admissions Not a l l of the p a t i e n t s who are scheduled to enter a s u r g i c a l area bed are operated on. Sometimes a p h y s i c i a n wants to admit a p a t i e n t f o r i n v e s t i g a t i o n before d e c i d i n g whether surgery i s a d v i s a b l e . The booking forms f o r p r e - i n v e s t i g a t i v e surgery p a t i e n t s go t o the Admitting O f f i c e {rather than the OH Booking O f f i c e ) . Such p a t i e n t s are admitted on weekdays, s i n c e X-ray and l a b f a c i l i t i e s are o n l y a v a i l a b l e on an emergency b a s i s on the weekend. Sin c e i t i s not c l e a r how many p a t i e n t s of t h i s type there are { i t appears t h a t there are few) nor how many of these are l a t e r operated on (these would be i n c l u d e d i n i n - h o s p i t a l demands anyway), the model d i d not d i f f e r e n t i a t e these p a t i e n t s . I t should a l s o be noted that a number of other s u r g i c a l p a t i e n t s (many from the Emergency Unit) are never operated on. P a t i e n t s with b l e e d i n g u l c e r s or traumas t h a t s t a b i l i z e Orthopedic "bed r e s t " p a t i e n t s , p a t i e n t s f o r N e u r o s u r g i c a l t e s t s and Urology p a t i e n t s who pass t h e i r stones are of t h i s type. 55 5.2-7 - G e n e r a l St. Paul's has a l a r g e r e f e r r a l program, f o r which p a t i e n t admission i s handled through a l o c a l c o n s u l t a n t . Some pr e f e r e n c e may be given to out-of-town p a t i e n t s . Often the p h y s i c i a n requests a p a r t i c u l a r admission day. There i s no l i m i t to the number of forms which a p h y s i c i a n may submit. A l i m i t of f i v e had been recommended i n order that the p h y s i c i a n would i d e n t i f y h i s h i g h e s t - p r i o r i t y p a t i e n t s . The Admitting o f f i c e attempts to ensure t h a t a p a t i e n t i s not c a n c e l l e d a second time due to "No Bed". There i s a number of s t a f f c a t e g o r i e s : Honorary, V i s i t i n g C o n sultant, Senior A c t i v e , A c t i v e , A s s o c i a t e , Courtesy, Non-Active Courtesy, C l i n i c a l F e l lows, Dental, and S c i e n t i f i c and Research. These are d e s c r i b e d i n "Medical S t a f f By-Laws". For admission p r i o r i t y , s t a f f category i s only c o n s i d e r e d "other t h i n g s being e q u a l " and hence i s seldom a f a c t o r (most admissions are by a c t i v e s t a f f anyway). As a r e s u l t , s t a f f category was not i n c l u d e d i n the model. 5.3 S u r g i c a l Scheduling C o n s i d e r a t i o n s For the past two years, St. Paul's H o s p i t a l has had a separate OR Booking o f f i c e . Admission booking forms f o r s u r g i c a l p a t i e n t s ( n o n - i n v e s t i g a t i v e ) are sent there from the p h y s i c i a n . The p a t i e n t i s scheduled f o r su r g e r y and the necessary admission date i s i n d i c a t e d on one copy of the form. 56 which i s then taken to the Admitting O f f i c e which handles the admission. Although i t i s simple to say "scheduled f o r surgery", there are many f a c t o r s t o be c o n s i d e r e d . These are now d i s c u s s e d . 5.3.1 Operating Rooms Table I I , with i t s d a i l y s l a t e s u b d i v i s i o n , a l s o i n d i c a t e s how the v a r i o u s o p e r a t i n g rooms are normally used - or r a t h e r were as of J u l y 1976., In August, Orthopedics and Gynecology switched rooms. There are a c t u a l l y nineteen rooms, but not a l l a r e needed and, s t a f f c l a i m , none i s r e a l l y l a r g e enough. Tabl e V gives approximate s i z e s of the rooms, and comments on t h e i r use. 5.3.2 Use of Information on the Admitting Forms There are s e v e r a l pieces of i n f o r m a t i o n on the admission booking form which are u s e f u l i n s c h e d u l i n g . The f i r s t , of course, concerns whether I n - P a t i e n t or Day Care s u r g e r y (the model does not c o n s i d e r the l a t t e r ) i s d e s i r e d . The type of admission ( d i a g n o s t i c category) and date p r e f e r r e d are used t o determine roughly when to t r y to f i t the p a t i e n t i n . The type of case may cause i t t o use one of f i v e o vernight PAR "e x t e n s i o n beds" or c e r t a i n s p e c i a l equipment, but n e i t h e r of these c o n s t r a i n t s was c o n s i d e r e d c r i t i c a l enough to be i n c o r p o r a t e d i n the model. Also, the p h y s i c i a n i s noted, because each has an 57 TABLE OPERATING V ROOMS Room S i z e 1 Large 6 7 8 9 10 11 12 Medium Medium Tiny Medium Small } } Small } Small } 3 Small } Large 13 Medium 14 Large 15 Small 16 Medium 17 Small 18 Medium Usual Use Orthopedics Medium General Surgery Medium Urology urology (Cystoscopy) Day Care (Cystoscopy) Storage Day Care ENT Opthalmology Open Heart Va s c u l a r Pathology Lab General Surgery Vascular Cast Room Gynecology General Surgery Neurosurgery & P l a s t i c Surgery Use Comments Formerly Gynecology Can be Gen'l Surgery or almost anything - even double setups Use by Gen'l Surgery A, B, or C determined by case type S day Seldom 3 and 4 both i n use Often f r e e f o r emergencies Only f o r cystoscopy Does most of Urology cases Only f o r Cystoscopy U s u a l l y r e s e r v e d f o r Day Care E x c l u s i v e l y Day Care Small l i g h t s In a pinch, could do something e l s e - of the f o u r , 10 i s best One OH per day, then v a s c u l a r I f spare time, can do anything Use by Gen'l Surgery A, B, or C determined by case type & day Formerly Orthopedics Use by Gen'l Surgery A, B, or C determined by case type & day Cramped, but p o s s i b l e f o r other 19 Large X-ray S p e c i a l X-ray eguipment only 58 upper l i m i t on the number o f beds he may book per day and, i f he i s not on a c t i v e s t a f f , h i s request may be of lower p r i o r i t y . The date of r e c e i p t i s stamped on the form. The number of days f o r p r e - o p e r a t i v e s t a y are noted, with the reason., For example, i f X-rays are needed, the surgery w i l l not be scheduled f o r Honday, s i n c e X-rays are not done over the weekend. 5.3.3 Pre-Operative Stay The p h y s i c i a n always i n d i c a t e s the p r e - o p e r a t i v e s t a y r e q u i r e d f o r h i s p a t i e n t . For 60%-70% of the p a t i e n t s i t i s only the niqht before. P a t i e n t s needing blood are u s u a l l y i n the h o s p i t a l a f u l l day b e f o r e surgery, those r e q u i r i n g X-rays or t e s t s probably two days. Heart, v a s c u l a r and bowel p a t i e n t s need about three days p r e p a r a t i o n . Obese p a t i e n t s a r e the most time-consuming, needing f i v e or more days before surgery. 5.3.4 Block Booking The OR Booking O f f i c e cannot choose to schedule a p a t i e n t on j u s t any day which f i t s t h e other c o n s t r a i n t s . Most s u r g i c a l s e r v i c e s at St. Paul's are "block booked". Rooms are blocked out so that each day c e r t a i n p h y s i c i a n s are given t h e i r t u r n . One major advantage o f t h i s system concerns a surgeon's p r i v a t e p r a c t i c e . I f he knows that he may expect to operate on, say, Wednesday mornings, he can plan h i s o f f i c e hours well i n advance, with that p r o v i s i o n . 59 Block booking a l s o enables a surgeon t o r e g u l a t e h i s demand and e x p e c t a t i o n s of the s u r g i c a l booking. Depending on how long h i s o p e r a t i o n s are l i k e l y to take, he knows how many forms t o submit and, i f he c a r e s to, he may probably p r e d i c t which day a p a r t i c u l a r p a t i e n t w i l l be operated on. For t h a t matter, the p h y s i c i a n may request that h i s p a t i e n t be s l a t e d on a p a r t i c u l a r day f o r which he i s booked. However, t h e r e i s a l i m i t to the p h y s i c i a n ' s c o n t r o l of the block. In p a r t i c u l a r , i f he has not f i l e d enouqh request forms t o f i l l h i s block e i g h t days i n advance, h i s block i s thrown open f o r urqent p a t i e n t s of other surqeons, and f o r i n - h o s p i t a l requests. Neurosurgery and P l a s t i c Surgery are not block booked. General Surgery i s blocked by " s e r v i c e " c a t e g o r y A, B, and C on l y , not by p h y s i c i a n . 5.3.5 S e r v i c e C h a r a c t e r i s t i c s Since General Surgery i s blocked by s e r v i c e o n l y , some attempt i s made to balance by surgeon as w e l l . G e n e r a l l y one p a t i e n t f o r each a c t i v e s t a f f surgeon i s chosen at a time. Choice i s guided by the date o f r e c e i p t of the form, and each c h o i c e i s placed on the s l a t e e i g h t days i n advance. There i s no General Surgery backlog. V a s c u l a r surgery has the e q u i v a l e n t of two days of blocked time per week, and i s always booked up. The open heart spots are u s u a l l y f i l l e d f o r a month ahead. The Neurosurgery and P l a s t i c Surgery s l a t e i s a l s o prepared 60 e i g h t days i n advance, r a t h e r than being developed as forms a r r i v e . Orthopedics and Gynecology spots are o f t e n not used by the blocked surgeon, but are f i l l e d up a f t e r being opened to others of the s e r v i c e . Urology i s not thrown open very o f t e n . , I t has no backlog. EENT i s o f t e n booked f o u r t o s i x weeks ahead. 5.3.6 L i m i t a t i o n s on Scheduling The main l i m i t on s c h e d u l i n g f o r surgery i s the number of beds. I f p a t i e n t s with a s c h e d u l a b l e admission category are booked up to the bed l i m i t s , t h e r e i s always room l e f t f o r i n - p a t i e n t s . Approximate bed l i m i t s by s e r v i c e appear on Table VI. The recovery room can only take f i v e " e x t e n s i o n s " {overnight p a t i e n t s ) . These beds are monitored c l o s e l y , and are r e q u i r e d f o r such cases as heart o p e r a t i o n s , pacemakers, tumors, c r a n i o t o m i e s , chest o p e r a t i o n s and p e r i n e a l s . There are a l s o some equipment and instrument c o n s t r a i n t s . The laparoscope may be used f o r one d i a g n o s t i c and one o p e r a t i v e procedure per day. The mediastinoscope and arthroscope may be used once per day. The image i n t e n s i f i e r can only be used on one procedure at a time. Although the Booking O f f i c e must c o n s i d e r these c o n s t r a i n t s , they are not c r i t i c a l {and p a t i e n t s are not c l a s s i f i e d so d i s t i n c t l y as to be i d e n t i f i e d as needing them), so the model does not c o n s i d e r such l i m i t s . , TABLE VI BED LIHIT GUIDELINES S e r v i c e per day per week Gynecology 4 19 Urology 5 ENT 6 Opthalmology 6 Orthopedics 4 17 Neurosurgery 2 } } 19 P l a s t i c Surgery 3 } General Surgery A 2 rooms H / H ; .1 F } B 1 room H / Tu ; 3 Th } 9 C 2 rooms Tu / F ; 1 W } TABLE VII IN-HOSPITAL DEMANDS FOR SURGERY S e r v i c e Number • " ~ " General Surgery 4 -6 / day Vascu l a r 2 / week Open Heart 1 / week Urology 1 V day Orthopedics 1 / (2 days) Neurosurgery 2 / wee k P l a s t i c Surgery 1 / week Gynecology 1 / week EENT 1 / (2 weeks) 62 The major nature of c e r t a i n cases r e q u i r e s t h a t they be done " f i r s t t h i n q " (at 8 am). At that time any " t o t a l h i p " o p e r a t i o n s s t a r t i n room 1, craniotomies i n room 18 and abdominal p e r i n e a l s i n room 14. 5 . 3 . 7 C o n s i d e r a t i o n s of A u x i l i a r y S t a f f In q e n e r a l , t h i s model assumes that the h o s p i t a l w i l l employ whatever l e v e l s of a u x i l a r y s t a f f (nurses, a n a e s t h e t i s t s , and others) t h a t the l e v e l of demand by p h y s i c i a n s and p a t i e n t s warrants. They are never e x p r e s s l y i n c l u d e d as e n t i t i e s i n the model. However, i t i s worth n o t i n g the e f f e c t of a u x i l i a r y s t a f f on turnaround time, adherence to the day's s l a t e , and OR a v a i l a b i l i t y a f t e r 3:30 pm. Turnaround time (between o p e r a t i o n s i n a p a r t i c u l a r theatre) depends on s e v e r a l f a c t o r s - which are i n f l u e n c e d by the preceding and f o l l o w i n g o p e r a t i o n s . Does the a n a e s t h e t i s t need t o s t a b i l i z e the l a s t p a t i e n t ? I s t h e r e a housekeeper a v a i l a b l e immediately to wash up - or are they a l l busy elsewhere? How q u i c k l y can the n u r s i n q s t a f f prepare instruments f o r the next operation? In bookinq time, the OR Booking O f f i c e a l l o w s one q u a r t e r hour between minor o p e r a t i o n s , one h a l f hour between major ones, and more f o r v a s c u l a r or N e u r o s u r q i c a l cases. In r e a l i t y , major or minor o p e r a t i o n s can r e q u i r e anywhere from about f i v e t o f o r t y minutes turnaround. The model, not o p e r a t i n q on a s m a l l time s c a l e anyway, o n l y uses a f i x e d turnaround time. 63 There are two charge nurses and a head nurse who, i n a d d i t i o n to monitoring and e v a l u a t i n g nursing s t a f f , may a l s o p l a c e e x t r a nurses or step i n themselves i n order t o help the s l a t e run as timed. They make sure that a l l of the nursing s t a f f members get breaks. The head nurse can arrange f o r e x t r a nurses i f cases get behind. Up to two "stagger nurses" can be c a l l e d to help with l a t e cases and r e l i e f . I t i s p r e f e r r e d t o have two nurses per room (as well as one nurses* a i d ) , "Open he a r t " gets three nurses. Normally cases run from 8:00 am t o 3:30 pm. Besides the r e g u l a r nurses f o r t h i s time, t h e r e are f o u r afternoon nurses (one from 3 to 11 and three from 3:30 to 11:30). Two n i g h t s h i f t nurses come on, so tha t a f t e r 11:30 pm, one emergency room can be used as long as necessary. I t i s worth n o t i n g t h a t no p a t i e n t i s ever removed from the day's s l a t e , whatever the l e n g t h of p r e v i o u s o p e r a t i o n s . 5.3.8 I n - H o s p i t a l Demands One of the major c o m p l i c a t i n g f a c t o r s i n s c h e d u l i n g the s l a t e i s t h a t p h y s i c i a n s may submit requests f o r surgery f o r t h e i r p a t i e n t s a l r e a d y i n the h o s p i t a l . Some of these have already had one o p e r a t i o n . For General Surgery, Neurosurgery or P l a s t i c Surgery, such requests u s u a l l y wait f o r the proper p h y s i c i a n ' s next day of surgery., Requests from the other s e r v i c e s are added to the s l a t e as soon as p o s s i b l e . , I f an i n - p a t i e n t happens to r e f u s e a time t h a t i s o f f e r e d , he goes t o 64 the end of the l i s t a g ain. Approximate numbers of demands from the v a r i o u s s e r v i c e s appear on Table VII. I n - h o s p i t a l r e q u e s t s are placed i n spots l e f t unclaimed by p h y s i c i a n s , \or i n time l e f t a f t e r o u t p a t i e n t s were l i m i t e d due t o bed space., 5.3.3 Handling o f Emergencies When a p h y s i c i a n comes to the o p e r a t i n g f l o o r r e q u e s t i n g surgery f o r h i s i n - p a t i e n t , the main q u e s t i o n i s "How urgent i s i t ? " . I f p o s s i b l e , the request w i l l be d e f e r r e d t o the next day and scheduled on the s l a t e . For those which should be handled the same day, but!' can wait, they are orqanized on a f i r s t - c o m e f i r s t - s e r v e d b a s i s at the end of the s l a t e . Any chanqe i n order would be worked out on a p h y s i c i a n - t o - p h y s i c i a n b a s i s . For emergencies which should be handled promptly, such as haemorrhaging i n the PAR, t h e r e i s always a place to go. (There are always s e v e r a l rooms not i n use.) The l a r g e s t a v a i l a b l e room i s always chosen. The a n a e s t h e t i s t on c a l l and n u r s i n g s t a f f are summoned. Another option i s to "break the s l a t e " of some room, hence making i t l a t e . I f the p a t i e n t i s s t a b l e , the case i s i n s e r t e d when a s t a f f e d room becomes f r e e . Since the model only operates on a one-day time u n i t , i t i s not necessary t o d i f f e r e n t i a t e among emergency handling methods. The model's output merely i n d i c a t e s the t o t a l time used each day f o r emergencies - which i s , i n f a c t , recorded by h o s p i t a l s t a f f . 65 5.3.10 Timing of S l a t e C o n s t r u c t i o n The OR Booking O f f i c e has a six-week v i s u a l f i l e on which booking forms are i n s e r t e d . As these forms a r r i v e , they are added to the f i l e , depending on c o n s i d e r a t i o n s mentioned p r e v i o u s l y . The p h y s i c i a n has u s u a l l y estimated o p e r a t i n g time to a m u l t i p l e of one q u a r t e r hour. The booking nurse a d j u s t s the time a c c o r d i n g to that p h y s i c i a n ' s tendency toward accuracy or i n a c c u r a c y i n e s t i m a t i o n . ,• Keeping w i t h i n time and room l i m i t s , she f i l l s i n the s l a t e s f o r each day. Bookings are never scheduled to run past 3:30 pm. Once the o p e r a t i n g day i s e i g h t days away, any open spots on the s l a t e may be f i l l e d with urgent or i n - h o s p i t a l demands. Ext r a space may go to n o n - a c t i v e s t a f f . , Real urgents (those the p h y s i c i a n would c l e a r l y l i k e to have admitted q u i c k l y ) are u s u a l l y not kept w a i t i n g over a week. A copy of the s l a t e i s prepared i n the a f t e r n o o n two days ahead., The next morning, p h y s i c i a n s and the Admitting O f f i c e are checked to make sure e v e r y t h i n g i s OK. C a n c e l l a t i o n s , "No Beds" and i n - p a t i e n t s s t i l l cause changes. Then about noon the f i n a l copy i s made. T h i s w i l l c o n t r o l OR usage the f o l l o w i n g day., 5.3.11 General There are a few other f a c t o r s which a f f e c t OR s c h e d u l i n g . Besides p h y s i c i a n s ' o f f i c e hours (which the Booking O f f i c e knows) , t h e i r time away f o r conferences and h o l i d a y s must be 66 observed. Some rooms are o c c a s i o n a l l y u n a v a i l a b l e due to maintenance. There are a l s o some unexpected sources of problems., For example, a p a t i e n t may be s l a t e d , and admitted. Then, a f t e r t a l k i n g to other p a t i e n t s around him, he may r e f u s e to s i g n the surgery consent form. Such t h i n g s do not happen very o f t e n and are not i n c l u d e d i n the model. 67 CHAPTER 6 MA JOE FLOP? •PATTEgjlS- 6. 1 Purpose and Form The extended f l o w c h a r t system presented i n t h i s chapter v i s u a l l y d e s c r i b e s the model framework and i d e n t i f i e s a l l r e l e v a n t i n t e r a c t i o n s w i t h i n the system. During the development of the model these c h a r t s c o n t r i b u t e d t o and were r e f i n e d by the processes of c l a r i f y i n g r e l e v a n t model f e a t u r e s and determining data requirements. The f i n a l form of the f l o w c h a r t s i n c l u d e s m o d i f i c a t i o n s and assumptions which had to be made t o d e a l with the u n a v a i l a b i l i t y of data on some asp e c t s of the system. In system f l o w c h a r t s , two streams are o f t e n i d e n t i f i e d , i n f o r m a t i o n flow and p h y s i c a l flow. In the d e s c r i p t i o n used here, the " p h y s i c a l u n i t " o f i n t e r e s t i s the p a t i e n t . These diagrams a c t u a l l y d e s c r i b e i n f o r m a t i o n flow r e l a t i v e to the p a t i e n t s . For example, when an admission request a r r i v e s at the h o s p i t a l , i t a r r i v e s as a form, as i n f o r m a t i o n , u s u a l l y unaccompanied by a p a t i e n t . When a p a t i e n t i s s l a t e d f o r surqery, aqain there i s no a c t u a l p a t i e n t at hand, but the inf o r m a t i o n i s v i t a l l y important to t h i s model. Of course, once the p a t i e n t a r r i v e s at the h o s p i t a l , the p h y s i c a l and in f o r m a t i o n flows o f t e n c o i n c i d e . N e v e r t h e l e s s , i t w i l l probably be h e l p f u l t o conceive o f the flows here as i n f o r m a t i o n about p a t i e n t s . The format o f t h i s d e s c r i p t i o n tends to f o l l o w the System Book o u t l i n e (Grams 1972). The complexity of the model c a l l s 68 f o r an overview f l o w c h a r t which serve s as a graphic index to subsequent f l o w c h a r t s , and s e v e r a l system f l o w c h a r t s d e p i c t i n g the d e t a i l s of the subsystems. Each f l o w c h a r t symbol has a number i n parentheses a s s o c i a t e d with i t which tags an o p e r a t i o n s statement g i v i n g any necessary or u s e f u l e x p l a n a t i o n . 6.2 Overview Flowchart T h i s f i r s t f l o w c h a r t s e t s out, i n g e n e r a l terms, the p a t i e n t i n f o r m a t i o n flows of the model. 69 SURGICAL SCHEDULABLE ADMITTING • AND OR BOOKING PROCESS GENERATE AND IDENTIFY ADMISSION REQUEST (1) (2) 1 t 1 SURGICAL BED POOL AND OR FILES IN-HOSPITAL TRANSFERS AND OR DEMANDS (6) (5) .00 EMERGENCY ADMITTING PROCESS .(3) MEDICAL SCHEDULABLE ADMITTING PROCESS SPECIAL UNIT BED FILES (7) T * MEDICAL BED POOL FILES DISCHARGES (9) (8) F i g . 6.1 Admission and OR s c h e d u l i n g i n f o r m a t i o n f l o w c h a r t (I) 70 Operations Statements <I) 1. From the p a t i e n t p o o l , r e q u e s t s f o r admission a r r i v e as booking forms from Medical p h y s i c i a n s or s u r g i c a l s p e c i a l i s t s with a d m i t t i n g p r i v i l e g e s , or through emergency {or DO) a r r i v a l s at the h o s p i t a l . , See flo w c h a r t I I A. 2. Schedulable (non-immediate) s u r g i c a l p a t i e n t s " r e q u e s t s undergo coordinated OS booking and admission procedures., See flow c h a r t I I I A. 3. Schedulable Medical p a t i e n t s * requests are processed f o r admission. See f l o w c h a r t IV A. 4., Emergency and DO p a t i e n t s r e g u i r i n g admission are immediately served. See f l o w c h a r t V A. 5., I n - h o s p i t a l demands r e s u l t i n some OS use and bed t r a n s f e r s between pools i d e n t i f i e d here. See f l o w c h a r t VI A. 6. See f l o w c h a r t I I I A. 7. ICO and C a r d i a c u n i t s . See f l o w c h a r t VI A. 8. See f l o w c h a r t IV A. 9. P a t i e n t s no lo n g e r occupying a bed r e t u r n to the p a t i e n t pool (or are deceased). See f l o w c h a r t IV A. 71 6.3 D e t a i l Flowcharts The f l o w c h a r t s and o p e r a t i o n s statements which f o l l o w d e s c r i b e i n d e t a i l the processes i n d i c a t e d on the overview c h a r t . The numbers i n sguare brackets at the end of each comment are c r o s s - r e f e r e n c e s t o any a p p r o p r i a t e data items of Table IX (Data and Information Osed). 72 (i) REQUEST ADMISSION F i g . 6.2 A d m i s s i o n r e q u e s t s f l o w c h a r t (IIA) 73 Operations Statements (II A) 1. P a t i e n t " g e n e r a t i o n " i s by s e r v i c e , and i s p r o p o r t i o n a l to the number of p h y s i c i a n s a c t i v e i n that s e r v i c e . S e r v i c e s : Medicine General Surgery i n c l u d e s v a s c u l a r may i n c l u d e open heart Eye, Ear, Nose and Throat (EENT) Orthopedics Urology Gynecology Neurosurgery } } the model combines these P l a s t i c Surgery } Each p a t i e n t admission reguest i s assigned: s e r v i c e admission d i a g n o s t i c category: \ E l e c t i v e , Semi-Urgent, Urgent, D i r e c t Urgent, Emergent p h y s i c i a n age, sex LOS any requested admission date perhaps ... t r a n s f e r t i m i n g and r o u t i n g f o r those p a t i e n t s t o be operated on: p r e - o p e r a t i v e LOS 74 l e n g t h of surgery [4,5,6,7,8,9,10,11,12, 13] 2. , The immediate (DD,Emergent) and schedu l a b l e (E1,S0,U) c a t e g o r i e s are handled s e p a r a t e l y [ 6 ] 3. The s c h e d u l a b l e p a t i e n t s are d i v i d e d between Medical and s u r g i c a l s e r v i c e s [ 4 ] 4. To the s t a r t o f emergency u n i t p r o c e s s i n g . 5. To the s t a r t o f s u r g i c a l s e r v i c e s p r o c e s s i n g . 6. To the s t a r t o f Medical s e r v i c e s p r o c e s s i n g . 75 F i g . 6.3 S u r g i c a l s e r v i c e s and o p e r a t i n g rooms f l o w c h a r t ( I I I A ) 76 Operations Statements ( I I I A) 1., In the OR Booking O f f i c e , the request forms are f i l e d i n a t e n t a t i v e l o c a t i o n on the six-week v i s u a l f i l e , or i n the f i l e box t o go there. Requested surgery date i s c o n s i d e r e d , as w e l l as p a t i e n t admission d i a g n o s t i c category. Surgery i s g e n e r a l l y block booked by p h y s i c i a n (except f o r General Surgery which i s booked by s e r v i c e A, B, or C, and Neurosurgery / P l a s t i c Surgery which i s not block booked). There are bed l i m i t s f o r each s e r v i c e per day and per week. There are time c o n s t r a i n t s (a maximum of seven hours per t h e a t r e ) . At t h i s p r e l i m i n a r y stage, some f l e x i b i l i t y i s l e f t . [5,6,12,13,14,15,16,17] 2. , S u r g i c a l emergency admissions cause some s l a t e m o d i f i c a t i o n s . About one week ahead of scheduled s u r g e r y , spaces l e f t i n the s l a t e begin t o be f i l l e d by backlog, i n - h o s p i t a l and urgent reg u e s t s . Postponers and "No Bed" p a t i e n t s must be re-booked.. P a t i e n t s who are made to wait a long time may c a n c e l . , [3,24] 3., The Maternity s e r v i c e may be t r e a t e d as an exogenous reguest on OR time, with s e p a r a t e beds., [Not implemented] 4. Is the demand f o r today (on an emergency basis) o r i s i t sche d u l a b l e ? [Not implemented] 5., " F i n a l " here i m p l i e s t h a t a d e f i n i t e surgery day has been determined - so the Admitting O f f i c e may be n o t i f i e d . , Although i t may be known w e l l ahead of time, t h i s o p e r a t i o n i s expected to appear on the f i n a l working copy of the s l a t e wich i s produced one day be f o r e surgery and c o n t r o l s OR usage. 77 6. I f the request was i n - h o s p i t a l , the p a t i e n t need not be admitted. [24] 7. I s t h i s i n - h o s p i t a l p a t i e n t i n a s p e c i a l u n i t or a s u r g i c a l area? 8. Once the day of surgery has been determined, the p r e - o p e r a t i v e LOS assigned by the p h y s i c i a n i s used to s p e c i f y the admission date. T h i s i n f o r m a t i o n i s then f i l e d i n the Admitting O f f i c e . [10 ] 9. The p a t i e n t may postpone. [Not Implemented] 10. I f there i s no a p p r o p r i a t e space f o r a scheduled admission, i t i s a "No Bed" s i t u a t i o n . 11., The p a t i e n t e n t e r s a h o s p i t a l bed. [20,21,23,24] 12. I s the admission to a r e g u l a r s u r g i c a l bed or to a c a r d i a c bed? 13. A record i s kept o f the t o t a l number of scheduled procedures per room and of the t o t a l d a i l y o p e r a t i n g time f o r both scheduled and emergency o p e r a t i o n s . , Emergencies (those procedures which cannot be planned f o r a day i n advance) come from emergency admissions and i n - h o s p i t a l r e q u e s t s . They may be handled: (i) i n a spare room; ( i i ) i n the f i r s t a v a i l a b l e room - which i s a l r e a d y s t a f f e d with nurses and an a n a e s t h e t i s t ; ( i i i ) i n a b a s i c a l l y F i r s t - I n , F i r s t - O u t (FIFO) order a t the end of the s l a t e ( v a r i a t i o n s i n the sequence are arranged on a p h y s i c i a n ^ t o - p h y s i c i a n b a s i s ) . At the completion of the scheduled s l a t e ( e s p e c i a l l y a f t e r 3:30) one or a maximum of two t h e a t r e s may be kept open as long as necessary. [11,17,23] 14. S u r g i c a l bed pool i n f o r m a t i o n i s updated by admissions, 78 t r a n s f e r s and d i s c h a r g e s . I n - h o s p i t a l t r a n s f e r s and OS demands can develop from here. [22,23,24] 15. From s u r g i c a l s e r v i c e admission requests. 16. From s u r g i c a l emergency admissions V A6 and from i n - h o s p i t a l demands VI A6, at l e a s t one day ahead. 17. An o p e r a t i o n f o r a p a t i e n t i n a s p e c i a l u n i t must be noted. 18. The bed which matches may be i n a s p e c i a l u n i t . 19. Open heart p a t i e n t s are admitted to c a r d i a c u n i t beds. 20. From s u r g i c a l emergency admissions V A5 and from i n - h o s p i t a l demands VI A5 which r e g u i r e surgery today. Also , from the s t a t u s of s p e c i a l u n i t p a t i e n t s who are t o be operated on VI A9. 21. To update the s t a t u s of s p e c i a l u n i t p a t i e n t s who have been operated on. 22. From Medical p a t i e n t s t a k i n g a s u r g i c a l bed V A4, emergency s u r g i c a l admissions V A7 and i n - h o s p i t a l t r a n s f e r s to s u r g i c a l beds VI A8. 23. To d ischarges IV A4, i n - h o s p i t a l t r a n s f e r s from surgery VI A1, bed i n f o r m a t i o n f o r t r a n s f e r s VI A2, and i n - h o s p i t a l OB demands VI A4., 79 ( 9 ) ( i i FORM QUEUE WAIT A2) 'IN-HOSP^ N 0 DQJJE YES NO A3) HATCH PATIENT T$>~«-vBED^ DONE NO ^TATIEN YES (5) ADMIT MEDICAL BED POOL INFORMATION t (10) (6) (11) (7) DISCHARGE F i g . 6.4 M e d i c a l s e r v i c e f l o w c h a r t (IVA) 80 Operations Statements {IV A) Note: Scheduled s u r g i c a l i n v e s t i g a t i v e and non-operative p a t i e n t s f o l l o w a s i m i l a r r o u t e , but to a s u r g i c a l bed. 1. A queue forms, ordered by p a t i e n t admission d i a g n o s t i c category and l e n g t h of wait. The s t a f f l e v e l of the p h y s i c i a n and whether or not the p a t i e n t i s out-of-town may a l s o be f a c t o r s . . In p r a c t i c e , the gueue i s almost mental - forms are a c t u a l l y f i l e d with the date of r e c e i p t stamped on them, i n order of the p h y s i c i a n s • l a s t names. Pressure from the p h y s i c i a n i s a a r e a l but unprogrammable f a c t o r . [ 6 ] 2. Each morning, i n - h o s p i t a l t r a n s f e r s must be processed before c o n s i d e r i n g s c h e d u l a b l e admissions. 1 1 ] 3. The admitting c l e r k s attempt to f i n d an a p p r o p r i a t e bed. [19] 4. The p a t i e n t may postpone. [Not Implemented] 5. The p a t i e n t e n t e r s a h o s p i t a l bed. [23,24] 6. Medical bed pool i n f o r m a t i o n i s updated by admissions, t r a n s f e r s , and d i s c h a r g e s . . 7. The p a t i e n t no longer occupies a h o s p i t a l bed. 8. , From Medical s e r v i c e admission requests. 9. From emergency Medical admissions V A3 and t r a n s f e r s to the Medical area VI A3. 10. To i n - h o s p i t a l t r a n s f e r s from the Medical area VI A1 and bed i n f o r m a t i o n f o r t r a n s f e r s VI A2. 11. From s u r g i c a l d i s c h a r g e s I I I A9 and s p e c i a l u n i t d i s c h a r g e s VI A9, 81 F i g . 6.5 Emergency U n i t f l o w c h a r t (VA) 82 Operations Statements {V A) 1. T h i s o v e r a l l process i s the r o u t i n g of emergency p a t i e n t s . P a t i e n t s i n c l u d e d are e i t h e r emergencies or are " d i r e c t urgent" p a t i e n t s from the p h y s i c i a n ' s o f f i c e who are e i t h e r c r i t i c a l or, i n h i s o p i n i o n , need to circumvent the slow admission queue.. I t i s s a f e t o assume that the Emergency U n i t ' s bed c a p a c i t y i s s u f f i c i e n t - o l d beds are a v a i l a b l e i n s t o r a g e i f needed. [2,6] 2. Does the p a t i e n t r e q u i r e c l o s e enough monitoring and / or the s p e c i a l care t o be i n the I n t e n s i v e {and Coronary) Care Un i t ? [Not implemented], 3. I s the p a t i e n t c l a s s i f i e d as Medical or s u r g i c a l ? [ 4 ] 4. I f Medical beds are f u l l ( i n c l u d i n g semi-closed, perhaps c l o s e d , and some "overflow" beds) the p a t i e n t may occupy a s u r g i c a l bed.. These p a t i e n t s probably cause i n - h o s p i t a l t r a n s f e r s soon. The s e m i - c l o s e d , c l o s e d , and overflow beds used at t h i s p o i n t w i l l probably cause t r a n s f e r s soon., [18,20,21,22] 5. Is surgery needed immediately? [23] 6. Does the p a t i e n t i n f a c t r e q u i r e any o p e r a t i o n s , or only the care provided i n a s u r g i c a l area? [23,24] 7. I s t h i s a c a r d i a c emergency or one of another s e r v i c e ? [ 4 ] 8. From emergent admission r e g u e s t s . 9. To the ICU. (Perhaps a t r a n s f e r should be arranged.) 10. To a Medical bed. (Some w i l l cause t r a n s f e r s . ) 11. A Medical p a t i e n t i s placed i n a s u r g i c a l bed, . . . w h i c h probably causes a t r a n s f e r . 12. To modify OP data f o r today., 83 13. Surgery i s r e q u i r e d l a t e r , so the s l a t e must be modified. 14. To a s u r g i c a l bed. 15. To a c a r d i a c u n i t bed. 84 IN-HOSPITAL TRANSFERS ROUTING (1) Fig. 6.6 In-hospital variations flowchart (VIA) 85 Operations Statements (VI A) 1. The process which f o l l o w s i s the r o u t i n g of i n - h o s p i t a l t r a n s f e r s . , 2. The admitting c l e r k attempts t o match the p a t i e n t to the a p p r o p r i a t e bed, which may be anywhere., I f t h e r e i s such a shortage of beds t h a t t h i s cannot be done y e t , i t w i l l be done l a t e r . I f matched, the p a t i e n t must be removed from h i s former l o c a t i o n to the new one. 3. To a Medical bed? (the bed might otherwise be s u r g i c a l or s p e c i a l ) [ 4 ] 4. A p a t i e n t at t h i s point may need a s p e c i a l o r s u r g i c a l care u n i t although not r e q u i r i n g any o p e r a t i o n , or may be r e t u r n i n g to a s u r g i c a l bed from a s p e c i a l u n i t . These cases would not imply a need f o r surgery. 5. Demands may come from s u r g i c a l o r c a r d i a c p a t i e n t s who have already had one o p e r a t i o n or who s u f f e r some "ward c a t a s t r o p h e " ( i n which case a bed t r a n s f e r may not be a d d i t i o n a l l y i m p l i e d ) , or from i n v e s t i g a t i v e , M e d i c a l , o r ICU p a t i e n t s found to r e q u i r e surgery. 6. For today or not ... see I I I A note 13., [23,24] 7. To a s p e c i a l u n i t bed or a s u r g i c a l area bed? [Not implemented] 8. " S p e c i a l u n i t s " (ICU and c a r d i a c unit) bed i n f o r m a t i o n i s updated by admissions to the c a r d i a c u n i t , and a c o n s i d e r a b l e amount of t r a n s f e r r i n g and d i s c h a r g i n g . , [Not implemented] 9. From Medical t r a n s f e r s IV A3 and s u r g i c a l t r a n s f e r s I I I A9, 86 10. From Medical bed i n f o r m a t i o n IV A3 and s u r g i c a l bed i n f o r m a t i o n I I I A9. 11. To a Medical bed. 12. From s u r g i c a l u n i t OR demands. 13. To today's OR data. 14. To modify the s l a t e . 15. From s l a t e - m o d i f y i n g s p e c i a l u n i t r e q u e s t s I I I A3, scheduled admissions to the c a r d i a c u n i t I I I A5, updating of s p e c i a l u n i t p a t i e n t s by today's OR run I I I A7, emergency admissions needing ICU monitoring and care V A2, and emergency c a r d i a c admissions V A8. , 16. To a s u r g i c a l bed. 17. From c a r d i a c bed i n f o r m a t i o n to the s u r g i c a l admissions match I I I A4, p a t i e n t s t o today's OR data I I I A6, and d i s c h a r g e s IV A4. 87 CHAPTER 7 THE DATA AND INFORMATION USE- The u n a v a i l a b i l i t y of data i s a prime c o n s t r a i n t i n the d e f i n i t i o n of the model and i n the determination of the depth of the study., In t h i s work, a v a r i e t y of data sources was u t i l i z e d : a magnetic data tape of p a t i e n t census data, c o p i e s of completed s u r g i c a l s l a t e s , emergency admissions forms. Medical and s u r g i c a l admission booking forms i n the course o f being processed, as well as the 1976 Admitting O f f i c e r e p o r t (see Appendix 2.1) and, t o some extent, a p a t i e n t t r a n s f e r study (Scroggs, 1970) . 7.1 D e s c r i p t i o n of Data-Sets The d e s c r i p t i o n o f the data gathered, and t h e i r s o u r c e s , w i l l serve to c l a r i f y the scope of t h i s study and to a s s i s t any f u t u r e data c o l l e c t i o n e f f o r t s . Defined a c c o r d i n g to t h e i r sources, the four d a t a - s e t s d e s c r i b e d below were the most important f o r t h i s work. 7.1.1 Waiting L i s t s As i t has been mentioned, s u r g i c a l admission booking forms are r e c e i v e d by the OR Booking O f f i c e and, u s u a l l y , stamped with the date of r e c e i p t . Once the p a t i e n t i s scheduled f o r surgery, another copy of the form i s sent t o the Admitting O f f i c e . 88 Medical forms and p r e - i n v e s t i g a t i v e surgery forms a l s o go to the Admitting O f f i c e , In order to gather data on w a i t i n g times f o r admission t o a feed, i t i s necessary t o observe the appearance (or at l e a s t presence) and disappearance of these forms. The h o s p i t a l keeps no records of waits! The best way to observe these data i s to r e c o r d and f o l l o w a l l forms on f i l e over a long p e r i o d of c o n s e c u t i v e days. U n f o r t u n a t e l y , i t i s not always convenient t o the h o s p i t a l s t a f f to have someone c o l l e c t i n g data from these forms d a i l y . (A s u g g e s t i o n i n t h a t regard may be found i n S e c t i o n 11.3.) Because o f t h i s d i f f i c u l t y , the data gathered here are sparse. One part s e r v e s to supplement other data (age, sex, a r r i v a l r a t e s ) , another part s e r v e s to v a l i d a t e w a iting times (output), and yet another p a r t i s the only source f o r c e r t a i n parameters (p r e - o p e r a t i v e LOS, d i a g n o s t i c c a t e g o r y ) . The data items a v a i l a b l e from observing the admission booking forms are l i s t e d and t h e i r use commented on, i n Table V I I I . 7.1.2 Operations One copy of the f i n a l s l a t e i s kept i n the OH Booking O f f i c e a f t e r use. To t h i s copy, the d u r a t i o n of scheduled o p e r a t i o n s , and the presence and d u r a t i o n of a l l emergency o p e r a t i o n s have been added. The s l a t e s from 1974 were used because p a t i e n t LOS data f o r 1974 were c o n v e n i e n t l y a v a i l a b l e . Since l e n g t h of surgery was the primary v a r i a b l e of i n t e r e s t , a s t r a t i f i e d random sample was c o l l e c t e d . The days of 89 TABLE V I I I DATA COLLECTION GROUPS Data Group Item Use WAITING Date form r e c e i v e d Date of admission C a n c e l l a t i o n s Postponements "No Beds" S e r v i c e P h y s i c i a n P r e - o p e r a t i v e LOS Age Sex D i a g n o s t i c category Date requested P o t e n t i a l week d i s t r Rate of sc Waiting t i P o t e n t i a l week d i s t r S e l f - e x p l a Schedulable p a t i e n t s per s e r v i c e P a t i e n t vo Booking pa S e r v i c e ' s tt ft P r o p o r t i o n P a t t e r n of P o t e n t i a l it Teaching bed? Accomodation T h i s group c o u l d a l s o be used t o show v a r i a s l a t e and placement of p a t i e n t s as per date d i a g n o s t i c category, t e a c h i n g bed, accomoda s e r v i c e . use i n day-of-the- i b u t i o n hedulable admissions me v a l i d a t i o n use i n day-of-the- i b u t i o n natory lume per p h y s i c i a n t t e r n d i s t r i b u t i o n II it ti f o r s e r v i c e use use f o r p r o p o r t i o n n n ti t i o n s made i n the r e g i e s t e d , t i o n , sex, and OPERATIONS Number per room L i m i t D i s t r i b u t i Length of S e r v i c e ' s ti Booker's time Age Sex Surgeon Room use p C a n c e l l a t i o n s P o t e n t i a l A note i s now made on the s l a t e s of a c t u a l not j u s t the booker's estimate plus t u r n a r o s t a r t i n g time of each procedure was a l s o no turnaround and surgery time c o u l d be c a l c u l the p h y s i c i a n ' s estimate was added, then a accuracy of h i s and the booker's estimates Instead of r e c o r d i n g a l l emergencies togeth u s e f u l t o note those which "broke" the s l a t 5.3.9). I t would be u s e f u l f o r the data-co f e a t u r e s , i f any, which cause some o p e r a t i o s e r v i c e to be done i n one OR and other oper i n another OR a l s o used f o r t h a t s e r v i c e . on, f o r v a l i d a t i o n surgery d i s t r i b u t i o n d i s t r i b u t i o n II a t t e r n use f o r p a t t e r n " s k i n - t o s k i n " time, und. I f the ted, a c t u a l ated. A l s o , i f study of the coul d be of value, e r , i t might be e (see s e c t i o n H e c t o r to note ns of a p a r t i c u l a r a t i o n s to be done 90 TABLE VI I I {cont.) LOS Admission date O v e r a l l admissions rate P o t e n t i a l use i n day-of-the- week d i s t r i b u t i o n P o t e n t i a l use i n t i m e - c y c l e study Discharge date Length of st a y P o t e n t i a l use i n study o f occupancy c o n t r o l v i a LOS S e r v i c e P a t i e n t s per s e r v i c e C l a s s i f i c a t i o n o f p a t i e n t s Age S e r v i c e ' s d i s t r i b u t i o n Sex " " Number of o p e r a t i o n s U s e f u l only i f decoded t o i d e n t i f y OR procedures Although not a v a i l a b l e on the tape used, CPHA could provide i n f o r m a t i o n on the use of s p e c i a l c a r e u n i t s and dis c h a r g e s t a t u s , as w e l l as diagnoses. EMERGENCIES Time of a r r i v a l A r r i v a l r a t e Time that Admitting P r o p o r t i o n placed i n morning was informed o f d a y - s h i f t Time t h a t p a t i e n t P o t e n t i a l use i n study o f was p l a c e d of delay S e r v i c e Emergency p a t i e n t s per s e r v i c e P h y s i c i a n P a t i e n t volume per p h y s i c i a n Bed r e c e i v e d Ward / s e r v i c e p a t t e r n To OR? P o t e n t i a l use f o r p r o p o r t i o n Age S e r v i c e ' s d i s t r i b u t i o n Sex " *' 91 the year were l i s t e d a c c o r d i n g to the number of procedures done on t h a t day. These s e t s of days were d i v i d e d i n t o roughly egual s i z e d groups ( s t r a t a ) a l i g n e d by the number of procedures. The d e s i r e d number of days to sample was determined, and from each stratum the same p r o p o r t i o n of days was chosen at random. ; T a b l e VIII l i s t s the data items and uses. 7.J.3 Length of Stay The l a r g e s t block of data was a magnetic tape of PAS case a b s t r a c t data f o r 1974 obtained from the Commission on P r o f e s s i o n a l and H o s p i t a l A c t i v i t i e s (CPHA). For each p a t i e n t discharged from the h o s p i t a l , the H e d i c a l Records L i b r a r y prepares a case a b s t r a c t of demographic, d i a g n o s t i c and treatment i n f o r m a t i o n , and submits i t to the CPHA. T h i s commission assembles the data on magnetic tape f i l e s , and a n a l y z e s i t . The tape which we obtained contained some 21,000 p a t i e n t records of data items which we had requested, with the r e s t o f the o r i g i n a l a b s t r a c t * s i n f o r m a t i o n d e l e t e d . T a b l e VIII d e t a i l s the i n f o r m a t i o n we e x t r a c t e d from those r e c o r d s . 7.1.4 Emergency Admissions The emergency u n i t maintains a d a i l y r e c o r d of admissions as well as a form on each p a t i e n t admitted. (These forms are l i a b l e to disappear i f the p h y s i c i a n wants them.) For t h i s study, r e c o r d s c o v e r i n g the peri o d of the 92 waiting-time data were used. A sample drawn from a l o n g e r time p e r i o d could a l s o have been used. The data usage i s d e s c r i b e d on Table V I I I . 7.2 The S p e c i f i c a t i o n of Data and Information Most of the data i n c o r p o r a t e d i n the model have been converted t o e m p i r i c a l f u n c t i o n s which d e s c r i b e the c h a r a c t e r i s t i c s f o r each of the v a r i o u s h o s p i t a l s e r v i c e s . However, some c h a r a c t e r i s t i c s are i d e n t i c a l over a l l s e r v i c e s , and could be r e p r e s e n t e d by s i m p l e r s i n g l e d e s c r i p t i o n s . Other i n f o r m a t i o n , obtained from St., Paul's, determined the s t r u c t u r e of the model i n such d e t a i l s as the seguence of events or the numbers of beds. A b r i e f d e s c r i p t i o n of the data i n c o r p o r a t e d i n the model f o l l o w s . In cases f o r which the d e r i v a t i o n of data used by the s i m u l a t i o n model from the raw c o l l e c t e d data i s r a t h e r i n v o l v e d , a f u l l e r e x p l a n a t i o n may be found i n Appendix 2., The f i n a l form of a l l f u n c t i o n s may be found i n the program l i s t i n g , i n Appendix 3., Table IX l i s t s the types of data and i n f o r m a t i o n used i n the model, and i n d i c a t e s those f o r which f u r t h e r d i s c u s s i o n may be found i n the appendix. Except f o r a couple of program book-keeping items, event p r i o r i t i e s were arranged to cause the f o l l o w i n g sejuence ( r e f e r a l s o to F i g u r e 8.1}. Each day, the reguests f o r admission were creat e d f i r s t . Emergency and DU r e g u e s t s were processed up t o , but not i n c l u d i n g admission. Orgeat, semi-urgent and e l e c t i v e 93 TABLE IX DATA AND INFORMATION OSED Item More In Number Type Appendix ? 1 Event sequencing 2 P r o p o r t i o n of morning d a y - s h i f t emergencies 3 P r o p o r t i o n of long-wait c a n c e l l a t i o n s 4 D a i l y p a t i e n t a r r i v a l s (non-schedulable Yes and schedulable) by s e r v i c e 5 P h y s i c i a n s per s e r v i c e / P h y s i c i a n s ' days f o r surgery 6 P a t i e n t admission d i a g n o s t i c category Yes 7 P a t i e n t sex Yes 8 P a t i e n t age group Yes 9 P a t i e n t length of st a y Yes 10 P a t i e n t p r e - o p e r a t i v e LOS 11 P a t i e n t l e n g t h of surgery Yes 12 P r o p o r t i o n r e q u e s t i n g an admission date 13 Time u n t i l reguested admission date 14 D a i l y bed l i m i t f o r s l a t e 15 D a i l y o p e r a t i n g time l i m i t f o r s l a t e (420 min. * no. o f OR's) 16 Scheduling p r i o r i t y f e a t u r e s 17 Turnaround time 18 Medical bed l i m i t f o r morning emergencies 19 Medical beds allowed f o r sc h e d u l a b l e p a t i e n t s 20 A l t e r n a t e areas 21 L i m i t on use of o f f - s e r v i c e beds 22 P a t i e n t s to stay i n o f f - s e r v i c e areas 23 P r o p o r t i o n of p a t i e n t s r e q u e s t i n g emergency surgery 24 P r o p o r t i o n of p a t i e n t s with i n - h o s p i t a l o p e r a t i o n reguests 9H requests were processed i n t h a t order as f a r as being scheduled and queued up. Discharges (which f r e e d beds f o r the day) were processed next. The f i r s t c l a i m on these beds were t r a n s f e r s . A number of emergency p a t i e n t s equal t o the p r o p o r t i o n which would appear during the morning of the d a y - s h i f t made the next c l a i m on beds. I f there was s t i l l room, scheduled p a t i e n t s were admitted next. (Emergency and other i n - h o s p i t a l o p e r a t i o n requests were generated from the p a t i e n t s admitted.) The remaining emergency p a t i e n t s ( a l l those not " i n the morning") were then placed wherever i t was p o s s i b l e . F i n a l l y , the c a l c u l a t i o n s r e g a r d i n g the day's o p e r a t i o n s were done. T h i s arrangement i s b e l i e v e d to c l o s e l y represent the bed-claim sequence at S t . Paul's. In p a r t i c u l a r , the p r o p o r t i o n of immediate p a t i e n t s to be handled i n the morning of the d a y - s h i f t was obtained by comparing the number of emergency p a t i e n t s being placed between 6 am and 11 am plus an a r b i t r a r y 50% of DO p a t i e n t s with the t o t a l number of immediate p a t i e n t s . The p r o p o r t i o n of p a t i e n t s c a n c e l l i n g each week, of those who waited over seven weeks, i s f a i r l y a r b i t r a r y , based on observed w a i t i n g times. The " P a t i e n t Generation Segment" of the model uses a l a r g e amount of data. Each o f s e v e r a l p a t i e n t i d e n t i f i c a t i o n items i s based on a d i f f e r e n t f u n c t i o n ( s e r i e s of proportions) f o r each s e r v i c e . For the a r r i v a l d i s t r i b u t i o n s , the observed p a t t e r n of d a i l y a r r i v a l s f o r each of emergency (with DU) and schedulable c a t e g o r i e s was smoothed and t a i l o r e d to a c c e p t a b l e r a t e s f o r 95 y e a r l y t o t a l s . These d i s t r i b u t i o n s were used to g i v e the d a i l j a r r i v a l r a t e f o r each type of p a t i e n t (see Appendix 2.3). The number of Bl,l§icians per s e r v i c e was taken on the b a s i s of an a r b i t r a r y "average a c t i v e " p h y s i c i a n . The number of p a t i e n t s f o r each p h y s i c i a n and t h e i r c h a r a c t e r i s t i c s were sampled from the same d i s t r i b u t i o n s , so t h a t , i n e f f e c t , a "composite" p h y s i c i a n was used. In Orthopedics, f o r example, the r e were nine a c t i v e s t a f f l i s t e d . Most were q u i t e busy during the time observed - so the model evened the p a t i e n t l o a d and kept nine p h y s i c i a n s . At the other extremity, i n Medicine, some 33 p h y s i c i a n s each admitted from 1 to 35 p a t i e n t s during the time observed. I t was decided that at a l e v e l of 22 p h y s i c i a n s , each could be c o n s i d e r e d to have a reasonable lo a d . The value of i n c l u d i n g these composite p h y s i c i a n s i s p a r t i a l l y i n i d e n t i f y i n g p h y s i c i a n ' s b l o c k s on the s l a t e , and p a r t i a l l y i n d e f i n i n g an "average p a t i e n t l o a d " to g i v e an i d e a of the e f f e c t of i n c r e a s e d or decreased s t a f f . The p r o p o r t i o n of p a t i e n t s i n each p_atient d i a g n o s t i c category was based on the observed number of emergency cases, known t o t a l s o f emergency and DU p a t i e n t s , known s l a t e d numbers of s c h e d u l a b l e p a t i e n t s , and known o v e r a l l t o t a l s . For d e t a i l s , see Appendix 2.2. The PAS data, together with observed data from s l a t e d and emergency cases was used to g i v e the p r o p o r t i o n of p a t i e n t s by sex, and, f o r each sex, the p r o p o r t i o n i n each §,a§ SEoup. (see Appendix 2.4). Length of stay, was o b t a i n e d by a more complex c a l c u l a t i o n . 96 From the PIS data, LOS was s u b d i v i d e d by sex, age group, and 3 s e a s o n a l l y - r e l e v a n t groups of months. I t was observed t h a t LOS was dependent on age, but not s i g n i f i c a n t l y on time-of-year. The average f o r each sex was s i g n i f i c a n t l y d i f f e r e n t , but a simple c a l c u l a t i o n ( i n c l u d e d i n Appendix 2.5) showed t h a t t h i s was almost e n t i r e l y accounted f o r by age-sex p a t t e r n s ( i . e . there were many more e l d e r l y females - which boosted the female average s t a y ) . Hence age groups were assigned by sex, then LOS by age group. Furthermore, t h e o r e t i c a l c o n s i d e r a t i o n s and the e x i s t i n g l i t e r a t u r e suggested t h a t the best parametric d i s t r i b u t i o n to rep r e s e n t LOS would be the log-normal. A rough t e s t of t h i s hypothesis was done by p l o t t i n g p o i n t s on l o g a r i t h m i c p r o b a b i l i t y paper. Although not g i v i n g an ac c e p t a b l y s t r a i g h t l i n e (to support the log-normal h y p o t h e s i s ) , these p l o t s were h e l p f u l . A c t u a l l y , f o r some s e r v i c e - a g e groups, the graph and even a c h i - s q u a r e t e s t supported the log-normal hypothesis. For most groups, however, the data d e v i a t e d s u f f i c i e n t l y from l o g - n o r m a l i t y that the parametric d i s t r i b u t i o n was avoided. E m p i r i c a l d i s t r i b u t i o n s were used f o r LOS, i n c l u d i n g a number of i n t e r m e d i a t e p o i n t s obtained from the graphs of the computer-tabulation of PAS data., (Appendix 2.5 c o n t a i n s a more complete d e s c r i p t i o n . ) P r e - o ^ e r a t i v e stay, was assigned a c c o r d i n g t o d i s t r i b u t i o n s based on the p h y s i c i a n s ' admission forms. The data c o l l e c t e d on l e n g t h of surgery was a l s o t a b u l a t e d by age group and sex. Although i n EENT, the average l e n g t h v a r i e d g r e a t l y by sex i n the f i r s t t h r e e of the age groups, the 97 h o s p i t a l c o u l d o f f e r ao e x p l a n a t i o n . V a r i a t i o n was r e l a t i v e l y s m a l l f o r Orthopedics. Hence, i n the s u r g i c a l s e r v i c e s modelled, age was taken to be the only dependent v a r i a b l e i n a s s i g n i n g l e n g t h of surgery. E m p i r i c a l data was smoothed a r b i t r a r i l y and used as input (see Appendix 2.6). The p r o p o r t i o n of p a t i e n t s r e q u e s t i n g a date f o r surgery (by d i a g n o s t i c category) was based e n t i r e l y on e m p i r i c a l data. When a date was requested, i n r e a l i t y i t was almost always on the day of the week f o r which the p h y s i c i a n was booked. For each request then, t h e r e was a c e r t a i n delay between the next date f o r which the a p p r o p r i a t e p h y s i c i a n was booked, and the date which was requested., The e m p i r i c a l data was processed and smoothed t o determine which p r o p o r t i o n of p a t i e n t s would request a date any given number of weeks from the next booked date. O n f o r t u n a t e l y , the date s e l e c t e d i n the model i s e n t i r e l y random, whereas the p h y s i c i a n would h o p e f u l l y have some idea of h i s next f r e e day, or of whether he wanted to "bump" one of h i s own p a t i e n t s (see a l s o Figure 8.2). The bed l i m i t per day and the time lim.it (based on the number of OR's used) were as i n d i c a t e d by the h o s p i t a l . Scheduling, p r i o r i t y was represented by the f o l l o w i n g d e c i s i o n mechanism: (i) p a t i e n t s f o r whom no s p e c i f i c date was requested could be scheduled no l e s s than e i g h t days away (correspondinq to the requirement that the p h y s i c i a n submit h i s forms at l e a s t e i g h t days i n advance), ( i i ) true urgent cases (no requested date or requested w i t h i n two weeks) c o u l d bump lower-category p a t i e n t s of the the same p h y s i c i a n , ( i i i ) bumped 98 p a t i e n t s were r e p l a c e d one week l a t e r ( i f p o s s i b l e ) , (iv) c a n c e l l e d p a t i e n t s were re-scheduled on an urgent b a s i s , (v) p a t i e n t s c o u l d only use OS's of t h e i r own s e r v i c e , (vi) non-urgent cases had to be handled on a c o r r e c t block day. F i g u r e s 8.3 and 8.4 i n c l u d e these c o n s i d e r a t i o n s . S i n c e only the t o t a l d a i l y time per OR was of i n t e r e s t , i n s t e a d of making the time between o p e r a t i o n s dependent on the l e n g t h s of adjacent o p e r a t i o n s , a c o n s t a n t turnaround time of f i f t e e n minutes seemed reasonable (see a l s o S e c t i o n 5.3.7). The placement of Medical p a t i e n t s presented a problem. In r e a l i t y , t e a c h i n g r e s i d e n t s c o n t r o l some o f the M e d i c a l beds, and t h e r e are many emergency Medical admissions beyond the c a p a c i t y of the Medical wards. S i n c e data are not a v a i l a b l e on the p r o p o r t i o n of each category of p a t i e n t using teaching beds, or on the d i f f e r e n c e i n LOS, or on the a c t u a l use made of t e a c h i n g beds, they cannot be d i s t i n g u i s h e d i n the model. In an e f f o r t t o keep i n mind the e f f e c t of the t e a c h i n g beds, and t o "tune" the model, morning emergencies were allowed up to a c e r t a i n number of Medical beds., When i t was time t o admit scheduled p a t i e n t s f o r the day, the l e n g t h of the queue and the number of a v a i l a b l e beds were noted. Depending on the number of a v a i l a b l e beds, the number of p a t i e n t s to admit was determined. Furthermore, i f the w a i t i n g l i n e was l o n g , e x t r a p a t i e n t s were admitted. I f i t was s h o r t , l e s s p a t i e n t s were admitted., T h i s was implemented by s p e c i f y i n g an upper and lower l i m i t on a c c e p t a b l e queue l e n g t h , then d e f i n i n g t h r e e f u n c t i o n s (one f o r l o n g , one f o r a c c e p t a b l e , and one f o r s h o r t queues) s p e c i f y i n g 99 the number of p a t i e n t s to admit at each l e v e l of "remaining c a p a c i t y " . The l i m i t s and numbers are a r b i t r a r y . When emergency p a t i e n t s cannot be admitted to the proper area, they are p l a c e d i n an a l t e r n a t e - area* There i s an a r b i t r a r y l i m i t d e f i n i n g the number o f beds which may not be used by o f f - s e r v i c e p a t i e n t s . Data suggest which sequence of a l t e r n a t e areas s o u l d be checked f o r empty beds. S e r v i c e area "2" i s used i n t h i s model as an overflow area. (Overflow beds are necessary because Medical emergency p a t i e n t s a c t u a l l y use e x t r a beds i n many s e r v i c e areas, not j u s t those implemented i n the model.) For M e d i c a l p a t i e n t s i n s u r g i c a l beds, t r a n s f e r s are arranged to avoid e x c e s s i v e "No Bed" s i t u a t i o n s . O f f - s e r v i c e data and c o n s u l t a t i o n with the h o s p i t a l suggest the p r o p o r t i o n of other types of p a t i e n t s allowed to stay i n o f f - s e r v i c e beds. The number of beds per s e r v i c e r e f l e c t s the a c t u a l s i t u a t i o n . . However, the a l l o t m e n t f o r Medicine i n c l u d e s the ICU, and the A c t i v a t i o n beds are d i v i d e d approximately by use as 6 f o r Medicine, 5 f o r Orthopedics, and 5 f o r General Surgery. The t o t a l number of emergency r e q u e s t s on the OR was found from data. The OR Booking O f f i c e , and some data, suggested the number of i ^ h p s p i t a l demands on the OR per day ( i f these c o u l d not be placed w i t h i n a week, they were handled as emergencies). These were i n c l u d e d i n the model by having an a p p r o p r i a t e p r o p o r t i o n of the admitted p a t i e n t s request such s p e c i a l surqery. 100 7.3 Comments The adequacy of the data used i n the model should be d i s c u s s e d . Were the data too o l d ? Were the observed samples too s m a l l , or f a u l t y ? Were any important f e a t u r e s i n c l u d e d or omitted without adequate data s u b s t a n t i a t i o n ? Would other types of data have been h e l p f u l ? Let us c o n s i d e r the f o u r data c o l l e c t i o n groups i d e n t i f i e d . The w a i t i n g l i s t s were d i s a p p o i n t i n g i n that the sample was s m a l l , so S e c t i o n 11.1 i n c l u d e s some su g g e s t i o n s r e g a r d i n g sample c o l l e c t i o n . The Medical a d m i t t i n g forms moved e s p e c i a l l y slowly during the c o l l e c t i o n time - a t about one t h i r d of the normal r a t e ! Furthermore, the f a c t t h a t t e a c h i n g r e s i d e n t s decide whom to admit t o t h e i r area and when, y i e l d s data which deny any a n a l y t i c a l p a t t e r n based on such c r i t e r i a as p a t i e n t admission d i a g n o s t i c category, and FIFO. Data on o p e r a t i o n s were taken from a good sample. However, the OH s u p e r v i s o r y s t a f f suggests that d i f f i c u l t y of o p e r a t i o n s (and hence t h e i r length) has i n c r e a s e d somewhat s i n c e 197 4, so t h a t newer data might show s l i g h t changes., The LOS data were a l s o taken from a l a r g e sample. The removal of the p e d i a t r i c s p e c i a l t y from the h o s p i t a l has probably had a s l i g h t l y d i f f e r e n t e f f e c t than t h a t c a l c u l a t e d , but these data should be q u i t e a c c u r a t e . Emergency admissions gave good data (except that a sample s e l e c t e d from the e n t i r e year might be p r e f e r a b l e ) . . As mentioned before, i t might be p r e f e r a b l e to modify the model so that the l e n g t h of time to a requested admission date 1 0 1 i s not random. T h i s would r e q u i r e a c l o s e r o b s e r v a t i o n of i n d i v i d u a l p h y s i c i a n ' s p r a c t i c e . I t would a l s o be p r e f e r a b l e to have a l e s s r i g i d d a i l y bed l i m i t f o r scheduled s u r g i c a l p a t i e n t s . T h i s would r e g u i r e observance of the f i n a l s l a t e as i t emerges - with a knowledge of which p a t i e n t s are scheduled and which p a t i e n t s are i n - h o s p i t a l . The main u n a v a i l a b l e i n f o r m a t i o n which would be of value i s a study of t r a n s f e r s between s e r v i c e areas - with a knowledge of which were c o r r e c t i o n s of o f f - s e r v i c e placement. The t o t a l number of p a t i e n t s placed o f f - s e r v i c e f o r each s e r v i c e (not j u s t Medicine) would a l s o help. , 102 CHAPTER 8 THE MODEL IMPLEMENTATION- T h i s chapter e x p l a i n s the a c t u a l concepts i n v o l v e d i n the programmed model, and b r i e f l y summarizes i t s c o n t e n t s . The e n t i r e computer program i s l i s t e d i n Appendix 3. At present, t h r e e s e r v i c e s have been implemented i n the model: Medicine, EENT, and Orthopedics. 8.1 General Features There are probably t h r e e f e a t u r e s of the program which should be e x p l a i n e d f i r s t . These are: (i) the i d e a of a "composite" p h y s i c i a n , ( i i ) the implementation of the s u r g i c a l s l a t e s , and ( i i i ) the d a i l y sequence of events which the model observes. (i) In order to r e l a t e p a t i e n t l o a d to the number of a c t i v e p h y s i c i a n s , i t was considered d e s i r a b l e t h a t each s e r v i c e have a c e r t a i n number of p h y s i c i a n s , and t h a t each p a t i e n t have a p a r t i c u l a r p h y s i c i a n . In t h i s manner, i t would be e a s i e r to suggest the e f f e c t on p a t i e n t load of i n c r e a s i n g or decreasing the number of p h y s i c i a n s on s t a f f . However, p h y s i c i a n p r a c t i c e p a t t e r n s are by no means s i m i l a r . Some p h y s i c i a n s admit many p a t i e n t s , some very few. Some p h y s i c i a n s c o n s i d e r a l l t h e i r p a t i e n t s t o be semi-urgent, others a l l e l e c t i v e . Some p h y s i c i a n s request s p e c i f i c admission days f o r a l l of t h e i r p a t i e n t s , others f o r a few, others f o r none. Because of t h i s 10 3 variety, and because in increasing or decreasing the active s t a f f only a " t y p i c a l " physician can be considered e a s i l y , i t was f e l t that a Ilcomgosite^ physician should be used (already mentioned i n Section 7.2). Hence, except for random variations, a l l physicians in the model have i d e n t i c a l practice patterns. Furthermore, rather than having a specified patient load generated for each physician, the language i s better structured to generate patients, and then to assign a physician to each. As a res u l t , i f the s t a f f s i z e i s to be varied, i n addition to changing the number of physicians for the service i t w i l l be necessary to re-compute the proportion of schedulable and DO patients a t t r i b u t a b l e to the physicians i n guestion, and to re-construct the patient a r r i v a l rate and admission diagnostic category functions., I t may also be necessary to adjust certain l i m i t s on patient flow. Refer to Chapter 10 for examples. ( i i ) The main scheduling device in the OS Booking Office at the hospital i s a six-week v i s u a l s l a t e f i l e . The counterparts of this f i l e i n the program are matrices counting the scheduled number and t o t a l time of patients to be operated on each week, and corresponding chains on which complete patient data f o r each operation are f i l e d . , For each s u r g i c a l service there i s a matrix, the f i r s t row of which gives the "dates" of Monday through Friday of the present week. Each of the s i x pairs of rows after that corresponds to a p a r t i c u l a r week in the future. The f i r s t row of each pair stores the number of patients to be admitted and operated on for each day of the week. The second row of each pair accumulates the operating time (and turnaround 104 time) r e q u i r e d by these p a t i e n t s as w e l l as i n - p a t i e n t s . These are the two c r i t i c a l f a c t o r s determining whether another p a t i e n t may have surgery on a given day {refer a l s o t o S e c t i o n 9.1). The time c a l c u l a t i o n s work as f o l l o w s . Each o p e r a t i n q t h e a t r e i s s l a t e d from 8:00 am t o 3:30 pm with a h a l f hour f o r l u n c h , which giv e s 420 minutes to be used. Turnaround time of f i f t e e n minutes i s added between p a t i e n t s . However, i t i s assumed that one turnaround c o u l d proceed durinq the lunch break. Since only t o t a l o p e r a t i n q time per s e r v i c e per day i s of i n t e r e s t , the " o v e r - l u n c h " turnaround i s counted as f a l l i n q between the f i r s t p a i r of p a t i e n t s - and no time i s added f o r t h a t . For each of the s i x weeks mentioned above, i n a d d i t i o n to the matrix there i s a l s o a " c h a i n " f o r each s e r v i c e . D a t a - e n t i t i e s r e p r e s e n t i n g the p a t i e n t s to be operated on are f i l e d on the c h a i n . , To avoid s h i f t i n g data between rows and between c h a i n s , t h e r e i s a p o i n t e r which i n d i c a t e s which rows and chain are those of the " p r e s e n t " week. T h i s p o i n t e r changes weekly, c y c l i n g through the s e t s . { i i i ) The d a i l y se&uenee of events ( e f f e c t e d by p r i o r i t y l e v e l s ) was mentioned i n chapter 7, but i s worthy of r e p e t i t i o n here. F i g u r e 8.1 d e p i c t s the time stream. The f i r s t and l a s t t h i n g s done each day are "book-keeping" events. Of the p a t i e n t - r e l a t e d events, the g e n e r a t i o n of p a t i e n t admission requests f o r a l l c a t e g o r i e s of p a t i e n t s i s done f i r s t . P r i o r i t i e s are set i n such a way t h a t , of the s c h e d u l a b l e p a t i e n t s , urgent reguests are processed f i r s t , then semi-urgent 105 W A I T I N G QUEUE S L A T E S T R A N S F E R QUEUE T R A N S F E R QUEUE W A I T I N G QUEUE S L A T E S B O O K - K E E P I N G I T E M S GENERATE A D M I S S I O N REQUESTS P R O C E S S E M E R G E N C I E S & D U ' S U N T I L A D M I S S I O N P R O C E S S U / S U / E L ONTO W A I T I N G L I N E AND S L A T E S D I S C H A R G E S ADMIT S C H E D U L A B L E P A T I E N T S FROM W A I T I N G L I N E MEANWHILE G E N E R A T E EMERGENCY & I N - H O S P I T A L OR DEMANDS T R A N S F E R QUEUE - « * (SOME) R E M A I N I N G E M E R G E N C I E S & D U ' S A D M I T T E D S L A T E S OR C A L C U L A T I O N S B O O K - K E E P I N G ITEMS BEDS A V A I L A B L E T R A N S F E R S . ( S O M E ) " M O R N I N G " E M E R G E N C I E S & D U ' S A D M I T T E D - * - CLAIM B E D S -f» CLAIM B E D S . CLAIM B E D S -is- CLAIM BEDS F i g . 8.1 Flowchart f o r d a i l y time stream 106 ones, then the e l e c t i v e s . A l s o , each request i s completely processed before beginning the next. Then, of the events which a f f e c t bed occupancy, dis c h a r g e s are f i r s t . T r a n s f e r s w i t h i n the h o s p i t a l f o l l o w . An a p p r o p r i a t e p r o p o r t i o n of emergencies to be placed during the morning of the d a y - s h i f t come next. Scheduled admissions then make t h e i r c l a i m on beds, followed by the r e s t of the emergencies f o r the day. To c l o s e o f f , the day's OR data i s computed. T h i s seguence i s intended to r e s u l t i n a r e a l i s t i c s i m u l a t i o n of wa i t i n g time, "No Bed" c a n c e l l a t i o n s f o r scheduled p a t i e n t s , and o f f - s e r v i c e placement of emergency p a t i e n t s . , 8.2 The Program Segments The program l i s t i n g begins with an e x t e n s i v e t a b l e of d e f i n i t i o n s f o r r e f e r e n c e , f o l l o w e d by d i f f e r e n t c a t e g o r i e s of GPSS d e f i n i t i o n s . The remainder of the l i s t i n g i s d i v i d e d i n t o s e c t i o n s by comment l i n e s . These s e c t i o n s are b r i e f l y e x p l a i n e d below. 8.2.1 Housekeeping Segments The f i r s t segment i n the program updates the s l a t e f i l e each "Saturday" (the s i x t h day o f each seven). The p o i n t e r mentioned i n S e c t i o n 8.1 i s moved t o a new "present week". Data on the week j u s t completed i s erased. P a t i e n t s whose forms had not been placed on the six-week " v i s u a l f i l e " (due t o a s p e c i f i c 107 request or l a c k of space) had been f i l e d i n a separate pl a c e . As many of these as i s a p p r o p r i a t e are now moved onto the new " f i f t h week" l o c a t i o n . , Weekly date chanqes are made. The l a s t two program segments are a l s o f o r "housekeeping". The f i r s t of these i s t o c o n t r o l p r i n t - o u t s as d e s i r e d . The f i n a l program segment i s a ti m e r . I t keeps tr a c k of how many days the program has run, and helps with some data g a t h e r i n g . 8.2.2 P a t i e n t Generation A t r a n s a c t i o n i s r e l e a s e d d a i l y and marked with the date. (Each e n t i t y which moves through the model i s c a l l e d a t r a n s a c t i o n . As i n t h i s case, use of the term i n t h i s t h e s i s i s normally to i d e n t i f y an i n t e r n a l program e n t i t y , as opposed to a t r a n s a c t i o n which r e p r e s e n t s a p a t i e n t - which w i l l u s u a l l y be c a l l e d a p a t i e n t . ) Then f o r each s e r v i c e , the t r a n s a c t i o n " s p l i t s " t o generate f i r s t the non-schedulable then the sch e d u l a b l e p a t i e n t admission reguests i n accordance with the ap p r o p r i a t e a r r i v a l d i s t r i b u t i o n s f o r th a t s e r v i c e . T h i s generating t r a n s a c t i o n leaves the model, and the reguests are sent to be assigned p a t i e n t c h a r a c t e r i s t i c s . , To each p a t i e n t , the model a s s i g n s a p h y s i c i a n , an admission d i a g n o s t i c c ategory, a sex, an age group, and a LOS. Emergency reguests are then d i v e r t e d , as are the remaining Medical and s u r g i c a l requests. 108 8.2.3 S u r g i c a l Request Handling For s u r g i c a l r e q u e s t s , p r e - o p e r a t i v e LOS (makinq sure t o t a l LOS i s longer) and length of surgery must be assigned. Then the p a t i e n t requests are separated a c c o r d i n q to the bookinq method observed by t h e i r s e r v i c e (e.g. block booking, see S e c t i o n 5.3.4). (Only block booking i s implemented i n the model at the time of w r i t i n g . ) As shown i n F i g u r e 8.2, the f i r s t item t o be determined i s a date on which to attempt to schedule surgery. T h i s date may e i t h e r be "as soon as p o s s i b l e " or may be requested f o r some time i n the f u t u r e . I t i s necessary to decide which p a t i e n t s are t o have a requested date of surqery. , For these, t h a t date i s determined i n accordance with e m p i r i c a l data {Section 7.2). For the o t h s r s , the e a r l i e s t p o s s i b l e date of surgery which i s blocked f o r the proper surgeon i s determined. I t must be over seven days away s i n c e the p h y s i c i a n i s r e q u i r e d to submit h i s r e q u e s t s at l e a s t e i g h t days i n advance. Having a d e s i r e d date f o r s urgery, one may attempt t o schedule the p a t i e n t , as i n F i g u r e 8.3. I f the date i s over s i x weeks away, the request i s placed on a c h a i n c o r r e s p o n d i n q to the f i l e box - separate from the main six-week f i l e . Another copy of the request i s added to an admission chain to wait f o r the a p p r o p r i a t e day. I f the date i s w i t h i n s i x weeks, the o p e r a t i o n s already scheduled f o r that date are checked. Here t h i s one added, would the bed or time l i m i t s be exceeded? I f there i s room, the 109 NO YES FIND NE PHYSICIAN XT DAY IS BOOKED 1 ADD 1 WEEK f FIND NEXT DAY PHYSICIAN IS BOOKED DETERMINE DESIRED DELAY ADD, FOR DATE TO TRY 1 NO ADD 1 WEEK " " V* • TRY THAT DATE YES F i g . 8.2 Flowchart f o r f i r s t d e s i r e d surgery date F i g . 8.3 Flowchart f o r p l a c i n g schedulable s u r g i c a l p a t i e n t s on the s l a t e 111 p a t i e n t i s added t h e r e . I f t h e r e i s no room, a l a t e r date must fee found as f o l l o w s . , For a non-urgent request, there w i l l be an attempt t o schedule i t one week l a t e r . I t i s considered that an urgent request f o r a date beyond two weeks away i s one which i s not r e a l l y t o p - p r i o r i t y , but i s more important than non-urgent requests of the same p h y s i c i a n . Hence, the model w i l l t r y to bump an e l e c t i v e f i r s t , or a semi-urgent, from the d e s i r e d day. I f there i s none which would allow the new p a t i e n t room and time, a week i s added before t r y i n g again. Note t h a t urgent p a t i e n t s are supposed to be admitted w i t h i n two weeks., As a r e s u l t , i f a request i s being handled i n t h i s p a r t of the model i t i s because the p h y s i c i a n submitted i t with a long-term "urgent" reguested date. , The model only allows him to bump h i s own p a t i e n t s . , An urgent request which did not come asking s p e c i f i c a l l y f o r admission two or more weeks away i s c o n s i d e r e d t o d e s i r e admission as soon as p o s s i b l e . I f i t cannot be f i t i n t o the proper p h y s i c i a n ' s s l o t , the e a r l i e s t p o s s i b l e date i s found, r e g a r d l e s s of p h y s i c i a n . , The p a t i e n t i s added t o the f i r s t day with enough space and time. I f there are none w i t h i n two weeks, t h i s request bumps another, as above. P a t i e n t s who were bumped must be removed from the s l a t e s and taken out of the admission f i l e . A week i s added to the date o r i g i n a l l y obtained before t r y i n g again. Once a day i s obtained f o r any of these r e q u e s t s , the s u c c e s s f u l surgery date, and hence, admission date i s marked. 112 The request i s added to the s l a t e and to the admission f i l e . 8.2.4 Medical Heguest Handlinq A Medical request i s simply added to the queue of those a w a i t i n g admission. 8.2.5 S u r g i c a l Admissions Once a day, the s u r g i c a l admissions f o r that date are r e l e a s e d from the w a i t i n g queue. Admission proceeds as shown i n F i g u r e 8.4. Some who should be admitted f i n d no room a v a i l a b l e . These are "No Bed" p a t i e n t s . T h e i r category l e v e l i s r e s e t so t h a t they w i l l be t r e a t e d as h i g h - p r i o r i t y urgent r e g u e s t s . They are removed from the s l a t e to be t r i e d one week l a t e r . The category i s r e s t o r e d once a new date i s found. For the p a t i e n t s who are admitted, there i s another process. A c e r t a i n p r o p o r t i o n of the p a t i e n t s i n the h o s p i t a l w i l l have e x t r a o p e r a t i o n s - besides t h a t f o r which they were o r i g i n a l l y admitted. In order t o represent these demands on the OR, i t was decided to use the p a t i e n t s being admitted to i n i t i a t e demands f o r emergency and in - r h o s p i t a l o p e r a t i o n s . Emergencies are generated and set f o r the next day ( i f the p a t i e n t ' s LOS warrants using him). I n - h o s p i t a l r e q u e s t s are more complex, as they must be scheduled. For them, checking begins two days from the present time, or i f that day would be on a weekend, checking begins with the f o l l o w i n g Monday). 113 YES SCHEDULE FOR NEXT DAY NO ENTER BED I ARRANGE DISCHARGE TIME YES ADD TO SLATE YES TRY 2 DAYS HENCE DETERMINE PHYSICIAN THEN ADD 1 OPERATING DAY MAKE IT AN EMERGENCY OPERATION NO NO BED! TAKE OFF SLATE CLASSIFY AS IF URGENT 1 ADD 1 WEEK TO ATTEMPTED OPERATION DATE r GO TRY (AS FIG. 8.3] WHEN RE-SCHEDULED, RESTORE CATEGORY YES F i g . 8.4 Flowchart f o r a d m i t t i n g s u r g i c a l p a t i e n t s 114 Having decided the date, the p h y s i c i a n who operates then must be i d e n t i f i e d . , One may now check whether the date i s p o s s i b l e , or go on l o o k i n g u n t i l one i s . {Recall t h a t " p o s s i b l e " r e q u i r e s only enouqh time. The p a t i e n t already has a bed).. Once a date i s found, the model checks to be sure that the p a t i e n t w i l l s t i l l be i n the h o s p i t a l (or e l s e i g n o r e s t h i s r e q u e s t ) . I f the p a t i e n t w i l l be i n the h o s p i t a l , the o p e r a t i o n i s scheduled on the s l a t e . Note t h a t i f an i n - h o s p i t a l request cannot be scheduled w i t h i n two weeks, i t i s changed to emergency handling. Now, the remaining d e t a i l s f o r an e n t e r i n g p a t i e n t are taken care of. He i s put i n a bed and a p p r o p r i a t e s t a t i s t i c s are gathered. According t o h i s LOS, he i s scheduled f o r d i s c h a r g e . , 8.2.6 Medical Admissions Each day, when the time comes to admit Medical p a t i e n t s from the w a i t i n g l i n e , the number of beds a v a i l a b l e and the l e n g t h of the gueue are determined. Depending on the amount of space, a d e c i s i o n i s made concerning how many beds to allow these p a t i e n t s to take. Furthermore, i f the w a i t i n g l i n e i s l o n g , e x t r a p a t i e n t s are allowed i n ; i f i t i s s h o r t , l e s s are admitted. (The a l g o r i t h m i s d i s c u s s e d i n S e c t i o n 7.2.), The admitted p a t i e n t s are put i n beds and a p p r o p r i a t e s t a t i s t i c s are gathered. According t o t h e i r LOS, they are f i l e d f o r discharge. 115 8.2.7 Emergency Admissions F i g u r e 8.5 d e p i c t s emergency admissions. Note that both emergency and DO p a t i e n t s are handled i d e n t i c a l l y . , S ince the e n t i r e day i s t r e a t e d as one time u n i t , proper DO p r o c e s s i n g i s not p o s s i b l e . Morning d a y - s h i f t and other a r r i v a l s are d i f f e r e n t i a t e d (by p r o p o r t i o n s ) to a f f e c t sequencing. The morning ones are allowed t o c l a i m beds a f t e r d i s c h a r g e s and t r a n s f e r s , but before scheduled admissions. The r e s t wait u n t i l a f t e r r e g u l a r admissions. As with the other p a t i e n t s admitted, a p r o p o r t i o n of these a r r i v a l s cause emergency and i n - h o s p i t a l o p e r a t i o n r e g u e s t s . These emergencies, however, are c o n s i d e r e d to happen on the same day. I f a bed i s a v a i l a b l e i n the proper area (and the p a t i e n t would not exceed an a l l o w a b l e l i m i t ) the p a t i e n t i s put i n the bed and on the d i s c h a r g e f i l e . Otherwise, admission i s permitted t o an a l t e r n a t e area (except f o r r e s t r i c t i o n s t h e r e a l s o ) . Any Medical p a t i e n t s who must be placed i n s u r g i c a l beds are a l s o put on a s p e c i a l f i l e . (See S e c t i o n 8.2.8 r e g a r d i n g t h e i r t r a n s f e r s . ) Other p a t i e n t s placed i n s u r g i c a l beds are allowed to stay i f a s p e c i f i e d number of beds are s t i l l f r e e i n t h a t area. A p r o p o r t i o n of the p a t i e n t s placed i n the overflow area are allowed to s t a y there. The r e s t are f i l e d to cause t r a n s f e r s the next day. NO YES ARRANGE PRIORITY & BED LIMITS FOR AFTER SCHEDULED ADMISSIONS — \ r • ARRANGE PRIORITY & BED LIMITS FOR BEFORE SCHEDULED ADMISSIONS JUL GENERATE EMERGENCY & IN-HOSPITAL OPERATIONS SIMILARLY TO FIG, 8.4 MEDICAL ? YES DETERMINE NEXT ALTERNATE AREA ML. . YES > PLACE IN OWN AREA > SCHEDULE FOR DISCHARGE STAY IN EMERGENCY UNIT < ARRANGE TRANSFER NEXT MORNING F i g . 8.5 Flowchart f o r emergency admissions 117 8.2.8 I n - H o s p i t a l T r a n s f e r s These happen r i g h t a f t e r d i s c h a r g e s , a s s u r i n g t h a t t r a n s f e r r i n g p a t i e n t s get f i r s t c l a i m on r e l e a s e d beds "each morning". The s u r g i c a l areas are checked t o see whether there are enough beds f r e e t o allow admission of s l a t e d s u r g i c a l p a t i e n t s . I f not, enough Medical p a t i e n t s are t r a n s f e r r e d out of the areas t o avoid e x c e s s i v e "No Bed" c a n c e l l a t i o n s . For p a t i e n t s t o be t r a n s f e r r e d , i f there are beds i n the proper a r e a , they are taken from the o f f - s e r v i c e area and placed i n the proper s e r v i c e area. 8.2.9 Discharges T h i s i s the f i r s t change a f f e c t i n g census each day. A l l the p a t i e n t s scheduled to leave today are d i s c h a r g e d , and a p p r o p r i a t e records are kept. 8.2.10 Operating Room Data Note t h a t , as f a r as o p e r a t i o n s go, the l e n g t h of time scheduled i s the a c t u a l l e n g t h of time operated. (Any problem due t o v i o l a t i o n of t h i s assumption warrants and can be covered by an independent, s p e c i f i c study.) Turnaround time i s i n c l u d e d as e x p l a i n e d i n S e c t i o n 7.2, A l l of the day's emergency and r e g u l a r l y scheduled p a t i e n t s to be operated on are r e l e a s e d f o r p r o c e s s i n g . For emergency 118 o p e r a t i o n s and f o r each t o t a l times and p a t i e n t s s e r v i c e ' s scheduled o p e r a t i o n s , the are accumulated and t a b u l a t e d each day. 119 CHAPTER 9 IIALJJftTION OF THE SIMULATION MODEL T h i s chapter d i s c u s s e s the "behaviour" of the St. Paul's s i m u l a t i o n model. The form of the r e s u l t s given by the s i m u l a t i o n program i s e x p l a i n e d . T h i s i s f o l l o w e d by an e x p l a n a t i o n of the v e r i f i c a t i o n and v a l i d a t i o n of the model: V e r i f i c a t i o n i s a check that the model behaves i n t e r n a l l y as the modeller i n t e n d s . V a l i d a t i o n i s the process which t e s t s t h a t the model provi d e s a reasonable r e p r e s e n t a t i o n of r e a l i t y . .{Fishman and K i v i a t , 1967) 9.1 Form of the R e s u l t s A s i m u l a t i o n run i n GPSS a u t o m a t i c a l l y generates a "standard" s et of s t a t i s t i c a l r e s u l t s d e s c r i b i n g the behaviour of the model. I f the programmer uses any matrices i n the program, or s p e c i f i e s the format of any freguency t a b l e s (of wai t i n g times, f o r i n s t a n c e ) , they w i l l be i n c l u d e d i n the print-out.„ The language a l s o allows the monitoring o f each " t r a n s a c t i o n " (normally a p a t i e n t ) on any s p e c i f i e d f i l e or a t any s p e c i f i e d l o c a t i o n i n the model. As the output from such monitoring may be voluminous, i t tends to be u s e f u l only f o r debugging or v e r i f i c a t i o n purposes. In a d d i t i o n , i t i s p o s s i b l e to arrange f o r GPSS to p r i n t out any subset of the t o t a l a v a i l a b l e i n f o r m a t i o n . The f o l l o w i n g d i s c u s s i o n i n c l u d e s a l l r e s u l t s which are provided by GPSS without needing to be 1 2 0 s p e c i f i e d . F i r s t i t should be noted t h a t s e v e r a l of the items are cumulative averages over time (cumulative sums d i v i d e d by the t o t a l t i m e ) . I f a run i s l o n g , the e f f e c t of the most recent time i n t e r v a l i s weighted l e s s and l e s s due to the e f f e c t of preceding ones. To avo i d t h i s , a "RESET" between "START" blocks allows i n f o r m a t i o n on i n d i v i d u a l time i n t e r v a l s t o be generated and d i s p l a y e d . A l l averages p r i n t e d with the " t a b l e s " such as those of w a i t i n g times or LOS r e p r e s e n t p a t i e n t s who have completed the p a r t i c u l a r process being monitored. The averages l i s t e d elsewhere may be s l i g h t l y b i a s e d due to the f a c t t h a t they count a l l p a t i e n t - d a y s spent i n the process s i n c e the s t a r t of the c u r r e n t time i n t e r v a l , and d i v i d e by the elapsed time s i n c e then. I n a c c u r a c i e s r e s u l t i f p a t i e n t s are being processed a t the s t a r t of the time i n t e r v a l and i f any are being processed at the time of p r i n t - o u t . , S c h r i b n e r ' s t e x t S i m u l a t i o n J s i n s GPSS (1974) and the GPSS manual p o i n t out these b i a s e s more completely. The f i r s t items p r i n t e d i n the standard output are "block counts". Each f u n c t i o n a l statement (as opposed t o "comment" statement) i n GPSS i s a " b l o c k " . For each " b l o c k " - which i s numbered on assembly - there i s a count of the c u r r e n t and t o t a l number of times i t was used., Since these counts are u s e f u l only f o r c a r e f u l l y f o l l o w i n g the flow through the model, no examples are i n c l u d e d i n t h i s d e s c r i p t i o n . , Any time a " t r a n s a c t i o n " (patient) must be f i l e d f o r a 121 p e r i o d of time before being used again, i t i s most e f f i c i e n t to p l a c e the t r a n s a c t i o n on a "user c h a i n " . In the p r i n t - o u t , "user c h a i n " i n f o r m a t i o n (see Table X), f o l l o w s the "block" counts. SLEW1-6 are f o r the s i x one-week c h a i n s o f EENT p a t i e n t s s l a t e d f o r o p e r a t i o n s . The " c u r r e n t c o n t e n t s " columns f o r the v a r i o u s weeks i d e n t i f y how many p a t i e n t s are w a i t i n g f o r ope r a t i o n s and when they are scheduled. (The number f o r the present week, probably the l a r g e s t , may not be the f i r s t , due to c y c l i n g as e x p l a i n e d i n S e c t i o n 8.1.) SLEEN g i v e s s i m i l a r i n f o r m a t i o n on EENT p a t i e n t s t o be scheduled beyond s i x weeks away. SL0W1-6 and SLOEN gi v e the same i n f o r m a t i o n f o r Orthopedic p a t i e n t s . , ADMSC i d e n t i f i e s the c u r r e n t , maximum, average and t o t a l number w a i t i n g f o r admission f o r surgery, as w e l l as the average time waited. T h i s i n f o r m a t i o n i s u s e f u l f o r v a l i d a t i o n . A s i m i l a r and very c r i t i c a l s e t of values concerns ADMMC, which i s the c h a i n of Medical p a t i e n t s a w a i t i n g admission. EMSGC provides i n f o r m a t i o n (probably of l i t t l e use) on those i n l i n e f o r emergency surgery. MALTn i d e n t i f i e s the number of Medical p a t i e n t s i n s u r g i c a l bed areas, where n=3 f o r EENT and n=4 f o r Orthopedics. The average numbers may be u s e f u l f o r experiments. XFERC i d e n t i f i e s other p a t i e n t s o f f - s e r v i c e and i n l i n e t o be t r a n s f e r r e d back. DISCH (together with XFERC and MALT3-U) i d e n t i f i e s the t o t a l number of p a t i e n t s i n the h o s p i t a l , a l l of whom are on f i l e t o be di s c h a r g e d . The i n f o r m a t i o n on "s t o r a g e s " (bed pools, Table XI) i s g u i t e u s e f u l . I t g i v e s d e t a i l s on the u t i l i z a t i o n o f each bed area (1=Medicine, 2=overflow, 3=EENT, 4=0rthopedics). The TABLE X * * * * * * * * * * * ti * * * USER CHAINS * * * ** ** * ******************************** USER CHAIN TOTAL AVERAGE CURRENT AVERAGE MAXIMUM ENTR IE S TIME/TRANS CONTENTS CONTENTS CONTENTS SIEW1 40 4 .875 9 6. 964 29 SLEW2 35 10.085 6 12.607 29 SLEW3 30 12.000 2 12.857 28 SLEW* 2 9 15.137 ' 2 15.678 27 SLEWS 23 12. 739 23 10.464 23 SLEW6 I 1 6.454 11 2.535 1 1 SLEEM 6 11.833 2. 535 5 SLOWl 36 5.472 14 7.035 21 SLOW2 24 10.500 s 9. 000 18 SLOW3 20 13.349 9.53 5 18 S10W4- 21 11.047 I 8.285 18 SLOW 5 1 6 15.937 16 9. 107 16 SL0W6 V 5 7.599 15 4.071 1 5 SLOEN 5 5.599 .999 3 AOMSC 2 84 10.193 104 103.392 137 ADMMC 124 5.354 24 23.714 34 DISCH 909 8. 102 249 263.035 279 EMRGC 34 .500 .607 6 XFERC 16 1.000 .571 MALT 3 6 1 3.803 17 8.285 17 MALT 4 3a 8.578 5 11.642 21 **************************************** * * TABLE XI * S T O R A G E S * * » »»»*• * * * * * * * * * * *<**«»*** * * * * * *«** * * *»**» - A V E R A G E U T I L I Z A T I O N D U R I N G - S T O R A G E C A P A C I T Y A V E R A G E E N T R I E S A V E R A G E T O T A L A V A I L . U N A V A I L . C U R R E N T P E R C E N T C U R R E N T MAXIMUM C O N T E N T S T I M E / U N I T T I M E T IME T I M E S T A T U S A V A I L A B I L I T Y C O N T E N T S C O N T E N T S 1 165 1 6 4 . 3 2 1 5 2 6 8 . 7 4 7 . 9 9 5 1 0 0 . 0 1 6 5 1 6 5 2 100 9 . 0 0 0 3 5 7 . 2 0 0 . 0 9 0 1 0 0 » 0 10 16 3 35 3 2 . 2 5 0 2 1 0 4 . 3 0 0 . 9 2 1 1 0 0 . 0 3 5 3 5 4 75 71 . 7 5 0 2 1 2 9 . 4 7 6 . 9 5 6 1 0 0 . 0 6 7 7 5 TABLE X I I * * * Q U E U E S * * * O U E U E MAX I MUM A V E R A G E T O T A L Z E R O P E R C E N T A V E R A G E S A V E R A G E T A B L E C U R R E N T C O N T E N T S C O N T E N T S E N T R I ES E N T R I E S Z E R O S T I M E / T R A N S T I M E / TRANS NUMBER C O N T E N T S WMEDU I S l l . 0 7 1 65 . 0 4 . 7 6 9 4 . 7 6 9 7 12 WM EDS 8 4 . 107 22 . 0 5 . 2 2 7 5 . 2 2 7 8 3 WMEOE 15 9 . 1 7 8 50 . 0 5 . 1 3 9 5 . 1 3 9 9 14 WE ENU 3 1 . 3 2 1 4 . 0 9 . 2 50 9 . 2 5 0 10 1 WEENS 2 . 6 7 8 3 . 0 6 . 3 3 3 6 . 3 3 3 11 I WEENE 8 8 6 6 . 3 5 7 1 8 3 1 . 5 1 0 . 1 5 3 1 0 . 2 0 8 12 8 3 WORPU 1 . 392 I . 0 1 1 . 0 0 0 1 1 . 0 0 0 13 WORPS 12 8 . 9 6 4 23 . 0 1 0 . 9 1 3 1 0 . 9 1 3 14 7 UORPE 5 0 4 0 . 4 2 8 109 . 0 1 0 . 3 8 5 1 0 . 3 8 5 15 5 0 L O S M E 1 9 9 1 8 7 . 2 5 0 6 2 0 . 0 8 . 4 5 6 8 . 4 5 6 16 186 LOSMM 114 1 0 1 . 8 5 7 3 2 6 . 0 8 . 7 4 8 8 . 7 4 8 105 L O S M F 9 9 8 5 . 3 9 2 2 9 4 . 0 8 . 1 3 2 8 . 132 81 L O S E E 33 2 2 . 8 5 7 145 . 0 4 . 4 1 3 4 . 4 1 3 17 2 4 1 0 S E M 24 1 1 . 3 2 1 72 . 0 4 . 4 02 4 . 4 0 2 16 L O S E F 18 1 1 . 5 3 5 73 . 0 4 . 4 2 4 4 . 4 2 4 8 1 0 S O R 7B 6 7 . 2 1 4 192 . 0 9 . 8 0 2 9 . 8 0 2 18 6 7 LOSOM 38 3 2 . 5 7 1 97 . 0 9 . 4 0 2 9 . 4 0 2 33 L O S O F 43 3 4 . 6 4 2 95 . 0 1 0 . 2 1 0 1 0 . 2 1 0 34 MI N2 12 7 . 5 0 0 22 . 0 9 . 5 4 5 9 . 5 4 5 5 MIN3 18 9 . 9 6 4 68 . 0 4 . 1 0 2 4 . 1 0 2 1 1 MI N't 14 5 . 4 6 4 2 7 . 0 5 . 6 6 6 5 . 6 6 6 5 E IN2 3 . 392 4 . 0 2 . 7 5 0 2 . 7 5 0 E IN4 2 . 2 8 5 3 . 0 2 . 6 6 6 2 . 6 6 6 01 N2 7 1 . 1 0 7 9 . 0 3 . 4 4 4 3 . 4 4 4 5 01 Hi 1 . 107 3 . 0 1 . 0 0 0 1 . 0 0 0 • A V E R A G E T I M E / T R A N S = A V E R A G E T I M E / T R A N S E X C L U D I N G Z E R O E N T R I E S CO 1 2 4 "average u t i l i z a t i o n during t o t a l time" i s the most u s e f u l v a r i a b l e . "Average c o n t e n t s " may be i n t e r e s t i n g when compared with o f f - s e r v i c e usage. "Current c o n t e n t s " i s u s e f u l f o r day-to-day examination. The queue i n f o r m a t i o n (Table XII) i s s i m i l a r t o that f o r "user c h a i n s " . Those queues having an e n t r y under "Table Number" are more completely d e s c r i b e d i n a t a b l e . At a glance, the gueue output g i v e s i n f o r m a t i o n on waits f o r urgent, semi-urgent and e l e c t i v e p a t i e n t s of M e d i c a l , EENT and Orthopedic p a t i e n t s (BMEDU, WMEDS, HMEDE, WEENU, ... ,WOSPU, . . . ) . O v e r a l l LOS f o r each s e r v i c e may be found (LOSME, LOS EE, LOSOR), as w e l l as LOS by sex w i t h i n each s e r v i c e (LOSMM, LOSMF, . . . ) . The p i c t u r e by sex, i n g i v i n g the average numbers i n the h o s p i t a l , suggests bed d i s p o s i t i o n . A l s o , a q u a n t i f i c a t i o n of LOS d i f f e r e n c e by sex appears. F i n a l l y , f o r each s e r v i c e there are gueues of those o f f - s e r v i c e . (eg., MIN3 means Medicals i n area 3 - EENT beds). Of these the averages i n each area and o v e r a l l average o f f - s e r v i c e may be i n f o r m a t i v e . The format of a l l the " t a b l e s " i s i d e n t i c a l (see T a b l e XIII f o r examples). T h e i r mean and standard d e v i a t i o n f i g u r e s are unbiased. The freguency d i s t r i b u t i o n t a b l e s may be of use. To i d e n t i f y what each " t a b l e " shows, see the l i s t i n Table XIV. Information may be f o r v e r i f i c a t i o n , v a l i d a t i o n , or experimentation. TABLE XIII OUTPUT TABLES T A B L E O R P S N E N T R I E S IN T A B L E 20 U P P E R L I M I T 0 I 2 3 4 5 6 MEAN ARGUMENT . 3 . 7 9 9 O B S E R V E D F R E Q U E N C Y 0 1 3 1 10 4 1 R E M A I N I N G F R E Q U E N C I E S A R E A L L Z E R O PER CENT OF T O T A L . 0 0 4 . 9 9 1 4 . 9 9 4 . 99 5 0 . 0 0 1 9 . 9 9 4 . 99 S T A N D A R D D E V I A T I O N 1 . 2 3 8 C U M U L A T I V E P E R C E N T A G E . 0 4 . 9 1 9 . 9 2 4 . 9 7 4 . 9 9 4 . 9 1 0 0 . 0 C U M U L A T I V E R E M A I N D E R 1 0 0 . 0 9 5 . 0 8 0 . 0 7 5 . 0 2 5 . 0 5 . 0 . 0 SUM OF A R G U M E N T S 7 6 . 0 0 0 M U L T I P L E OF MEAN - . 0 0 0 . 2 6 3 . 5 2 6 . 7 8 9 1 . 0 5 2 1 . 3 1 5 1 . 5 7 8 D E V I A T I O N F R O M MEAN - 3 . 0 6 8 - 2 . 2 6 1 - 1 . 4 5 3 - . 6 4 6 . 161 . 9 6 9 1 . 7 7 6 T A 8 L E O R P S T E N T R I E S 1 T A B L E MEAN A R G U M E N T 2 0 2 8 9 . 5 0 0 UPPER O B S E R V E D PER C E N T L I M I T F R E Q U E N C Y OF T O T A L 0 0 . 0 0 60 0 . 0 0 1 2 0 3 1 4 . 9 9 180 2 9 . 9 9 2 4 0 1 4 . 9 9 3 0 0 2 9 . 9 9 360 6 2 9 . 99 4 2 0 6 2 9 . 9 9 S T A N D A R D D E V I A T I O N 1 1 5 . 0 0 0 SUM OF A R G U M E N T S 5 7 9 0 . 0 0 0 R E M A I N I N G F R E O U E N C I E S A R E A L L ZERO C U M U L A T I V E C U M U L A T I V E M U L T I P L E P E R C E N T A G E R E M A I N D E R OF MEAN .0 1 0 0 . 0 - .000 . 0 100.0 . 2 0 7 1 4 . 9 8 5 . 0 . 4 1 4 2 4 . 9 7 5 . 0 .621 2 9 . 9 7 0 . 0 . 8 2 9 3 9 . 9 6 0 . 0 1 . 0 3 6 6 9 . 9 3 0 . 0 1 . 2 4 3 100.0 . 0 1 . 4 5 0 O E V I A T I O N F R O M MEAN - 2 . 5 1 7 - 1 . 9 9 5 - 1 . 4 7 3 - . 9 5 2 - . 4 3 0 . 0 9 1 . 6 1 3 1 . 1 3 4 T A B L E W T U l E N T R I E S IN T A B L E 50 U P P E R L I M I T 0 2 4 6 M E A N ARGUMENT 6. 03 9 O B S E R V E D F R E Q U E N C Y 28 18 R E M A I N I N G F R E Q U E N C I E S A R E A L L Z E R O PER C E N T OF T O T A L .00 .00 7 . 9 9 55 .99 3 5 . 9 9 S T A N D A R D D E V I A T I O N 1 . 0 4 6 C U M U L A T I V E P E R C E N T A G E .0 .0 7 . 9 6 3 . 9 100.0 C U M U L A T I V E R E M A I N D E R 1 0 0 . 0 l oo.o 9 2 . 0 3 6 . 0 . 0 SUM OF A R G U M E N T S 302.000 M U L T I P L E OF MEAN - . 0 0 0 . 3 3 1 . 6 6 2 . 9 9 3 1 . 3 2 4 D E V I A T I O N FROM MEAN - 5 . 7 6 9 - 3 . 8 5 9 - 1 . 9 4 8 - . 0 3 8 1 . 8 / 2 T A B L E WTS1 E N T R I E S IN T A B L E 11 MEAN A R G U M E N T 5 . 9 0 9 U P P E R O B S E R V E D PER C E N T L I M I T F R E Q U E N C Y OF T O T A L 0 0 .00 2 0 .00 4 3 2 7 . 2 7 6 2 1 8 . 1 8 8 6 5 4 . 5 4 R E M A I N I N G F R E Q U E N C I E S A R E A L L Z E R O S T A N D A R D D E V I A T I O N 1 . 5 1 1 C U M U L A T I V E P E R C E N T A G E .0 .0 2 7 . 2 4 5 . 4 1 0 0 . 0 C U M U L A T I VE R E M A I N D E R 100.0 100.0 7 2 . 7 5 4 . 5 .0 SUM OF A R G U M E N T S 6 5 . 0 0 0 M U L T I P L E OF MEAN - . 0 0 0 . 3 3 8 . 6 7 6 1 . 0 1 5 1 . 3 5 3 D E V I A T I O N FROM MEAN - 3 . 9 0 8 - 2 . 5 8 5 - 1 . 2 6 2 . 0 6 0 1 . 3 8 3 T A B L E W T E l E N T R I E S IN T A B L E 46 MEAN A R G U M E N T 6.739 U P P E R L I M I T 0 2 4 6 8 10 R E M A I N I N G F R E U U E N C I E S A R E A L L Z E R O O B S E R V E D F R E Q U E N C Y 18 21 P E R C E N T OF T O T A L . 00 .00 6 . 5 2 3 9 . 13 4 5 . 6 5 8 . 6 9 S T A N D A R D D E V I A T I O N 1 . 3 7 1 C U M U L A T I V E P E R C E N T A G E . 0 . 0 6.5 45.6 9 1 . 3 1 0 0 . 0 C U M U L A T I V E R E M A I N D E R 1 0 0 . 0 1 0 0 . 0 9 3 . 4 5 4 . 3 8 . 6 . 0 SUM OF A R G U M E N T S 3 1 0 . 0 0 0 M U L T I P L E OF MEAN - . 0 0 0 . 2 9 6 . 5 9 3 . 8 9 0 1. 187 1.483 D E V I A T I O N FROM MEAN - 4 . 9 1 5 - 3 . 4 5 6 - 1 . 9 9 7 - . 5 3 9 . 9 1 9 2 . 378 126 TABLE XIV MODEL OUTPUT TABLES LIST Name Pu rjsose EENSN Number of EENT p a t i e n t s s l a t e d each weekday EENST T o t a l time f o r EENT p a t i e n t s s l a t e d each weekday OBPSN Number of Orthopedic p a t i e n t s s l a t e d each weekday ORPST T o t a l time f o r Orthopedic p a t i e n t s s l a t e d each weekday HTU1 Medical urgent p a t i e n t s * w a i t i n g time WTS1 Medical semi-urgent p a t i e n t s ' w a i t i n g time WTE1 Medical e l e c t i v e p a t i e n t s ' waiting time WTU3 EENT urgent p a t i e n t s ' waiting time ITS3 EENT semi-urgent p a t i e n t s * w a i t i n g time WTE3 EENT e l e c t i v e p a t i e n t s * w a i t i n g time WTU4 Orthopedic urgent p a t i e n t s ' w a i t i n g time BTS4 Orthopedic semi-urgent p a t i e n t s * w a i t i n g time ITE4 Orthopedic e l e c t i v e p a t i e n t s ' waiting time STA1 LOS f o r Medical p a t i e n t s STA3 LOS f o r EENT p a t i e n t s STA4 LOS f o r Orthopedic p a t i e n t s EMTBN Number of (combined) p a t i e n t s d a i l y f o r emergency surgery EMTBT T o t a l time f o r (combined) p a t i e n t s d a i l y f o r emergency surgery EMGDU T o t a l d a i l y number of emergency and DU a r r i v a l s NOBED T o t a l d a i l y c a n c e l l a t i o n s f o r "No Bed" 127 Following the t a b l e s , the "halfword s a r e v a l u e s " are p r i n t e d . Most of these are i n t e r n a l and not too h e l p f u l . However, the f o l l o w i n g three may be u s e f u l : CftNCL = Number who c a n c e l l e d from surgery due to a very long wait. EhDIS = Number of d i s c h a r g e s from the Medical area, s i n c e t h i s i s not i d e n t i c a l t o Medical p a t i e n t s ' d i s c h a r g e s . MEMBN = Number of Medical emergencies and DU's i n the morning. T h i s has an impact on the day-to-day queue. S e v e r a l very important "halfword m a t r i c e s " , as i n Table XV, f o l l o w these. There i s a matrix of p a t i e n t numbers f o r each s e r v i c e implemented. Rows 1-5 correspond t o the Emergent / DU / 0 / SO / E l d i a g n o s t i c c a t e g o r i e s . Row 6 i s the t o t a l of those. The columns are as f o l l o w s : 1. P a t i e n t s qenerated, 2. P a t i e n t s admitted, 3., P a t i e n t s r e q u e s t i n g a p a r t i c u l a r date, 4. P a t i e n t s g e t t i n g t h a t date, 5. P a t i e n t s placed o f f - s e r v i c e , 6. P a t i e n t s r e t u r n e d to the proper s e r v i c e area. Note that the number of p a t i e n t s g e t t i n g a reguested date should be lower i n the model than i n r e a l i t y , s i n c e i n the model the date i s e n t i r e l y random and i n r e a l i t y the p h y s i c i a n r e q u e s t i n g a date should know when he has f r e e time. Two more types of matrices are p r i n t e d , but have not been TABLE XV H A L F W O R O M A T R I C E S H A L F W O R O M A T R I X M E O N O R O W / C O L U H N I 1863 472 333 117 321 3106 1863 472 328 116 316 3095 0 0 0 0 0 0 557 145 0 0 0 702 H A L F W O R O M A T R I X EENNO- ROW/COLUMN 1 2 3 . 4 5 1 92 92 0 0 29 2 24 24 0 0 6 3 21 21 10 7 0 4 26 28 27 20 0 5 701 689 478 449 0 6 864 854 515 476 35 HALFWORO M A T R I X ORPNO ROW/COLUMN 1 2 3 4 5 1 333 3 3 3 0 0 46 2 1 1 5 115 0 0 12 3 9 9 8 6 0 4. 87 91 8 0 65 0 5 389 389 96 76 0 6 933 937 184 147 58 129 shown i n the f i g u r e s as t h e i r use i s p r i m a r i l y i n t e r n a l . The f i r s t o f these are the s l a t e matrices f o r the s u r g i c a l s e r v i c e s . They are e x p l a i n e d i n S e c t i o n 8.1. The l a s t item i s a matrix of a l l o w a b l e a l t e r n a t e areas. The rows correspond to the s e r v i c e of the p a t i e n t . The columns correspond to a l l o w a b l e a l t e r n a t i v e areas. That o f column 3 i s t r i e d f i r s t , then column 2, then column 1. In t h i s implementation area "2" i s f o r overflow. "0" means "stay i n the emergency u n i t o v e r n i g h t " . 9.2 V e r i f i c a t i o n S e v e r a l t e s t s were performed to ensure that the model behaved i n a c o n s i s t e n t manner and worked as intended. One concern i n any s i m u l a t i o n based on "random" elements i s the accuracy of the pseudo-random number generators used. GPSS provi d e s an a l g o r i t h m f o r e i g h t i d e n t i c a l b u i l t - i n generators. For c e r t a i n procedures, such as those i n which a p r o p o r t i o n of p a t i e n t s are routed one way i n the model and the r e s t another, the system uses generator 1. For o t h e r s , the c h o i c e of a generator i s at the programmer's d i s c r e t i o n . The generators have been a l i g n e d i n such a way that the sequence of p a t i e n t s generated, and t h e i r ' c h a r a c t e r i s t i c s , can be d u p l i c a t e d i n c o n s e c u t i v e experimental runs. The l e n g t h - o f - s u r g e r y f u n c t i o n s , however, have been assigned to generator 1. (This was done s i n c e generator 1 n e c e s s a r i l y determines the p r o p o r t i o n , and hence number and sequence, of p a t i e n t s demanding emerqency and i n - h o s p i t a l o p e r a t i o n s - which r e q u i r e l e n q t h s - o f - s u r g e r y . ) 130 A l s o , generator 1 c o n t r o l s the p a t t e r n of requested dates f o r o p e r a t i o n s . As a r e s u l t , almost any change i n the model w i l l a l t e r the c o n s t r u c t i o n of the s l a t e s . S e v e r a l t e s t s were performed to check t h a t the numbers generated " f i t " a u n i f o r m l y f l a t d i s t r i b u t i o n on the 0-1 i n t e r v a l . The p r o p o r t i o n of "morning d a y - s h i f t " emergencies was checked, as w e l l as the p r o p o r t i o n of p a t i e n t s t r a n s f e r r i n g and the p r o p o r t i o n s of p a t i e n t s i n the d i f f e r e n t d i a g n o s t i c c a t e g o r i e s . The p r o p o r t i o n o f s u r g i c a l p a t i e n t s r e q u e s t i n g a p a r t i c u l a r date was a l s o t e s t e d . Each was a c c e p t a b l y c l o s e t o the intended value - tending to get c l o s e r the l a r g e r the sample. (e.g. f o r 22,000 "immediate" Medical p a t i e n t s , the p r o p o r t i o n i n each d i a g n o s t i c category was accurate to w i t h i n 0. 2%.) The random number seeds were changed and long runs were done, to t e s t the r e p e a t a b i l i t y of the processes d e s p i t e d i f f e r e n t pseudo-random number streams. F i g u r e s 9.1 to 9.6 show the r e s u l t s f o r one f o u r - y e a r run ( a f t e r one year of i n i t i a l i z a t i o n ) with p r i n t - o u t s each three months. F i g u r e s 9.7 to 9.12 show a one-year run with p r i n t - o u t s each f o u r weeks. (These f i g u r e s , which are r e f e r r e d t o s e v e r a l times i n t h i s c h apter, may be found at the end of the chapter.) The one-year run i s a c t u a l l y a c l o s e r look a t the t h i r d of the f o u r years, during which the number of o f f - s e r v i c e Medical placements was near the average and t h e r e were no extreme f l u c t u a t i o n s i n output v a r i a b l e s . The g r a p h i c r e s u l t s show the t y p i c a l v a r i a n c e s i n model performance v a r i a b l e s . Other runs y i e l d e d 131 s i m i l a r r e s u l t s . A d i s c u s s i o n of the i n d i v i d u a l items appears i n S e c t i o n 9.3, but f o r the present purpose the r e s u l t s demonstrate that the model i s s t a b l e . The d i f f e r e n t random number generators were a l s o r e a l l o c a t e d (so t h a t , i n s t e a d of being a l i g n e d by s e r v i c e , the assignment of generators to f u n c t i o n s was s h u f f l e d ) to t e s t any chance of c o r r e l a t i o n i n the streams dependent on a p a r t i c u l a r generator. There was no n o t i c e a b l e d i f f e r e n c e i n the range of output v a r i a b l e s . To check both the generator and the f u n c t i o n s p e c i f i e d , a separate t e s t was done on the Medical a r r i v a l f u n c t i o n s . The mean r a t e s were w i t h i n 1% of those d e s i r e d , and the freguency d i s t r i b u t i o n s u i t a b l y matched t h a t s p e c i f i e d by the f u n c t i o n . For v e r i f i c a t i o n purposes the l e n g t h - o f - s u r g e r y d i s t r i b u t i o n was r e p l a c e d by a constant. T h i s demonstrated that time and bed l i m i t s were being p r o p e r l y observed d u r i n g the development of the s l a t e . As intended, the t o t a l amount of time s l a t e d each day was an i n t e g r a l m u l t i p l e of the constant value s p e c i f i e d per procedure (plus turnaround time). In another run, t h e d i s t r i b u t i o n s of a r r i v a l r a t e s and LOS were r e p l a c e d by constant v a l u e s near the o r i g i n a l mean values. These values showed up as intended on the LOS t a b l e s and " p a t i e n t s generated" columns of the " p a t i e n t numbers matrices". In a d d i t i o n , the w a i t i n g queues and numbers placed o f f - s e r v i c e s t a b i l i z e d c o n s i d e r a b l y . T h i s was expected, s i n c e the two main sources of v a r i a t i o n had been removed. LOS of p a t i e n t s i n the model depended f i r s t on sex, which 132 was used to determine the age group, which i n tu r n was used to determine the LOS. De s p i t e t h i s c o m p l i c a t i o n , the o v e r a l l d i s t r i b u t i o n matched the e m p i r i c a l data g u i t e w e l l , with one year averages w i t h i n 5% of o r i g i n a l s (as modified to remove P e d i a t r i c p a t i e n t s ) . For both s e t s of data ( e m p i r i c a l and simulated) the standard d e v i a t i o n s are of about the same magnitude as the means, so short-term averages f l u c t u a t e c o n s i d e r a b l y . The average l e n g t h of surgery generated by s i m u l a t i o n , seems to be about 4-7% low compared t o e m p i r i c a l data. However, the surgery d u r a t i o n i n the model i s a l s o based on age groups which are d i v i d e d a c c o r d i n g to sex. These groups are d e f i n e d from l a r g e samples. The l e n g t h - o f - s u r g e r y v a l i d a t i o n sample i s r e l a t i v e l y s m a l l . As a r e s u l t , d i f f e r e n c e s between o b s e r v a t i o n s and simulated r e s u l t s might w e l l be a t t r i b u t e d to the d i f f e r e n t p r o p o r t i o n s of p a t i e n t s i n the d i f f e r e n t age groups. .. T h i s i d e a i s supported by the f a c t t h at s i m u l a t i o n v a l u e s are w e l l w i t h i n the range of e m p i r i c a l averages of the groups. In a d d i t i o n , day-to-day examinations of the flow through the Medical area were c a r r i e d out f o r two four-rweek p e r i o d s . Depending on the number of beds l e f t from the n i g h t b e f o r e , the number of p a t i e n t s r e t u r n i n g from o f f - s e r v i c e beds, and the number of "morning" emergencies, the number of scheduled admissions c o u l d be v e r i f i e d . Then the remaining number of emergencies could be checked a g a i n s t the t o t a l number of o f f - s e r v i c e placements. The model performs as intended., 133 9.3 V a l i d a t i o n T h i s s e c t i o n d i s c u s s e s the reasons f o r c o n s i d e r i n g the model to be a p o t e n t i a l l y u s e f u l a d m i n i s t r a t i v e t o o l . The u l t i m a t e q u e s t i o n i s ; How w e l l does the model r e p r e s e n t r e a l i t y ? In t h i s s e c t i o n , remember that only the Medicine, EENT, and Orthopedic s e r v i c e s are p r e s e n t l y implemented i n the model. The data used to determine a r r i v a l r a t e s , LOS, and l e n g t h - o f - s u r g e r y a l l came from l a r g e or c a r e f u l l y s e l e c t e d samples. These data are from 1974, though, and s e v e r a l s i g n i f i c a n t changes have occ u r r e d s i n c e then. The advent of Day Care surgery has had an impact i n r e d u c i n g the number of scheduled i n - p a t i e n t s u r g i c a l cases and, by h a n d l i n g some of the s h o r t e r cases, has a l t e r e d both LOS and l e n g t h - o f - s u r g e r y p a t t e r n s . The removal of the P e d i a t r i c s e r v i c e and the improved handling of placement f o r f u r t h e r c a r e (outside of S t . Paul's) have a l s o changed the system somewhat. The l a t t e r improvement may be p a r t i c u l a r l y s i g n i f i c a n t i n i t s e f f e c t on LOS (see S e c t i o n 12.1). . New d a t a - s e t s f o r a l l three of these v a r i a b l e s would be d e s i r a b l e . Next, c o n s i d e r the u t i l i z a t i o n of the bed areas. In the Medical area, occupancy i s very high - c l o s e to 100%,, In the model i t averaged about 99.5%, dropping below 99% f o r o n l y one three-month average i n f o u r years during a period when disch a r g e s were extremely high.. The EENT and Orthopedic areas are u s u a l l y not f i l l e d with t h e i r own p a t i e n t s , but t y p i c a l week-day occupancy i s s t i l l near c a p a c i t y due to o f f - s e r v i c e 134 p a t i e n t s . In the model, the excess Medical p a t i e n t s served t h i s purpose, and occupancy averaged about 92% i n the EENT area and 95% i n the Orthopedic area. T h i s i s below c a p a c i t y p a r t i a l l y due to the e f f e c t o f weekends and p a r t i a l l y due t o the f a c t t h a t i n the a c t u a l h o s p i t a l , o f f - s e r v i c e p a t i e n t s come from s e v e r a l s e r v i c e s , not j u s t one. (In the s i m u l a t i o n , s u r g i c a l area u t i l i z a t i o n dropped s i g n i f i c a n t l y when o f f - s e r v i c e placement of Medical p a t i e n t s was low due to e x t r a d i s c h a r g e s or fewer emergency a r r i v a l s . ) The high number of Medical emergency p a t i e n t s , f a r beyond the Medical area c a p a c i t y , a l s o causes the Medical w a i t i n g l i s t to r e g u i r e c a r e f u l a t t e n t i o n . As the r e s u l t d e s c r i b e d i n S e c t i o n 10.1 demonstrates, i f the c o n t r o l of t h i s queue i s l e f t independent of gueue le n g t h and h o s p i t a l occupancy f a c t o r s , the queue length f l u c t u a t e s w i l d l y . Since no such extreme f l u c t u a t i o n s are apparent i n the h o s p i t a l , i t i s assumed that s e v e r a l f a c t o r s i n t e r a c t to c o n t r o l the waiting l i s t t h e r e . I f the l i n e i s g e t t i n g l o n g , the Admitting O f f i c e s t a f f w i l l probably make an e x t r a e f f o r t to admit more p a t i e n t s . I f i t i s s h o r t they can r e l a x a b i t . These v a r i a t i o n s may be e f f e c t e d by f o r c i n g more or l e s s of the Medical emergency admissions o f f - s e r v i c e . A c t u a l l y , about h a l f of the M e d i c a l admission booking forms s p e c i f i c a l l y request " t e a c h i n g beds". Since the t e a c h i n q r e s i d e n t s e x e r t most of the c o n t r o l over who f i l l s t h e i r beds and how long they s t a y , (see S e c t i o n 5.2.5), they may w e l l be the ones who respond to i n c r e a s e d or decreased pressure to admit. In a d d i t i o n , p h y s i c i a n s may n o t i c e the l e n g t h of the 135 queue and act a c c o r d i n g l y i n t h e i r a d v i c e to p o t e n t i a l e l e c t i v e admissions. One f u r t h e r explanatory note i s i n order. The l e n g t h of the queue was determined by counting the number of forms i n the f i l e box. In some cases a scheduled p a t i e n t may be admitted by d i r e c t communication between the a d m i t t i n g p h y s i c i a n and a r e s i d e n t without ever g e n e r a t i n g a form. A l s o , f o r p a r t i c u l a r l y urgent cases there i s a s l i g h t p o s s i b i l i t y t h a t the form might be "at the desk" u n t i l the p a t i e n t i s admitted (as long as a couple of days), and might not be observed by an o u t s i d e r l o o k i n g through the f i l e box. The e m p i r i c a l data appear as f o l l o w s . In a three-week c o l l e c t i o n p e r i o d the l e n g t h of the gueue averaged 28.7 with a small standard d e v i a t i o n of 1.4. , A l a t e r o b s e r v a t i o n r e v e a l e d 36 waiting. In each case, t h e r e was a l a r g e number of long-wait p a t i e n t s . Many of these are expected to have c a n c e l l e d and never to have been admitted. In f a c t , at the s t a r t of the three-week sample, t h e r e were seventeen p a t i e n t s who had waited over one week., A f t e r the t h r e e weeks, f i v e of these had c a n c e l l e d ... none had been admitted! Furthermore, the s l i g h t v a r i a t i o n i n the sample may be a t t r i b u t a b l e t o the f a c t t h a t only one t h i r d of the average volume of requests appeared during those t h r e e weeks. I t i s f e l t t h a t , of the h o s p i t a l queue observed t o range from 26-36, some p o r t i o n - say maybe 20% w i l l probably c a n c e l and are not, i n f a c t , " a c t i v e " gueue members. A four-week t e s t on the model y i e l d e d a 23.2 average and 1.5 standard d e v i a t i o n which i s h i g h l y a c c e p t a b l e . The 136 three-month averages over f o u r years themselves average 23.4, with 80% of the values l y i n g w i t h i n f o u r of t h i s number. T h i s se t of averages and the four-week averages f o r one year are graphed at the end of t h i s chapter. ( F i g u r e s 9.1 - 9.3 and 9.7 - 9 . 9 r e l a t e to the l e n g t h of t h e Medical gueue, which i s the v a r i a b l e shown i n F i g u r e s 9.4 and 9.10.) The waiting-time d i s t r i b u t i o n f o r Medical p a t i e n t s i s another matter. The data sample was very s m a l l , but the average was 5.2 days, and was almost i d e n t i c a l f o r a l l three schedulable p a t i e n t c a t e g o r i e s . Although the Admitting O f f i c e c l e r k s attempt to g i v e higher p r i o r i t y t o the urgent and semi-urgent c a t e g o r i e s , the sample showed no d i f f e r e n c e (over t h r e e - q u a r t e r s of those admitted were te a c h i n g p a t i e n t s ) . Thus, i n s t e a d of o r d e r i n g the e n t i r e w a i t i n g l i s t by category, the only use made of the category of a Medical p a t i e n t was to determine the sequence i n which to f i l e each-dayIs forms. , Furthermore, s i n c e no proqrammable a l q o r i t h m c o u l d be d i s t i n q u i s h e d i n the s e l e c t i o n of p a t i e n t s to be admitted, the model has a b a s i c a l l y FIFO queue f o r i t s Medical p a t i e n t s . Postponement (which i n c r e a s e s the v a r i a n c e of the w a i t i n q time d i s t r i b u t i o n ) was not implemented i n the model due t o a l a c k of a c c u r a t e data. Hence, a Medical p a t i e n t i n the model has an averaqe w a i t i n q time of about 6.3 days (probably reasonable) with s l i q h t v a r i a t i o n s . A c r o s s - s e c t i o n of waits at any i n s t a n t would show some p a t i e n t s with one day waits, some with two, some with three, and so on up to whatever the c u r r e n t maximum miqht be (no more than f o u r t e e n days i n the one-year r u n ) . The a c t u a l l i s t has a c r o s s - s e c t i o n 137 spreading from one day to as much, as f i v e months {in the case of one "urgent teaching p a t i e n t " n o t i c e d ) ! The modelling s i t u a t i o n seems even b e t t e r f o r the s u r g i c a l gueue. D e v i a t i o n s from r e a l i t y i n the s i m u l a t i o n , p a r t i c u l a r l y i n the p a t t e r n of p a t i e n t s s l a t e d any given number of weeks i n advance, may be a t t r i b u t a b l e to d i f f e r e n c e s i n the 1974 data and 1976 p r a c t i c e . In 1974, t h e r e was no Day Care su r g e r y , and i t seems t h a t up to f i v e scheduled procedures f o r Orthopedics and nine f o r EENT were allowed per day {in c o n t r a s t to f o u r and s i x now). The model observes the 1974 l i m i t s and p a t i e n t a r r i v a l r a t e s . Because of the s c h e d u l i n g mechanism e x p l a i n e d i n Chapters 7 and 8, the s u r g i c a l queue i s q u i t e s t a b l e . The three-month averaqes over f o u r years themselves averaqed 111.4, with t h r e e - q u a r t e r s of these values l e s s than 5.5 away. About two-thirds o f t h i s queue i s made up o f EENT p a t i e n t s . The one sampled value of 136 {96 EENT, 40 Orthopedics) i s w e l l w i t h i n the range of the s i m u l a t i o n ' s queue l e n g t h d e s p i t e i t s s t a b i l i t y . As suggested above, the s i m u l a t i o n ' s d i s t r i b u t i o n of the number of p a t i e n t s s l a t e d f o r a given number of weeks away does not q u i t e " f i t " the sample d i s t r i b u t i o n , but appears reasonable. Greater accuracy would r e q u i r e a thorough examination of s c h e d u l i n g r u l e s . As suggested by the time stream sequence of F i g u r e 8.1, the c r i t i c a l number of Medical p a t i e n t s t r a n s f e r r e d to the wrong area i s the product of s e v e r a l i n t e r a c t i n g v a r i a b l e s each of which may f l u c t u a t e {Medical d i s c h a r g e s . M e d i c a l area r e t u r n e e s . 138 morning and other emergencies, l e n g t h of the w a i t i n g l i n e ) . Only one data value, the year's t o t a l f o r 1976, i s c u r r e n t l y a v a i l a b l e (see Appendix 2.1). I t suggests t h a t a t the model's l e v e l of Medical admissions, a r a t e of 1460 placed o f f - s e r v i c e per year i s e x c e l l e n t . The s i m u l a t i o n suggests t h a t t h i s v a r i a b l e i s g u i t e s e n s i t i v e t o f l u c t u a t i o n s i n the v a r i a b l e s which determine i t s l e v e l . N e v e rtheless, i t s average over f o u r years i s 1455! The v a l u e s f o r four years and one year are graphed at the end of t h i s chapter (Figures 9.5 and 9.11). The number o f "No Beds" f o r EENT and Orthopedics i s d i f f i c u l t t o determine, s i n c e only the d a i l y t o t a l f o r a l l s e r v i c e s has been recorded. T h i s v a r i e d g r e a t l y i n 1974, with an average of 39 per month, but as high as twenty i n one day! The average i n 1976 was 31 per month. I t i s not c l e a r whether the improvement i s random or a r e s u l t of g r e a t e r care i n p a t i e n t placement and t r a n s f e r s . I f the p r o p o r t i o n of "No Beds" i s i d e n t i c a l to the p r o p o r t i o n of procedures, EENT and Orthopedics may expect 115 per year (at the 1976 r a t e ) . The model has an average over f o u r years of about 117! The c o n s t r a i n t s i n e f f e c t a r e : the l e v e l to which o f f - s e r v i c e p a t i e n t s may f i l l beds before causing t r a n s f e r s and the l e v e l to which morning emergencies of the proper area (and other areas) are allowed to take o f f - s e r v i c e beds before being placed elsewhere. Figures 9.6 and 9.12 show "No Bed" numbers. The f i n a l v a l i d a t i o n item used was the number of p a t i e n t s s l a t e d f o r surgery. For Orthopedics, t h i s averaged about 4 i n the model. 1974 data suggested 4.5. The d i s t r i b u t i o n f o r the 139 model was c o r r e s p o n d i n g l y low. For EENT the model gave 5.7 per day. Heal data gave 6.7, but on a s m a l l sample. These d i f f e r e n c e s may w e l l be a t t r i b u t a b l e t o block booking by "composite p h y s i c i a n " and not a l l o w i n g anyone e l s e to f i l l h i s day with any but urgent p a t i e n t s or i n - h o s p i t a l p a t i e n t s . P a r t i c u l a r l y i n the Orthopedic s e r v i c e , f o r which each of fou r days has two p h y s i c i a n s booked and the other has only one, t h i s may be a f a c t o r . As these comments on v a l i d a t i o n i n d i c a t e , the model behaves very s a t i s f a c t o r i l y , p a r t i c u l a r l y f o r s i m u l a t i o n over the long-term. Since a complete range of v a l i d a t i o n data i s not a v a i l a b l e , and the accuracy o f d i f f e r e n t v a r i a b l e s i s not well known, nor i s the s e n s i t i v i t y of the system t o t h e i r changes, I do not f e e l t h a t a q u a n t i f i c a t i o n of the p r e c i s i o n o f the model i n terms such as "a c c u r a t e to w i t h i n ..." would be meaningful. To summarize, the r e s u l t s obtained f o r a l l of the c r i t i c a l v a r i a b l e s , i n c u d i n g some which a r e the r e s u l t of s e v e r a l i n t e r a c t i n g f o r c e s , suggest t h a t the model s t r u c t u r e i s good. 140 Uoo-i 2 ui 1 0 8 H VO<«4 F i g . 9.1 f u n c t i o n T Z M e d i c a l o f time T I M E l y e c r s ) "immediate" p a t i e n t s (per 3 3 months) as a T I M E Ivje.^v-s1) F i g . 9.3 M e d i c a l a r e a d i s c h a r g e s (per 3 months) as a f u n c t i o n of time TIME ( a «.«.»•*) F i g . 9.4 Average M e d i c a l queue l e n g t h (over 3 months) as a f u n c t i o n o f time 1 4 2 T I M E ( y e.(x^s^ F i g . 9.5 M e d i c a l p a t i e n t s p l a c e d o f f - s e r v i c e (per 3 months) as a f u n c t i o n o f t i m e 8 0 n F i g . 9.6 S u r g i c a l "No Bed" c a n c e l l a t i o n s (per 3 months) as a f u n c t i o n o f time 143 36<H 3oo4 o F i g . 9.7 M e d i c a l "immediate" p a t i e n t s (per 4 weeks) as a f u n c t i o n o f time F i g . 9.8 M e d i c a l s c h e d u l a b l e p a t i e n t r e q u e s t s (per 4 weeks) as a f u n c t i o n o f time 144 F i g . 9.9 M e d i c a l a r e a d i s c h a r g e s (per 4 weeks) as a f u n c t i o n o f time 55-, F i g . 9.10 Average M e d i c a l queue l e n g t h (over 4 weeks) as a f u n c t i o n o f t i m e 145 o Ui co 16̂ 0 12 T T I M E U « k s ) F i g . 9.12 S u r g i c a l "No Bed" c a n c e l l a t i o n s (per 4 weeks) as a f u n c t i o n o f time 146 CHAPTEB 10 EXPERIMENTS S e v e r a l experiments were performed with the v a l i d a t e d and v e r i f i e d model. These p a r t i c u l a r experiments were s e l e c t e d i n order to demonstrate some of the changes i n the St. Paul's H o s p i t a l admissions and s c h e d u l i n g system which the model might be used t o i n v e s t i g a t e . In a d d i t i o n to these experiments, one r e s u l t which appeared d u r i n g the development of the model i s i n c l u d e d i n t h i s chapter because of i t s s i g n i f i c a n c e . The experiments were t e s t e d over the same one-year peri o d d i s c u s s e d e a r l i e r . Unless d e l i b e r a t e l y a l t e r e d , then, the sequence of p a t i e n t s and t h e i r l e n g t h s - o f - s t a y are i d e n t i c a l . However, i n the experiments f o r which the sequence of p a t i e n t s a r r i v i n g has been a l t e r e d ( S e c t i o n s 10.5 and 10.6), i t has been noted that the experimental r e s u l t s are w i t h i n the range of the random v a r i a t i o n s i n the o r i g i n a l run. In order t o draw any f i r m c o n c l u s i o n s , i t would be advantageous to run such experiments f o r at l e a s t two years and p r e f e r a b l y f o u r . 10.1 admission Str a t e g y In the course of " t u n i n g " the model, i t became c l e a r t h a t the f l u c t u a t i o n i n the l e n g t h of the Medical queue i s extremely s e n s i t i v e t o the admission s t r a t e g y employed. In the present model a f t e r " t u n i n g " , the number of p a t i e n t s t o admit i s determined from both the number of beds a v a i l a b l e and the length 147 of the Medical gueue. An e a r l i e r p r e l i m i n a r y v e r s i o n of the model admitted p a t i e n t s i n a more random f a s h i o n . On 50% of the days, admissions were allowed from the Medical gueue u n t i l there were t h r e e beds l e f t . On the other 50% of the days, they were allowed u n t i l four beds remained i n the Medical area. (These p r o p o r t i o n s and l i m i t s had been found to give the most r e a l i s t i c numbers of "No Beds" and o f f - s e r v i c e placements.) In an e i g h t - y e a r run, the Medical gueue was observed to f l u c t u a t e from 0 to 150, with s e v e r a l g u a r t e r - y e a r averages over 100! I t should be noted that t h e r e were three other d i f f e r e n c e s i n t h a t e a r l y model which would have c o n t r i b u t e d to the f l u c t u a t i o n , (i) Rather than 20% of the emergency a r r i v a l s being allowed to precede the scheduled a r r i v a l s and to enter u n t i l t here were e i g h t beds l e f t , 47.5% of the emergency a r r i v a l s were allowed to enter f i r s t , u n t i l t here were s i x beds l e f t . The f a c t t h a t the same t o t a l number of Medical p a t i e n t s entered suggests t h a t t h i s was not a c r i t i c a l f a c t o r . ( i i ) Rather than having separate a r r i v a l processes f o r immediate and schedul a b l e p a t i e n t s , the e a r l i e r model used a s i n g l e process. T h i s would have i n c r e a s e d the v a r i a n c e i n the number of Medical p a t i e n t s e n t e r i n g the gueue. A l a t e r t e s t i n d i c a t e d that the length of the the gueue was not p a r t i c u l a r l y s e n s i t i v e t o t h i s v a r i a n c e . ( i i i ) A p o r t i o n of the scheduled admissions o r i g i n a l l y postponed and returned to the gueue. T h i s should have a l t e r e d the waiting-time d i s t r i b u t i o n without s i g n i f i c a n t l y a f f e c t i n g the l e n g t h of the wa i t i n g gueue. In c o n c l u s i o n , t h e l e n g t h of the Medical gueue was a 148 c r i t i c a l v a r i a b l e observed while a d j u s t i n g the model. I n d i c a t i o n s a r e t h a t the number o f admissions from the gueue must be c a r e f u l l y c o n t r o l l e d r a t h e r than l e f t random, i f the l e n g t h i s not to be allowed t o f l u c t u a t e c o n s i d e r a b l y . 10.2 Bed A l l o c a t i o n In the one-year run of the f i n a l model, i t was observed t h a t t h e r e was an average of about seven Medical p a t i e n t s i n Orthopedic beds, e i g h t i n EENT beds, and t h i r t e e n i n "overflow" beds. As a r e s u l t , i t was decided to r e a l l o c a t e the number of beds per s e r v i c e area. The Orthopedic area was given f o u r l e s s beds, the EENT area f i v e l e s s , and the Medical area s i x t e e n more. S e v e r a l other a l t e r a t i o n s were necessary t o correspond to t h i s r e a l l o c a t i o n . The bed l i m i t s f o r "morning" emergency admissions were r e v i s e d . , The number of u n i t s of "remaining c a p a c i t y " which would permit the admission of c e r t a i n numbers of Medical s c h e d u l a b l e p a t i e n t s was r e d e f i n e d and the p a t t e r n was a l t e r e d s l i g h t l y . Furthermore, s i n c e t h e r e were l e s s beds i n the s u r g i c a l areas, r e s t r i c t i o n s were t i g h t e n e d on the number of o f f - s e r v i c e p a t i e n t s to be allowed without n e c e s s i t a t i n g a t r a n s f e r . The response of the system was as f o l l o w s . E i g h t weeks were allowed f o r the system t o r e s t a b i l i z e . The average length of the Medical queue decreased by three while the standard d e v i a t i o n i n c r e a s e d from 4.1 to 5.8 (see F i g u r e 10.1). The 149 number of "overflow" beds which was r e q u i r e d dropped by an average of 4.1.., The u t i l i z a t i o n of the s m a l l e r EENT area was even down s l i g h t l y . The number o f Medical p a t i e n t s who were t r a n s f e r r e d o f f - s e r v i c e dropped from 1261'{in 44 weeks) t o 707, but f l u c t u a t e d almost as g r e a t l y as be f o r e . The number of "No Beds" i n c r e a s e d from 106 to 161 over the same time p e r i o d (see Figure 10.2). The system became c o n s i d e r a b l y more s e n s i t i v e t o v a r i a t i o n s i n the random i n f l u e n c e s on i t . With l e s s s u r g i c a l beds, the "No Bed" v a r i a b l e showed much more s e n s i t i v i t y to changes i n the number of Medical p a t i e n t s o f f - s e r v i c e and i n the a r r i v a l r a t e s of s u r g i c a l p a t i e n t s . I t i s s i g n i f i c a n t t h a t although the net number of non-"overflow" beds was i n c r e a s e d by 7, the average number of "overflow" beds i n use dropped by only 4.1. (The number of Medical p a t i e n t s o f f - s e r v i c e dropped by more than f i f t e e n with the s i x t e e n e x t r a beds, but the s u r g i c a l p a t i e n t s had t o use a d d i t i o n a l overflow beds.) In view of the i n c r e a s e d t o t a l bed usage and the l a r g e i n c r e a s e i n "No Beds", t h i s a l t e r a t i o n does not appear to be a d v i s a b l e . 10.3 Combining Bed Areas An experiment was done to combine the EENT and Orthopedic bed areas. P a t i e n t s of both s e r v i c e s used a s i n g l e bed " p o o l " , which was given as many beds as the two areas t o g e t h e r had o r i g i n a l l y been a l l o c a t e d . , Any r e l e v a n t l i m i t s were changed t o 150 3 5 - i 5<M X (J? Lii 2 ? J UJ 15-1 ^  1—15—; 1 Fi T I M E (weeks ) F i g . 10.1 Average M e d i c a l queue l e n g t h (over 4 weeks) as a f u n c t i o n o f ti m e : O r i g i n a l x ; Experiment o 60- i T I M E (weeks) F i g . 10.2 S u r g i c a l "No Bed" c a n c e l l a t i o n s (per 4 weeks) as a f u n c t i o n o f time : O r i g i n a l x ; Experiment o 151 the sums of the p r e v i o u s l i m i t s . Of the one-year run, e i g h t weeks were allowed f o r the model to r e s t a b i l i z e , and the l a s t 44 weeks were compared. The r e s u l t s were i n t e r e s t i n g . The s u r g i c a l gueue le n g t h e x h i b i t e d a p a t t e r n s i m i l a r to the o r i g i n a l one. The u t i l i z a t i o n of the new bed "pool™ was about the same as the weighted average of the p r e v i o u s areas. However, the number of "No Beds" dropped s i g n i f i c a n t l y from 106 to 46 (see Fig u r e 10.3)! The number of Medical p a t i e n t s who were sent o f f - s e r v i c e dropped by 120, as a r e s u l t of the number of p a t i e n t s r e t u r n i n g to the Medical area dropping by 90. The only adverse r e a c t i o n was that an average of 4.1 more overflow beds were r e q u i r e d (see Figure 10.4). Further t e s t s which a l t e r e d o f f - s e r v i c e l i m i t s f a i l e d to reduce t h i s number. These r e s u l t s may be e x p l a i n e d as f o l l o w s . The s u r g i c a l areas together had more f l e x i b i l i t y i n bed use than e i t h e r had s e p a r a t e l y . I f a s u r g i c a l p a t i e n t needed a bed, he was more l i k e l y t o f i n d i t i n the combined area than he would have been i n h i s own area.„ As a r e s u l t , t h e r e were l e s s "No Bed" c a n c e l l a t i o n s , and l e s s M e d i c a l p a t i e n t s were allowed i n t o the combined area. T h i s f o r c e d more Medical p a t i e n t s to the "overflow" area. In a d d i t i o n , s u r g i c a l emergency p a t i e n t s who cou l d not f i n d a bed i n the combined area had to go to the "overflow" area. Of course, these r e s u l t s o f f e r o n l y the numerical aspects to be co n s i d e r e d r e g a r d i n g such an a l t e r a t i o n . The q u o t a t i o n from Goldman et a l (1968) which was i n c l u d e d i n Chapter 3 152 30-i F i g . 10.4 Average use of "overflow" beds (over 4 weeks) as a f u n c t i o n o f time : O r i g i n a l x ; Experiment o 153 e x p l a i n s why a b e d s - t o - s e r v i c e a l l o c a t i o n i s advantageous. I f the a d m i n i s t r a t i o n c o n s i d e r s the "No Bed" v a r i a b l e to be p a r t i c u l a r l y important, and i f e x t r a beds can be arranged elsewhere, then the a d m i n i s t r a t i o n should c o n s i d e r a removal of the d i s t i n c t i o n between beds of d i f f e r e n t s e r v i c e areas. 10.4 Reguests f o r S p e c i f i c Surgery Dates I t was observed from the data c o l l e c t e d t h a t a l a r g e number of the p h y s i c i a n s reguested p a r t i c u l a r dates on t h e i r s u r g i c a l admission forms. The g u e s t i o n a r i s e s : Hhat i f the p h y s i c i a n s l e f t more of the dates up to the booking c l e r k ? Of course, some of the reguests came from p a t i e n t s and were t r a n s m i t t e d by t h e i r p h y s i c i a n s . However, on some occ a s i o n s , the p h y s i c i a n could probably have l e t the booking c l e r k choose the date. An experiment was done to t e s t what would happen i f p h y s i c i a n s had only s p e c i f i e d h a l f as many dates as they a c t u a l l y asked f o r . The d i s t r i b u t i o n of these dates was not a l t e r e d . The l e n g t h of the s u r g i c a l gueue dropped s i g n i f i c a n t l y with a s i m i l a r drop i n s u r g i c a l w a i t i n g time. Eleven more Orthopedic p a t i e n t s and t h i r t y more EENT p a t i e n t s were admitted t h a t year. The numbers of o p e r a t i o n s which were performed each month f l u c t u a t e d , but the average was the same f o r Orthopedics and only one more per month f o r EENT. No other v a r i a b l e s changed s i g n i f i c a n t l y . F i g u r e s 10.5 - 10.7 show the comparative numbers of EENT procedures, numbers of Orthopedic procedures and s u r g i c a l gueue l e n g t h s . 154 110- bJ ZD OUO L J O O cc Q-110 100- F i g . 10.5 EENT f u n c t i o n o f time 100n T I M E ( w e ^ k s ) s u r g i c a l p r o c e d u r e s (per 4 weeks) : O r i g i n a l x ; Experiment o as a 60- 1T 2'H- 3'& T I M E ( w e e k s ) F i g . 10.6 O r t h o p e d i c s u r g i c a l p r o c e d u r e s (per 4 weeks) as a f u n c t i o n o f time : O r i g i n a l x ; Experiment o 155 F i g . 10.7 Average s u r g i c a l queue l e n g t h (over 4 weeks) as a f u n c t i o n o f time : O r i g i n a l x ; Experiment o 156 The r e a l gain seems t o be i n the w a i t i n g time of s u r g i c a l p a t i e n t s . As mentioned e a r l i e r , the p h y s i c i a n s probably do a b e t t e r job of s e l e c t i n g days than the model does, s i n c e the p h y s i c i a n s should be able t o t e l l when they are f r e e , while the model s e l e c t s days at random. As a r e s u l t , t h i s experiment may only i n d i c a t e a change that could be made to improve the model. Hovever, i t does p o i n t out the f a c t t h a t i f a p h y s i c i a n i s s e l e c t i n g h i s requested s u r g i c a l dates i n a haphazard f a s h i o n , or i f he i s choosing h i s dates f a r enough i n the f u t u r e that he expects them to be a v a i l a b l e , he would probably do b e t t e r to l e a v e i t up t o the booking c l e r k . ., 10.5 C l a s s i f i c a t i o n of P a t i e n t s I t has been suggested t h a t not every p a t i e n t who a r r i v e s at the St. Paul's Emergency Unit should be t h e r e . Some of the p a t i e n t s c o u l d p o s s i b l y be handled on a s c h e d u l a b l e b a s i s . With t h i s i n mind, the a r r i v a l p a t t e r n s of Medical p a t i e n t s were a l t e r e d so that 365 of the immediate p a t i e n t s were r e - c l a s s i f i e d as s c h e d u l a b l e (one per day). , No other model parameters were changed. The r e s u l t s were r a t h e r i n c o n c l u s i v e . The average l e n g t h of the Medical queue d i d r i s e by about 4.5, but the average waiting time dropped s l i g h t l y . , The t o t a l number of Medical p a t i e n t s placed o f f - s e r v i c e was the same, although the number i n each four-week time p e r i o d s t a b i l i z e d (see F i g u r e 10.8). T h i s s t a b i l i z a t i o n was r e f l e c t e d i n a somewhat lower v a r i a n c e f o r the 157 s u r g i c a l gueue. The number of "No Beds", however, i n c r e a s e d from 111 to 130 (see F i g u r e 10.9). The p r e v i o u s 4-year run had reached as many as 139 "No Beds" i n one year, so t h i s r e s u l t may be a random response to the other f l u c t u a t i o n s . However, s i n c e i t i s probably not, the r e s u l t i s d i s t u r b i n g . In any case, i t seems from the s t a n d p o i n t of h a n d l i n g the "No Bed" problem, t h a t the a d m i n i s t r a t i o n does not need to concern i t s e l f with encouraging Medical p h y s i c i a n s t o decrease t h e i r use of the Emergency Unit., The problem seems to be a r e s u l t of the number of t o t a l Medical p a t i e n t s , not n e c e s s a r i l y of the high p r o p o r t i o n of emergency p a t i e n t s i n t h a t s e r v i c e . 10.6 Number of P a t i e n t s One of the most obvious changes to be i n v e s t i g a t e d by the model i s i n the a r r i v a l r a t e of p a t i e n t s . The f i n a l experiment i n c r e a s e d the number of Orthopedic p a t i e n t s by "about 10%". (It turned out to be 13.4% on the one-year runs compared) and added one more Orthopedic surgeon, which reduced the s l a t i n g i r r e g u l a r i t y by making an even number of ten surgeons. C o r r e s p o n d i n g l y , the numbers of beds re s e r v e d i n the Orthopedic area were changed, as were the a l l o w a b l e l i m i t s before t r a n s f e r r i n g out an o f f - s e r v i c e p a t i e n t . The l e n g t h of the s u r g i c a l gueue s t a b i l i z e d somewhat, and i n c r e a s e d by an average of about seven. The "overflow" area u t i l i z a t i o n i n c r e a s e d s i g n i f i c a n t l y , by an average of about 5.5 beds (see F i g u r e 10.10). The Orthopedic area u t i l i z a t i o n d i d 158 zoo-. 160 H h-uo- UJ „ » 1 Yl * r 1\ * 1 35 1 H * f T I M E ( w e e k s ) F i g . 10.8 Med i c a l p a t i e n t s p l a c e d o f f - s e r v i c e (per 4 weeks) as a f u n c t i o n of time : O r i g i n a l x ; Experiment o 3o-i 18 H Ld c O -T 1 jfij 1 1 ^ 1— T I M E ( w e e k s ) F i g . 10.9 S u r g i c a l "No Bed" c a n c e l l a t i o n s (per 4 weeks) as a f u n c t i o n of time : O r i g i n a l x ; Experiment o V 4 - 159 not change a p p r e c i a b l y . The number of p a t i e n t s who were returned t o the Medical area i n c r e a s e d about 20%, by 93 i n 44 weeks. Th e r e f o r e , the number of Medical p a t i e n t s who were sent o f f - s e r v i c e i n c r e a s e d , by 77. Although t r a n s f e r l i m i t s had to be t i g h t e n e d c o n s i d e r a b l y , the t o t a l number of "No Beds" changed only s l i g h t l y to 107 from 106 and v a r i e d l e s s than before (see Figure 10.11). The number of Orthopedic procedures i n c r e a s e d by about two per week to compensate f o r the e x t r a demand. The e x t r a surgeon f a c i l i t a t e d t h i s e f f e c t . The average wait of Orthopedic p a t i e n t s i n c r e a s e d by l e s s than one day. As mentioned b e f o r e , the h o s p i t a l probably does a b e t t e r job than the model of l e v e l i n g the use of the Orthopedic s l a t e over a l l days-of-the-week. The i n c r e a s e of one surgeon i n the experiment achieves t h i s same e f f e c t to some extent, thereby r e d u c i n g the impact of the e x t r a p a t i e n t s . N e v e r t h e l e s s , the experiment shows what e f f e c t such an i n c r e a s e i n Orthopedic p a t i e n t s would probably have on the demand f o r " o v e r f l o w " beds and on the number of "No Beds". 160 SO-i U-t I | 7^ | 1 ^ 1 1 ? i 1 ^ T I M E ( w e e k s ) F i g . 10.11 S u r g i c a l "No Bed" c a n c e l l a t i o n s (per 4 weeks) as a f u n c t i o n of time : O r i g i n a l x ; Experiment o 161 CHAPTER 11 PHOPOSALS FOR EOTORE CONSIDERATION- In t h i s chapter I suggest areas which may be i n v e s t i g a t e d f o r development, improvement and use o f the model. These suggestions are intended t o be of a s s i s t a n c e i n d e f i n i n g the scope of f u r t h e r study and d e t a i l i n g some p o s s i b i l i t i e s . 11.1 Data C e r t a i n data items not p r e v i o u s l y a v a i l a b l e are now being c o l l e c t e d at St. Paul's. The experience gained i n t h i s p r o j e c t suggests improved c o l l e c t i o n methods f o r o t h e r s . In a d d i t i o n , changes i n p o l i c y or p r a c t i c e a t St. Paul's c a l l f o r updating c e r t a i n other data., Some f u r t h e r comments appear on Table V I I I . A s i g n i f i c a n t improvement at St. P a u l ' s , from the p o i n t of view of s t u d i e s of t h i s s o r t , concerns the the amount of data being c o l l e c t e d by the Admitting O f f i c e . , As of 1977, the f o l l o w i n g items are recorded d a i l y . , (i) Regarding o v e r a l l admissions: t o t a l number of admissions, admissions to extended c a r e , number of "No Beds", emergency admissions ( t o t a l . M e d i c a l , and s u r g i c a l ) , DU admissions, admissions t o the c o r r e c t area, admissions to the wrong area 162 ( i i ) By s e r v i c e : scheduled admissions, urgent admissions, admissions t o the c o r r e c t area, "No Bed" c a n c e l l a t i o n s ( i i i ) By s e r v i c e area: t r a n s f e r s {how many, where, and why) I s t r o n g l y urge the use of such data to r e f i n e and update the v a l i d a t i o n of the model. As I have i n d i c a t e d s e v e r a l times i n the t h e s i s , improved o b s e r v a t i o n of the forms on p a t i e n t s awaiting admission would be a d v i s a b l e . , I t would allow b e t t e r v a l i d a t i o n of the l e n g t h of the queue and of t h e d i s t r i b u t i o n of w a i t i n g times. In the H e d i c a l area, the c a r e f u l o b s e r v a t i o n of the queue might suggest some p e r t i n e n t a l g o r i t h m f o r determining whom to admit. Teaching p a t i e n t s w i l l probably need to be d i f f e r e n t i a t e d from non-teaching p a t i e n t s . In the s u r g i c a l area, the e n t i r e s l a t e should be recorded f i r s t ! Then a d d i t i o n s and v a r i a t i o n s may be noted d a i l y . C a r e f u l r e c o r d s w i l l enable a more exact study of the development o f the s l a t e , p a r t i c u l a r l y with r e s p e c t to p a t i e n t category. The c o l l e c t i o n of t h i s data must be done i n the Admitting O f f i c e and OR Booking O f f i c e . To a v o i d unacceptable i n t e r f e r e n c e with the d a i l y o p e r a t i o n of the OR Booking O f f i c e , i t should be done " a f t e r hours". The f i r s t couple of c o l l e c t i o n s e s s i o n s should be used to record i n f o r m a t i o n d e s c r i b i n g every day and every admission form which appears on the s l a t e or i n the f i l e box. A f t e r t h a t , a d d i t i o n s . 163 c a n c e l l a t i o n s , postponements, and replacements may be noted. I f done " a f t e r hours", i t should a l s o be p o s s i b l e to look a t the c o p i e s of the s l a t e s prepared one and two days i n advance. T h i s w i l l help p a r t i c u l a r l y i n n o t i n g i n - h o s p i t a l and other " l a s t - m i n u t e " changes. Due to the a d d i t i o n of Day Care surgery s i n c e 1974, i t might be a d v i s a b l e to c o l l e c t a more r e c e n t sample of surgery data. Furthermore, OR s u p e r v i s o r y s t a f f suggest t h a t the d i f f i c u l t y (and hence the length) of o p e r a t i o n s has i n c r e a s e d somewhat s i n c e 1974. For m u l t i p l e OH s e r v i c e s , data should be c o l l e c t e d by s e r v i c e r a t h e r than by OR. LOS data, as p r e s e n t l y c o r r e c t e d to exclude P e d i a t r i c s , are now q u i t e r e l i a b l e . , As p a t i e n t volume v a r i e s however, t h i s w i l l r e g u i r e improvement. Emergency data, p a r t i c u l a r l y i f supplemented by the new Admitting O f f i c e r e c o r d s , are adequate. Instead of the s i n q l e , continuous-time sample, one taken at random dates throuqhout the year raiqht be d e s i r a b l e . I f i t i s d e s i r a b l e to d i s t i n q u i s h t e a c h i n g beds, a comparative study o f t e a c h i n q and non-teaching p a t i e n t s ' LOS would be a d v i s a b l e . 11.2 Model M o d i f i c a t i o n and Expansion As i n d i c a t e d i n the comments on data, a d d i t i o n a l i n f o r m a t i o n may r e v e a l a more complex mechanism f o r admission of Medical scheduled p a t i e n t s , and f o r development of the s l a t e . 164 In p a r t i c u l a r , S e c t i o n 7.3 suggests a l e s s r i g i d d a i l y bed l i m i t f o r scheduled s u r g i c a l , p a t i e n t s , and m o d i f i c a t i o n of the a p p r o p r i a t e a l g o r i t h m so t h a t the l e n g t h of time to a requested surgery date i s not completely random. In order to f i l l up the s l a t e s , e i t h e r numbers or the whole concept of "composite" p h y s i c i a n s may have to be modified. , B e t t e r l i m i t s and r u l e s may a l s o be found r e g a r d i n g t r a n s f e r s , p a r t i c u l a r l y i f "overflow" beds are l i m i t e d . The a d d i t i o n a l data may make i t f e a s i b l e t o i n t r o d u c e extended care u n i t s to the model., Caution should be e x e r c i s e d however, as t h i s c o m p l i c a t i o n i n the model may not be warranted i n terms of the a d d i t i o n a l u s e f u l i n f o r m a t i o n t h a t would be obtained. The s e r v i c e s not yet i n c l u d e d i n the model may be implemented. However, two of these. General Surgery and Neurosurgery / P l a s t i c s u r g e r y are not block booked, and would r e q u i r e f u r t h e r study. T h i s e x t e n s i o n would be f a i r l y expensive i n terms of computer run time. Thus, i t should only be done i f i t would be u s e f u l f o r experimentation, and not merely f o r "completeness sake". 11.3 Experiments The questions which were mentioned i n S e c t i o n 2.4 and are provided i n Appendix 1.4 q i y e a number of i d e a s f o r experiments. A d d i t i o n a l d i s c u s s i o n with St. Paul's a d m i n i s t r a t i o n would no doubt add o t h e r s , perhaps more v a l u a b l e from the immediately 165 p r a c t i c a l p o i n t of view. , Some a d d i t i o n a l suggestions f o l l o w . The s c h e d u l a b l e and non-schedulable admissions data may be analyzed f o r c y c l i c a l p a t t e r n s , e s p e c i a l l y weekly. The e f f e c t of i n c o r p o r a t i n g t h i s i n t o the model c o u l d then be t e s t e d . For example, i t might be p o s s i b l e to generate p a t i e n t s each week from one d i s t r i b u t i o n and to sample from that group on a d a i l y b a s i s . According to a d m i n i s t r a t i v e suggestions, there are supposed to be 18 beds reserved f o r the emergency p a t i e n t s who may a r r i v e a f t e r the scheduled admissions. These beds could be l o c a t e d i n the v a r i o u s s e r v i c e areas i n order to t e s t t h e e f f e c t of observing such a l i m i t . I t might be of i n t e r e s t t o check the e f f e c t of s e p a r a t i n g areas by sex. The model a l r e a d y provides data on average numbers of males and females i n the h o s p i t a l , by s e r v i c e . These data should provide enough of a g u i d e l i n e that i t would be unnecessary to complicate the model by r e s t r i c t i n g beds t o usage a c c o r d i n g to sex. I t i s expected t h a t the number of a r r i v a l s a t the emergency u n i t i s f a i r l y random. The d e c i s i o n to admit from t h i s u n i t may be r e g u l a t e d somewhat by occupancy. I t might be p o s s i b l e to i n v e s t i g a t e the h y p othesis of occupancy-regulated emergency admissions and i n c o r p o r a t e f i n d i n g s i n t o the model. I t would be u s e f u l to i n v e s t i g a t e and b u i l d i n t o the model any c o n t r o l s on admissions or t r a n s f e r s which tend to maintain the occupancy l e v e l s of the v a r i o u s s e r v i c e areas at St. Paul's. An i n v e s t i g a t i o n of the f a c t o r s which c o n t r o l the 166 l e n g t h of the Medical w a i t i n g l i n e would a l s o be i n s t r u c t i v e . 167 CHAPTER J.2 DISCUSSION T h i s chapter r e f l e c t s on the i n f o r m a t i o n gained i n stu d y i n g and modelling p a t i e n t admissions and sch e d u l i n g a t St. Paul's H o s p i t a l . The f i r s t s e c t i o n d i s c u s s e s c e r t a i n i n f o r m a t i o n r e v e a l e d by the data which was s u r p r i s i n g , when compared with formal h o s p i t a l p o l i c y . The second s e c t i o n comments on the value of s i m u l a t i o n i n the h o s p i t a l s e t t i n g , from my vantage point . , 12.1 System Lapses Revealed by Data My f i r s t comment regards p a t i e n t d i a g n o s t i c c a t e g o r i e s as d e f i n e d by an a d m i n i s t r a t i v e d i r e c t i v e (see S e c t i o n 5 . 2 . 4 ) . Even w i t h i n a s i n g l e s u r g i c a l s e r v i c e , not a l l p h y s i c i a n s i n t e r p r e t the c a t e g o r i e s i n the same way. One p h y s i c i a n may i d e n t i f y a l l h i s p a t i e n t s as semi-urgent, another as a l l e l e c t i v e - though the s l a t e d o p e r a t i o n a l procedures are i d e n t i c a l . The most amazing problem has to do with urgent p a t i e n t s who are supposed t o be admitted w i t h i n two weeks. A surgeon w i l l i d e n t i f y h i s p a t i e n t as urgent and request a day f o r surgery f o u r or f i v e weeks away! T h i s i s not uncommon and i s not r e s t r i c t e d to s e r v i c e s with p a r t i c u l a r l y " t i g h t " s l a t e s . The s i t u a t i o n i s even more pronounced with Medical p a t i e n t s . The c r o s s - s e c t i o n of w a i t i n g times i n one recent sample was as i n Table XVI. Notice p a r t i c u l a r l y t h a t urgent p a t i e n t s are 168 supposed to be admitted w i t h i n two weeks and semi-urgent p a t i e n t s w i t h i n one month. {T = teaching) TABLE XVI AL CROSS-SECTION OF WAITING TIMES Wait so f a r T 0 0- 2 weeks 2 2 weeks-1 month 2 1- 2 months 3 2- 3 months 0 over 3 months 1 Perhaps the c l a s s i f i c a t i o n method should be re-examined or re-emphasized. There i s a f u r t h e r g e n e r a l problem with lon g - s t a y p a t i e n t s i n a l l acute-care h o s p i t a l s . T h i s problem may be h i g h l i g h t e d by a simple c a l c u l a t i o n i n which r e a l i s t i c approximations have been made. Consider a s e r v i c e , such as Medicine, with an average le n g t h of s t a y o f about twelve days. Seven percent of the p a t i e n t s stay over t h i r t y days, f o r an average of f i f t y days. The o t h e r 93% have a mean stay o f nine days. Then, 1% of the p a t i e n t s account f o r 30% of the bed-days used. T h i s s o r t of in f o r m a t i o n should urge improved placement of lo n g - s t a y p a t i e n t s . F i n a l l y , i t appears t h a t Orthopedic bed a l l o c a t i o n by sex U T SO SO T E l E l 0 2 2 2 4 0 0 3 1 1 1 0 1 0 4 0 1 1 0 1 0 2 1 1 0 169 does not correspond to usage. I t seems from my i n f o r m a t i o n that 40 Orthopedic beds are f o r males, 30 f o r females. The model i n s i s t s t h a t females almost always use more beds - averaging 35.5 beds to 31.4 f o r males. 12.2 Value of S i m u l a t i o n In a H o s p i t a l Context - A Personal View My remarks on t h i s p o i n t must be p r e f a c e d by a concern f o r how the p r o j e c t i s c a r r i e d out. I t i s t r u e that i n t h i s case we approached St., Paul's H o s p i t a l with a proposal f o r a Master's t h e s i s p r o j e c t . At t h a t time, I d i d have a s t r o n g background i n Mathematics, and some experience i n computer s i m u l a t i o n . However, i f a h o s p i t a l wished t o c a r r y out a study of t h i s s i z e , i t should not c o n s i d e r c o n s u l t i n g anyone without a c t u a l experience i n such r e s e a r c h . The task of becoming f a m i l i a r with the h o s p i t a l system, g a t h e r i n g and p r o c e s s i n g a p p r o p r i a t e data, l e a r n i n g a computer s i m u l a t i o n language s u i t a b l e to the p r o j e c t , modelling the system, programming the s i m u l a t i o n , t e s t i n g and running i t i s , f r a n k l y , enormous. I t r e q u i r e s a good deal of time and money. , Having s a i d t h a t , l e t me add t h a t I b e l i e v e my model i s now a good one, f a r s u r p a s s i n g i t s e x p e c t a t i o n s . L a r g e - s c a l e s i m u l a t i o n can be p r o f i t a b l e i n a h o s p i t a l context i f performed by an i n d i v i d u a l (or p r e f e r a b l y by a team) competent i n a n a l y z i n g h o s p i t a l systems and i n modelling and s i m u l a t i o n . I f the h o s p i t a l i s c a r e f u l l y run i n terms of data c o l l e c t o n , of 170 p o l i c y d e f i n i t i o n , and of adherence t o t h a t d e f i n i t i o n - so much the b e t t e r . , B a s i c a l l y a s i m u l a t i o n model such as t h i s one processes an input stream of p a t i e n t s , u s i n g c e r t a i n admission and s c h e d u l i n g mechanisms and a c e r t a i n number of beds and OS's, to produce a throughput r a t e , w a i t i n g l i n e i n f o r m a t i o n , and "No Bed" c a n c e l l a t i o n i n f o r m a t i o n . Such a " b l a c k box" model, i f good, and i t can be, i s designed to be v a l u a b l e as an a d m i n i s t r a t i v e t o o l . The primary r o l e of s i m u l a t i o n i n a h o s p i t a l s e t t i n g i s , and f o r h o s p i t a l s with l i m i t e d resources probably should be, s m a l l - s c a l e . S i n g l e wards or OB u n i t s can be s t u d i e d r e l a t i v e l y e a s i l y , with the s t u d i e s t a i l o r e d t o p a r t i c u l a r q u e s t i o n s . The e x e r c i s e of developing a l a r g e - s c a l e model i s i n f o r m a t i v e i n i t s e l f . , An examination of the data necessary f o r such a model a l e r t s the researcher t o c e r t a i n l a p s e s i n the system and t o other aspects which i n v i t e i n v e s t i g a t i o n (as those i n S e c t i o n s 12.1 and 11.3). Having the data, he can i n v e s t i g a t e other problems which may be suggested i n an u n g u a n t i f i e d form by h o s p i t a l s u p e r v i s o r y s t a f f (such as t h a t i n S e c t i o n 10.5). The implementation of such a l a r g e - s c a l e model on a computer w i l l r e v e a l a d d i t i o n a l areas of the system which are p a r t i c u l a r l y s e n s i t i v e to the v a r i a b l e s which a f f e c t them (such as the length of the Medical gueue and the number of Medical p a t i e n t s placed o f f - s e r v i c e ) . F i n a l l y , i t i s p o s s i b l e to develop a reasonable r e p r e s e n t a t i o n of an i n t r i c a t e h o s p i t a l system ( r e f e r to the v a l i d a t i o n i n S e c t i o n 9.3). The computer model can q u a n t i t a t i v e l y analyze the i n t e r a c t i o n of a l a r g e number of 171 v a r i a b l e s , which i t would be otherwise i m p o s s i b l e to estimate e f f e c t i v e l y . From t h a t p o i n t , there i s a vast a r r a y of a p p l i c a t i o n s f o r which the model may be used ( f o r example, r e f e r to Chapter 10 and to S e c t i o n 11.3). I f i n proper communication with the h o s p i t a l a d m i n i s t r a t i o n , the r e s e a r c h e r may e x p l a i n the numerical r e s u l t s of experiments, and co-operate i n a n a l y z i n g the impact which would f o l l o w from the a p p l i c a t i o n of such experimental s i t u a t i o n s . Though not i n e x p e n s i v e , a computer s i m u l a t i o n of a l a r g e - s c a l e h o s p i t a l model has v a l u a b l e p o t e n t i a l . 172 LIST OF REFERENCES 1. Anonymous. (1966) "Computer S i m u l a t i o n of H o s p i t a l D i s c h a r g e s . " V i t a l and Health S t a t i s t i c s ^ N a t i o n a l Center f o r Health S t a t i s t i c s . , PHS P u b l i c a t i o n No. 1000, S e r i e s 2, No. 13. Washington, D.C: U.S. Government P r i n t i n g O f f i c e , February. 2. Anonymous. (1971) General Purpose S i m u l a t i o n System V User's Manual., White P l a i n s , New York: IBM Corp. T e c h n i c a l P u b l i c a t i o n s Dept. 3. 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(1973) "A S t a t i s t i c a l Model of Length of Stay i n a Mental H o s p i t a l . 1 ; Health S e r v i c e s Research, 8 (Spring):37-45. 29. flearn, C a t h e r i n e Rhys and Bishop, J . M. (1970) "Computer Model S i m u l a t i o n Medical Care i n H o s p i t a l . " B r i t i s h Medical J o u r n a l , 3:396-399. 30. Johnson, Kenneth C. (1963) " F o r e c a s t i n g H o s p i t a l Admissions." H o s p i t a l T o p i c s , 4 1 (November) : 50-53. 31. Kao, Edward P.C. (1972) "A Semi-Markovian Model t o P r e d i c t Recovery Progress of Coronary P a t i e n t s . " Health S e r v i c e s Research, 7 (Fall):191-207. 32. . , (1973) "A Semi-Markovian P o p u l a t i o n Model with A p p l i c a t i o n s to H o s p i t a l Planning.',' I.E. E. E. T r a n s a c t i o n s on Systems, Man,and C y b e r n e t i c s , SMC-3 (July):327-336. 33. (1974) "Study of P a t i e n t Admission P o l i c i e s f o r S p e c i a l i z e d Care F a c i l i t i e s . " I.E.E.E. T r a n s a c t i o n s on Systems, Man,and C y b e r n e t i c s , SMC-4 (November):50 5-512. 34. Kohler, C O . , Wagner, G. , and Wolber, U. (1977) " P a t i e n t Scheduling - ( B i b l i o g r a p h y ) . " Methods of Information i n Medicine, 16 (April):112-115. 35. K o l e s a r , Peter. (1969-1970) "A Markovian Model f o r H o s p i t a l Admission S c h e d u l i n g . " Management Science, S e r i e s B, 116:B-384 - B-396. 36. K u z d r a l l , Paul J . , Kwak, N. K., and Schmitz, Homer H. (1974) "The Monte-Carlo S i m u l a t i o n of Operating-Room and Recovery-Room Osage." Operations Research, V o l . 22, No. 2, pp. 4 34-440. 175 37. Kwak, N. K., K u z d r a l l , Paul J . , and Schmitz, Homer H. (1976) "The GPSS Si m u l a t i o n of S c h e d u l i n g P o l i c i e s f o r S u r g i c a l P a t i e n t s , " Management Scie n c e , 22 (May):982-989. 38., Lew, I. (1966) "Day of the week and Other V a r i a b l e s A f f e c t i n g H o s p i t a l Admissions, D i s c h a r g e s , and Length of Stay f o r P a t i e n t s i n the P i t t s b u r g h Area." I n q u i r y , 3(February):3-39. 39. McCorkle, L o i s P. (1966) " U t i l i z a t i o n of F a c i l i t i e s of a U n i v e r s i t y H o s p i t a l : Length of I n p a t i e n t Stay i n V a r i o u s H o s p i t a l Departments." H e a l t h S e r v i c e s Research, 1.1(Summer):91-114. 40. Meredith, Jack. (1973) "A Markovian A n a l y s i s of a G e r i a t r i c Ward." Management S c i e n c e , 19 (February):604-612. 41... Milsum, John H., Turban, Efraim, and V e r t i n s k y , H a n . {1973) " H o s p i t a l Admission Systems: T h e i r E v a l u a t i o n and Management." Management Science, 19 (February):646-666. 42. Naylor, Thomas H., and F i n g e r , J . , M. {1971) " V a l i d a t i o n , " In Comjputer S i m u l a t i o n Experiments with Models of Economic Systems, Thomas H. Naylor. New York, London, Sydney, Toronto: John Wiley S Sons. Chapter 5, pp.153-164. 43. Newell, D. J . (1964) "Problems i n E s t i m a t i n g the Demand f o r H o s p i t a l Beds." J . Chronic Diseases, 17:749-759. 44. Pike, Malcolm C., P r o c t o r , David M., and W y l l i e , John M. (1963) " A n a l y s i s o f Admissions t o a C a s u a l t y Ward." B r i t . J . P r e v e n t i v e and S o c i a l Medicine, 17:172-176. 45. Reitman, J u l i a n . (1967) "The User of S i m u l a t i o n Languages - the F o r g o t t e n Man. »> Proc. ACM, pp. 537-579. 46. Robinson, Gordon H., Wing, P a u l , and D a v i s , L o u i s E. (1968) "Computer S i m u l a t i o n of H o s p i t a l P a t i e n t Scheduling Systems." Health S e r v i c e s Research, 3 (Summer):130-141. , 47. , Schmitz, Homer H. , and Kwak, N. K. (1972) "Monte C a r l o S i m u l a t i o n of Operating-Room and Recovery-Room Usage. , , O p e r a t i o n s Research, 20: 1171-1180. 48. , S c h r i b n e r , Thomas J . (1974) S i m u l a t i o n Using GPSS. New York, London, Sydney, Toronto: John Wiley & Sons. 176 49. Scroggs, Mrs. D. (1970) Study of P a t i e n t T r a n s f e r s Within St.. Paul's H o s p i t a l . Vancouver, B.C.: Management En g i n e e r i n g Unit of the Greater Vancouver Regional H o s p i t a l s , A p r i l . 50. Shao, D., and Thomas, W. H. (1970) "A S t o c h a s t i c Model f o r the Study of the Waiting Time of Nonemergency P a t i e n t s i n a H o s p i t a l Admission System." O.R.S.A. B u l l e t i n , V o l . 18, Sup.,, 2, p. B186. 51. Shonick, W i l l i a m . (1970) "A S t o c h a s t i c Model f o r Occupancy - Related Random V a r i a b l e s i n General - Acute H o s p i t a l s . " An._ S t a t . , Assoc. J . , 65:1474-1500. 52. Shonick, W i l l i a m and Jackson, J. R., (1973) "An Improved S t o c h a s t i c Model f o r Occupancy - Related Random V a r i a b l e s i n General - Acute H o s p i t a l s . " Operations Research, 21 (July-August):952-965. 53. Shuman, L a r r y J . , Speas, R. Dixon, J r . , and Young, John P. (1975) Operations Research i n Health Care. Baltimore and London: The Johns Hopkins U n i v e r s i t y Press. 5 4 ^ Stimson, David H. , and Stimson, Ruth, H. (1972) Operations Research i n H o s p i t a l s : D i a g n o s i s and Prognosis. Chicago: H o s p i t a l Research and E d u c a t i o n a l T r u s t . 55. Thomas, Warren H. (1968) "A Model f o r P r e d i c t i n g Recovery Progress of Coronary P a t i e n t s . " Health S e r v i c e s Research, 13 (Fall):185-213. 56. Uyeno, Dean. (1976) A Text of Notes on S i m u l a t i o n f o r Commerce 510. Unpublished notes, F a c u l t y of Commerce, U n i v e r s i t y of B r i t i s h Columbia, Vancouver. 57. Young, John P. (1965) " S t a b i l i z a t i o n of I n p a t i e n t Occupancy Through C o n t r o l of Admissions." H o s p i t a l s , 39 (Oct.. 1):41-48. , 58. (1966) " A d m i n i s t r a t i v e C o n t r o l of M u l t i p l e Channel Queuing Systems with P a r a l l e l Input Streams." Operations Research, 14:145-156. APPENDICES APPENDIX 1-(Refers to Chapter 2) .1 E a r l y S p e c i f i c a t i o n s f o r the Model MICRO-SIMULATION MODEL OF ST. PAUL'S HOSPITAL PROJECT OBJECTIVE To model the patient flow in and through St. Paul's Hospital. SUB OBJECTIVES 1. To build a dynamic computerized model \rfiich can be U3ed to provide guidelines for management action in controlling hospital admissions to effectively u t i l i z e hospital resources. 2. To determine on a daily basis how many patients to admit by specialty. 3. To demonstrate effect on hospital occupancy of adding/subtracting physicians to the medical roster. (Surgeons, non-surgeons, anaesthetists) If. To demonstrate the effect of changing the bed allocation in the . hospital. 5. To reduce the number of no-bed situations. 6. To demonstrate effect of varying numbers of emergency admissions upon bed occupancy, O.R. schedules and the number of surgical cancellations. B.L. Curtis July, 1975 179 - 2 - DATA REQUIRED FOr each admission/discharge for the year January 1, 1974 to December 31 > 1974: Patient's age, sex Length of stay (or admission date and discharge date) Primary diagnosis Secondary diagnosis Type o f admission Surgical procedure(s) Attending doctor Surgeon(s) Hospital Service Type of Anaesthetic - 180 1.2 The B a s i c Information Flow PATIENTS MEDICAL PHYSICIAN SURGICAL SPECIALIST INVFSTIflAT[VFS BED CONFIRMATION ADM & SURG BOOKING FORM BED BOARD FORM BED ALLOCATION ADMITTING OFFICE SURGICAL DATE F I L E MEDICAL / INVESTIGATIVE QUEUE it. •x < L  <o c OL UJ LL. if. CO L  z < a. tx. < 1-•x it. c SURG ADM FORMS TO F ILE ^ L A T E TO VERIFY ADM ADM VERIFICATION OR BOOKING OFFICE SURGICAL SLATE VISUAL F I L E COMPLETED SLATE SURGICAL WARDS (SPECIALTIES) -4tti H Q MEDICAL WARDS F i g . A 1.1 The b a s i c f l o w c h a r t o f i n f o r m a t i o n 1.3 The P r o p o s a l t o S t . Paul's H o s p i t a l 181 May 17, 1976 Dr. E.C.Q. Van Tllburg, Medical Director, St. Paul's Hospital, 1081 Burrard Street, Vancouver, B.C. Dear Dr. Van Tilburg: About a year ago Mr. Brian Curtis and myself started discussion on the problem described in the attached project description. We were restrained from actual implementation of our ideas from the lack of time and, even more importantly, the lack of a suitable collaborator who can look after the detailed work. With Mr. Mark Chase joining our program we are now in the position to proceed with this project. Presently we are finalizing our plans which are outlined in the proposal. We are anxious to i n - form a l l concerned staff and to ensure good co-operation. Brian Curtis has already contacted your secretary and arranged for a meeting with you on May 26th. I am looking forward to discussing the project with you in greater detail at that time. Yours sincerely, End. CAL/pdw Chas. A. Laszlo, Ph.D. Associate Director Division of Health Systems 182 A Proposal for the. APPLICATION OF SIMULATION TECHNIQUES TO ALLOCATION SCHEDULING, AND UTILIZATION PROBLEMS AT ST. PAUL'S HOSPITAL A number of studies have been carried out concerned with the operation of individual departments in St. Paul's using conventional management engineering techniques. In particular, Admitting, OR Scheduling and the a l l o c a t i o n of beds were investigated in depth. Although these studies provided important informa- tion i t i s now apparent that because of the complexity of the interaction of the various departments in the Hospital more sophisticated approaches are required. The range of services provided by St. Paul's has been greatly extended and a l l services have been increasingly u t i l i z e d mostly without corresponding increases in f a c i l i t i e s . As a consequence of t h i s expansion a number of operational problems have emerged: (1) Scheduling of surgical patients; (2) Allocation and u t i l i z a t i o n of operating rooms; (3) Allocation and u t i l i z a t i o n of beds; (4) Allocation and u t i l i z a t i o n of medical personnel (anesthetists, physicians, surgeons). Some problems of scheduling and resource al l o c a t i o n s may be investigated using modelling and simulation methods. These methods were developed i n response to the demand generated by complex organizational problems i n private and public i n s t i t u t i o n s . Examples of successful application of modelling and simulation methods exist i n manufacturing, marketing, transportation, banking and other areas. The application of modern operational research techniques to admitting and scheduling has aroused considerable academic i n t e r e s t . In p a r t i c u l a r , there have been numerous reports in the l i t e r a t u r e of the possible application of the exper- ience gained in other areas to th i s f i e l d . Techniques have been developed, data have been collected and computing systems and programs are available. Thus, i t seems that the time i s now ripe for the p r a c t i c a l u t i l i z a t i o n of simulation techniques. In view of the increasing acuteness of scheduling and u t i l i z a t i o n problems at St. Paul's and the possible usefulness of modelling and simulation methods, we plan to evaluate the effectiveness and potential of t h i s approach i n the St. Paul's environment. S p e c i f i c a l l y , we w i l l ; (1) Set up a simulation model; (2) Incorporate r e a l and relevant data; (3) Simulate the existing.operational environment; (4) Simulate possible alternatives for managerial evaluation. We aim to involve a l l interested people in t h i s project. Detailed reports of our progress w i l l be. made available and feedback on any and a l l aspects of t h i s work are welcome. May 1976 Brian Curtis, Head, Management Engineering Unit, Greater Vancouver Regional Hospitals, Vancouver General Hospital, Vancouver, B.C. V5Z 1M9 Mark Chase,* Graduate Student i n Applied Mathematics Chas. A. Laszlo,* Associate Director, D i v i s i o n of Health Syste Office of the Coordinator of Health Sciences John H. Milsum,* Director, Division of Health Systems, Office of the Coordinator of Health Sciences *4th Floor, IRC Building, University of B r i t i s h Columbia, Vancouver, B.C. V6T 1W5 1.4 "Questions" t o Ask of the Model 134 Questions for St. Paul's Hospital Simulation 3ed Allocation Can the allocation of beds to services be altered to increase throughput of patients? What i f numbers of patients in a l l services increases by lie; 2%; 3% - - - 20%? Can allocation of beds be altered to cope with increase of patients? What happens to length of waiting l i s t (in quantity and time to be admitted) What i f additional physicians are added to one/each service? Can allocation of beds be altered to cope with increase in number of physicians? What happens to length of waiting l i s t (in quantity and in time to be admitted) - What i f beds are not allocated by service? Can patient throughput be increased? O.R. Scheduling What i f O.R.'s are closed? Impact on bed occupancy; waiting l i s t length and time to be admitted? What i f #'s of patients increase? Impact of volume of surgeries per room, numbers of no bed occurrences. What i f § of surgeons is increased? Impact on number of surgeries; number of no bed situations; length of waiting l i s t and time to be admitted. What i f beds are booked f i r s t then O.R. time? What i f O.R. time is booked f i r s t then bed? Vary number of admissions; What happens to waiting l i s t in numbers and in time to be admitted? Emergency Admissions What i f emergency admissions increase/decrease by percentage points; by hospital service? Impact on O.R., impact on "no bed" situation. Seasonality First determine - i f occupancy varies with season - i f diagnoses vary with season If the answer to above is YES What i f we vary bed allocation on seasonal basis? Inpatient Transfers What i f number of inpatient transfers increases/decreases? Impact on surgical waiting l i s t . ^ 185 APPENDIX 2 {Refers to Chapter 7) Note that the s e c t i o n s d e a l i n g with the d e r i v a t i o n of data f o r the model are w r i t t e n i n the form of e x p l a n a t i o n s and i n s t r u c t i o n s f o r anyone who might wish to repeat or extend the data a n a l y s i s performed.. Not a l l of the data which were analyzed appears here; the Orthopedic s e r v i c e has been used as an example. A complete f i l e i s a v a i l a b l e from the D i v i s i o n of Health Systems at the U n i v e r s i t y of B r i t i s h Columbia. 2.1 Admitting O f f i c e Report 1976 186 St..Paul 's Hospital V A N C O U V E R 1 B .C. REPORT FROM THE ADMITTING DEPARTMENT - JANUARY TO DECEMBER 1976 NUMBER OF ADMISSIONS NUMBER OF DAY CARE SURGICAL ADMISSIONS NUMBER OF REGULAR AND DAY CARE ADMISSIONS NUMBER OF NEWBORNS ( INCLUDING 3 COMPANION BABES ) NUMBER OF PSYCHIATRIC ADMISSIONS NUMBER OF RENAL ADMISSIONS JANUARY - MAY NUMBER OF RENAL OUT PATIENTS PROCESSED JUNE TO DEC. NUMBER OF EXTENDED CARE ADMISSIONS NUMBER OF EXTENDED CARE DAYS NUMBER OF ADMISSIONS THROUGH THE EMERGENCY NUMBER OF URGENT DIRECT ADMISSIONS NUMBER OF MEDICAL ADMISSIONS MEDICAL ADMISSIONS TO MEDICAL AREAS MEDICAL ADMISSIONS TO OTHER AREAS EMERGENCY MEDICAL ADMISSIONS URGENT DIRECT MEDICAL ADMISSIONS URGENT DIRECT SURGICAL ADMISSIONS ADMISSIONS TO WRONG AREAS CANCELLATIONS FOR NO BED NUMBER OF TRANSFERS PLACEMENT OF PATIENTS IN CORRECT CLINICAL AREA PLACEMENT OF PATIENTS IN ACCOMODATION OF CHOICE PATIENTS' CONDITION FOR ISOLATION FOR PATIENT CARE AND MANAGEMENT NUMBER OF PATIENTS FROM OUTSIDE GREATER VANCOUVER 20577 (22 ADMISSIONS CANCELLED BY B.C.H.P.) 3104 (29 CANCELLED AFTER ADM - 26 ADMITTED) 23681 1491 807 1509 51 43 1620 1 7097 - 34.5% OF TOTAL ADMISSIONS 2152 - 10.5% OF TOTAL ADMISSIONS 5774 - 28.06% OF TOTAL ADMISSIONS 4368 - 75.7% OF TOTAL MEDICAL ADMISSIONS 1406 - 24.4% OF TOTAL MEDICAL ADMISSIONS 3525 - 61.05% OF TOTAL MEDICAL ADMISSIONS 883 - 15.3% OF TOTAL MEDICAL ADMISSIONS 1089 3151 - SURGICAL 1745 - MEDICAL 1406 372 - AN AVERAGE OF 31 PER MONTH 8795 - AN AVERAGE OF 24 PER DAY 2810 810 2304 272 2599 5029 F i g . A 2.1 A d m i t t i n g O f f i c e r e p o r t 1976 1 8 7 2.2 P a t i e n t D i a g n o s t i c C a t e g o r i e s Emergency admissions data c o l l e c t e d on a l l s e r v i c e s f o r 32 days showed 611 p a t i e n t s . T h i s would give 6965 p a t i e n t s i n a year. In 1976, t h e r e were a c t u a l l y 7097 emergency p a t i e n t s . Hence, the emergency data which was c o l l e c t e d i s g u i t e r e l i a b l e , although a b i t low. The t o t a l number o f DU p a t i e n t s i s known. Each s e r v i c e may be expected t o have the same p r o p o r t i o n of DU's as i t does of emergencies. The t o t a l admissions ( e x c l u d i n g O b s t e t r i c s ) i n 1974 were 18,853 (from PAS). 1976 t o t a l admissions were 20,577. Hence, co n s i d e r the PAS s e r v i c e t o t a l s to be g u i t e r e l i a b l e . To get the number of s c h e d u l a b l e p a t i e n t s , one can s u b t r a c t emergency and DU t o t a l s from o v e r a l l t o t a l s , each of these being f a i r l y r e l i a b l e . For s u r g i c a l s e r v i c e s , the s l a t e s can be used to check the number of s c h e d u l a b l e p a t i e n t s , by noting t h a t t h e r e are 250 o p e r a t i n g days per year ( s l a t e d ) and r e d u c i n g the t o t a l number of o p e r a t i o n s by the estimated number of i n - h o s p i t a l procedures. C o l l e c t e d a r r i v a l data may a l s o be used to check the number of s c h e d u l a b l e p a t i e n t s . These data f o r Orthopedic p a t i e n t s appear i n Table XVII. For the scheduled p a t i e n t s , d i a g n o s t i c c a t e g o r y was recorded. Hence, the w a i t i n g l i n e data may be used t o determine the p r o p o r t i o n s of urgent, semi-urgent, and e l e c t i v e p a t i e n t s . 188 TABLE XVII ORTHOPEDIC PATIENTS Estimated Group Data per year T o t a l 1738 from PAS data 17 40 Emergencies 57 i n 32 days gi v e s 675 650 i n a year. D i r e c t Urgents 57 of 611 emergencies were 215 Orthopedic, a s i m i l a r p r o p o r t i o n of 2152 DO's would be 201. Schedulable 100 Orthopedic procedures i n 25 days 850 - 13 e s t . i n - h o s p i t a l (at 1 per 2 days) = 87 i n 25 days or 870 i n 250 days. A l s o , 33 w a i t i n g l i n e admissions i n 11 days would be 750 i n 250 o p e r a t i n g days. Of the 51 w a i t i n g Orthopedic p a t i e n t s there were; 1 U; 10 SU; 40 E l . The r e s u l t s f o r d i a g n o s t i c category p r o p o r t i o n s of Orthopedic p a t i e n t s are; of emergency and DO p a t i e n t s : .759 Emergent / .241 D i r e c t Urgent of s c h e d u l a b l e p a t i e n t s : .020 Urgent / .197 Semi-Urgent / .783 E l e c t i v e . 189 2.3 P a t i e n t A r r i v a l D i s t r i b u t i o n s The 1974 s l a t e s may be used t o o b t a i n an idea of the scheduled a r r i v a l p a t t e r n , i f a weekend e f f e c t i s added. For example, i f p r e - o p e r a t i v e LOS i s constant, t h e r e w i l l be no scheduled admissions on 2/7 of the days., The observed a r r i v a l p a t t e r n of emergency p a t i e n t s may be incremented and smoothed by DO a r r i v a l s - a r b i t r a r i l y . In Medicine, where t h e r e i s a s i g n i f i c a n t number of DU admissions, a p o s s i b l e a r r i v a l d i s t r i b u t i o n f o r them was hypothesized and combined m u l t i p l i c a t i v e l y with t h a t of emergency p a t i e n t s to g i v e the non-schadulable p a t i e n t s * a r r i v a l d i s t r i b u t i o n . The i n d i v i d u a l r a t e s may need t o be modified t o match t o t a l s of the preceding s e c t i o n . The data which determined the p r o p o r t i o n of times f o r a given number of a r r i v a l s per day, i n the s c h e d u l a b l e and immediate c l a s s i f i c a t i o n s , appear i n Table XVIII. 190 TABLE XVIII ORTHOPEDIC ARRIVALS sc h e d u l a b l e p r o p o r t i o n J emergency with p r o p o r t i o n number 10 1 4 8 6 6 of times | number I _________ D# 0. of times .2857 .0286 . 1143 .2285 .1714 . 1714 6 9 6 7 1 2 6 6 9 7 6 2 1 .1622 . 1622 .2432 .1892 .1622 .0541 .0270 I f the random number generator y i e l d s a uniform d i s t r i b u t i o n , a c a l c u l a t i o n r e v e a l s t h a t these p r o p o r t i o n s should y i e l d 1745.7 Orthopedic p a t i e n t s per year, which i s c l o s e enough t o the approximately 1740 d e s i r a b l e . 191 2.4 P a t i e n t Sex and Age Groups F i r s t of a l l , i t i s u s e f u l to t a b u l a t e the number of p a t i e n t s i n each age group / sex category f o r the PAS data, and count and t a b u l a t e s i m i l a r l y f o r a l l c o l l e c t e d S l a t e and Emergency data (of 1976). C a l c u l a t e the percentages of each sex and of each age group w i t h i n sex f o r these samples. The PAS data should be modified s l i g h t l y i n the d i r e c t i o n of the s m a l l e r sample data, to give a f i n a l s e t of percentages t o use. In the age data, s i n c e PAS i n c l u d e s P e d i a t r i c p a t i e n t s which are no longer a St. Paul's s e r v i c e group, a f u r t h e r stage i s u s e f u l . In the PAS data, a r b i t r a r i l y f i x the percentage of p a t i e n t s i n the 0-14 age group at a l e v e l compatible with the 1976 data. Compute the other percentages again so that they f i l l the remaining t o t a l i n the same p r o p o r t i o n s as b e f o r e . Use t h i s set of values to combine with the 1976 values f o r a f i n a l f i g u r e . These data f o r Orthopedic p a t i e n t s f o l l o w i n Tables XIX - XXI. TABLE XIX SEX OF ORTHOPEDICS PAS 54.3755 male 1976 51.26% male USE 53.5 % male TABLE XX ORTHOPEDIC HALE AGE GROUPS Age PAS PAS with group % 1st gp set 1976 0-14 7.20 2.00 1.64 15-34 39.37 41.57 44.26 35-54 31.01 32.75 34.43 55-74 18.20 19.22 16.39 75 + 4.23 4.45 3.28 TABLE XXI ORTHOPEDIC FEMALE AGE GROUPS Age PAS PAS with group % 1st gp set 1976 0-14 5.93 2.00 0.00 15-34 24.09 25.10 39.66 35-54 21.82 22.74 29.31 55-74 27.99 29.17 29.31 75 + 20.18 21.03 15.22 193 2.5 P a t i e n t Length of Stay The age group / sex t a b u l a t i o n f o r LOS, produced from the PAS data appears on the next page (Table XXII). C l e a r l y the average LOS f o r females (16.36) i s much higher than t h a t f o r males (12.38). Instead o f being based on sex, t h i s d i f f e r e n c e can be e x p l a i n e d by age - s i n c e t h e r e are more females i n the o l d e r (longer stay) groups. To t e s t t h i s , the pr o p o r t i o n of males i n each age group was m u l t i p l i e d by the average LOS of females i n each age group., T h i s was thought to giv e a value which c o u l d be compared to the male o v e r a l l average with the e f f e c t of age removed. „ 7.02 ( 68 / 945 ) + 9.04 ( 372 / 945 ) + 11.13 ( 293 / 945 ) + 17.61 ( 172 / 945 ) * 31.79 ( 40 / 945 ) = 12.06 .... modified female average vs 12.38 ... male average As a r e s u l t , i t was decided t h a t s i n c e the model a l r e a d y a s s i g n e d age group by sex, i t would s u f f i c e t o a s s i g n LOS based on age group o n l y ( i . e . r e g a r d l e s s o f sex, the LOS would be sampled from the d i s t r i b u t i o n corresponding t o the age group of the p a t i e n t ) . To see how the LOS d i s t r i b u t i o n was obtained f o r a p a r t i c u l a r age group, c o n s i d e r the 35-54 age group of Orthopedics i n Table XXIII. ) 194 T A B L E X X I I P A S L O S T A B U L A T I O N AGE CROUP/SEX MALE FEM ALB ALL 0 • la • 18 • 8 • 11 • 2 • 0 * 0-14 0 3_ To' u 11 5 o o o 14 34 30 19 16 2 0 68 * 560 • 10656 • 8 .24 * * * » ' 3 12 81 177 67 7.02 47 330 4226 1 5 38 89 37 * 115 * 890 » 14882 * 7 . 74 4 17 119 266 104 • 9 * 9 • 18 « • 4 • 2 • 6 * 1 5 - 3 * . * • « • 372 * 191 563 « * 3211 * 1726 * 493 7 « • 124109 « 43364 * 167473 « 8 .63 8.77 LENGTH OF STAY Patients .atayingi— 2-3 4-7 8-15 16-31 32-63 —64+ days -day: days days days days days Total patients Total days Sum of squares of days Average Days ******** * *************************** • 2 • 2 * 4 • » 5 " * 4 9 • * 48 * 26 • 74 » * 107 * 54 * 161 * • 71 * 46 * 117 * * 41 * 34 • 75 * « 15 * 6 • 21 * 4 1 5 • 35 -54 • • • ' « • 293 » 173 * 466 « * 3372 * 1926 • 5298 « • 9 8696 * 45386 * 144082 * : _ * 11.51 * 11. 13 * 11.37 * • 2 * 1 » 3 * • 2 • 6 * 8 * • 27 * 30 * 57 » « 34 * 58 * 92 * : t '_ * 43 • ' 37 * 80 • 40 • 56 96 * • 18 • 28 • 46 * • 6 • 6 • 12 » 5 5 - 7 4 • * * * • 172 • 222 * 394 « * 2857 * 3909 * 6766 * V 102115 * 172467 * 274582 « • 16.61 * 17.61 • 17.17 * * 0 « 0 * 0 • • 1 * 0 * 1 » • 1 • 5 * 6 * • 6 • 13 * 19 • * 4 * 27 * 31 * • 9 * 60 * 69 « • 9 • 40 * 49 * • 10 • 15 * 25 • GE 75 • • • • • 40 • 160 * 200 * * 1701 * 5086 • 6787 • * 141359 * 277956 « 419315 « • 42.52 * 31.79 * 33 .93 • »••*»• *»*******•*.**•*•*»***#*.**.*.*»*•***«*,*.* * 7 • 4 • 11 • • 31 • 18 • 49 • • 175 • 115 * 290 • • 342 • 226 * 568 • • 19 3 * 158 • 351 • • 120 • 165 • 285 * • 53 • 83 * 136 • • 24 • 24 • 48 • ALL ' * • * • • 945 • 793 * 1738 • • 11701 • 12977 * 2*678 • » 476933 • 543399 * 1020334 * • 12.38 16 .36 • 14.20 • 195 TABLE XXIII EMPIRICAL LOS : AGE 35-54 ORTHOPEDICS 1 No. of | I i Cumulative J Time Days j p a t i e n t s { Percentage IJ Percentage | than 1 _ _ _ _ _ _ _ _ I I I 1 _——__. 0-1 13 2 .79 2 .79 2 2-3 74 15 .88 18 .67 4 4 -7 161 3 4 . 5 5 53 . 22 8 8-15 1 17 2 5 . 11 78 .33 16 16-31 75 16 .09 9 4 . 42 32 32-63 21 4. 51 98 .93 64 64 + 5 1.07 100.oo • • • ( a r b i t r a r i l y ended about 128) These p o i n t s , which had been s e l e c t e d i n an e f f o r t to have l o g a r i t h m i c i n t e r v a l s i n order t o t e s t a lognormal f i t to the curves, were p l o t t e d on l o g a r i t h m i c p r o b a b i l i t y paper. (See Fi g u r e A 2.2 which f o l l o w s . )  197 These o r i g i n a l p o i n t s were connected by s t r a i g h t l i n e segments {or approximated by a smooth c u r v e ) . . A d d i t i o n a l p o i n t s were then t a k e n from t h e c u r v e . The p o i n t s f i n a l l y used f o r age 35-54 O r t h o p e d i c s appear i n T a b l e XXIV. TABLE XXIV PROCESSED LOS : AGE 35-54 ORTHOPEDICS Up t o C u m u l a t i v e n days pe r c e n t a g e 1 0.0 2 2.8 4 18.7 6 37.0 8 53.2 10 62.0 12 68.7 16 78.3 20 85.2 24 88.9 32 94.4 40 96.6 48 97.7 64 98.9 80 99.5 96 99.7 128 100.0 198 Note: No p a t i e n t s were c o n s i d e r e d to have 0 days s t a y , as there i s a separate Day Care surgery s e r v i c e now, and such p a t i e n t s would not count on the census. The l a r g e number of i n t e r m e d i a t e p o i n t s taken from the graph were of v a l u e because the GPSS f u n c t i o n generator i n t e r p o l a t e s l i n e a r l y between adjacent p o i n t s . The " l i n e a r " or smooth i n t e r p o l a t i o n done on the graph paper i s b e t t e r , being done a g a i n s t a l o g a r i t h m i c s c a l e f o r which the curve i s s t r a i g h t e r . 199 2.6 Length of Surgery From the 1974 s l a t e s , l e n g t h - o f - s u r g e r y data were obtained. Tables were made i n which the v a r i o u s l e n g t h s were recorded f o r each age group / sex c l a s s i f i c a t i o n . From t h i s , a t a b l e of number of p a t i e n t s and average time ( i n minutes) c o u l d be made (see Table XXV). TABLE XXV ORTHOPEDIC LENGTH OF SURGERY Age M F ALL 0-14 p a t i e n t s 4 5 9 avg. time 41 49 46 15-34 p a t i e n t s 21 10 31 avg. time 70 60 67 35-54 p a t i e n t s 27 18 45 avg. time 71 67 69 55-74 p a t i e n t s 13 18 31 avg. time 79 75 76 75 + p a t i e n t s 1 13 14 avg. time 60 111 108 ALL p a t i e n t s 66 64 130 avg. time 70. 3 75.5 72.9 200 as noted p r e v i o u s l y , i t was decided t h a t age would be c o n s i d e r e d r e l e v a n t , but not sex. For each sex group, e m p i r i c a l data were recorded and smoothed to g i v e the f u n c t i o n used (see Table XXVI). 201 TABLE XXVI Empii LENGTH OF SURGERY : AGE 15-54 ORTHOPEDICS r i c a l I i I I Processed nutes P a t i e n t s I i • ] Minutes P a t i e n t s % Cum. 15 2 1 \ 30 3 9.74 9.7 25 1 45 2 6.45 16. 1 i*5 2 50 4 12.9 29.0 50 4 55 4 12.9 41.9 55 4 60 3 9.74 51.6 60 2 65 3 9.74 61.3 65 3 70 2 6.45 67.7 70 2 75 2 6. 45 74.2 75 3 80 1 3. 23 77.4 80 1 90 2 6.45 83.9 85 1 100 2 6. 45 90.3 90 1 110 1 3. 23 93.5 95 1 120 1 3.23 96.8 100 1 130 1 3.23 100.0 110 1 120 1 140 APPENDIX 3 PSQGSAM LISTING 1 REALLOCATE BLO, 1000 , FAC , 10, ST 0, 10 ,OUE , 200, T AB, 50, VAR, 100.FSV.10 2 REALLOCATE COM,146440 3 SIMULATE *> RMULT 5177 ,169 ,27279 ,6343 5 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 6 * TABLE OF DEFINITIONS 7 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 8 9 * * AD I ST VARIABLE •IDENTIFIES SERVICE/SEX AGE OIST FUNCTION 10 * ADMMC C HA IN *MEDI CAL ADMISSIONS 11 * ADMSC CHAIN * SURGER Y ADMISSIONS 12 * ALTER MATRl X •ALTERNATE AREAS FOR EMERGENCIES 13 * A NEE N FUNCTION • NON-SCHEDULABLE EENT ARRIVALS 14 * ANMED FUNCTI ON * NON-SCHEDUL A BL E MEDICAL ARRIVALS 15 * ANORP FUNCTION! •NON-SCHEDULABLE ORTHOPEDIC ARRIVALS 16 * APRWK VARIABLE •IDENTIFY APPR WEEK ON MATRIX 17 • AR NON FUNCTION * NON-SCHEDULABLE ARRIVALS BY SERVICE 18 * ARSCH FUNCTION •SCHEDULABLE ARRIVALS BY SERVICE 19 * A SEE N FUNCTION •SCHEDULABLE EENT ARRIVALS 20 * ASMEO FUNCTION •SCHEDULA8LE MEDICAL ARRIVALS 21 * ASORP FUNCTION •SCHEDULABLE ORTHOPEDIC ARRIVALS 22 * BTIME 8VAR! ABLE •ENUF TIME IF THIS ONE SUBSTITUTED? 23 * BUNPE BVARIABLE •TO BUMP ELECTIVE OF THIS OOCTOR 24 * BUMPS BVARI ABLE •TO BUMP SEM IURGENT OF THIS DOCTOR 25 * CANCL SAVEVALUE • COUNTS NUMBER OF CANCELLATIONS 26 * CHECK SAVEVALUE • DAY TO CHECK ON SLATES 27 * CHKDR SAVEVALUE •CCCTOR TO CHECK 28 * C MKTM SAVEVALUE •SURGERY TIME TO CHECK FOR 29 • CTPRI VARIABLE • •PRIORITIES U:19 SU:18 EL :17 30 * CWEFK VARIABLE •NUMRER OF WEEKS TO CHECK DATE 31 • * OA SAM VARIABLE •NEW DR REALLY ON SAME DAY? 32 * DISCH CHAIN • DISCHARGE CHAIN 33 * OSTRO VARIABLE •SERVICE/CATEGORY FUNCTION OF DAYS TO REQ 34 * EENNO MATRIX •FOR EENT NUMBERS 35 * EENSL MATRIX •FOR EENT SLATE 36 • EENSN TABLE •EENT SLATE NUMBERS 37 * EENST TABLE • EENT SLATE TIME 3B • EINO QUEUE •EENTS IN EMERG 39 * EIN2 QUEUE • EENT S IN GSG ETC. 40 • EIN4 OUEUE • EENTS IN ORTHO 41 * EMARR SAVEVALUE •COUNTS EMERG AND O.U. ARRIVALS T flDAY K> O LO 42 * EHRED SAVEVALUE •TRACKS EMERGENCY BEDS IN USE 43 • EMGDU TABLE •EMERG AND D . U . ARRIVALS DAILY 44 • EMGNO SAVEVALUE •EMERGENCY NUMBER OPERATED 45 * EMGTM SAVEVALUE •EMERGENCY OPERATING TIME 46 * EMRGC CHAIN •EMERGENCY OPERATIONS CHAIN 47 • FMTBN TABLE •EMERGENCY OPERATED NUMBER 48 * E««TP T TABLE • EMERGENCY OPERATED NUMBER 49 * ENDWK VARIABLE • I S DATE ON WEEKEND? 50 • EOPNO SAVEVALUE • EENT NUMBER OPERATED 51 * EOPTM SAVEVALUE • E E N T OPERATING TIME 52 • GOPTM SAVEVALUE •GENERAL SURGERY OPERATING TIME 53 * GSGNO MA TRIX • F O R GENERAL SURGERY NUMBERS 54 * GSGSN TABLE •GENERAL SURGERY SLATE NUMBERS 55 * GSGST TABLE • GENERAL SURGERY SLATE TIME 56 * HI TBL VARIABLE •NUMBER OF THE HIGHEST OPERATIONS TABLE 57 * HUONG VARIABLE • NUMBER OF WEEKS WAITED FOR OPERATION 58 * W I S T VARIABLE • IDENTIFIES S E R V I C E / A G E LOS OIST FUNCTION 59 * LOSEE QUEUE • E E N T L OF STAY 60 * LOSEF QUEUE • E E N T FEMALES L OF STAY 61 * LOSEM QUEUE •EENT MALES L OF STAY 62 • LOSME OUEUE •MEDICINE L OF STAY 63 * LQSMF OUEUE •MEDICINE FEMALES L OF STAY 64 * LOSMH OUEUE •MEDICINE MALES L OF STAY 65 * LOSOF OUEUE •ORTHOPEDICS FEMALES L OF STAY 66 * LOSCM QUEUE • ORTHOPEDICS MALES L OF STAY 67 * LOSOR QUEUE •ORTHOPEDICS L OF STAY 68 * LOSO VARIABLE • IDENTIFIES S E R V I C E ' S LOS OUEUE 69 * LOSQS VARIABLE • I D E N T I F I E S S E R V I C E / S E X LOS QUEUE 70 * MACHO BVARIABLE • T O MATCH PATIENT ON DISCHARGE CHAIN 71 * "ACHR BVARIABLE • TO MATCH PATIENT ON ADM OR SURG CHAIN 72 * MACHS 8VAR IABLE • U S E D IN THE ABOVE 73 * MA DI S SAVEVALUE •MEDICAL AREA DISCHARGES 74 * MALT3 CHAIN •MEDICAL PATIENTS IN AREA 3 75 * MALT4 CHA IN • MEDICAL PATIENTS IN AREA 4 76 * MOATE SAVEVALUE •AOMISSION (OR ANOTHER) DATE TO MATCH 77 * "OGEN SAVEVALUE • D A T E GENERATED TO MATCH 78 * MEDNO MATRIX •FOR MEDICINE NUMBERS 79 * MEMRN SAVEVALUE •MEDICAL EMGOU IN MORNING 80 * MINO QUEUE •MEDICALS IN EMERG 81 * MIN2 QUEUE •MEDICALS IN GSG E T C . 82 * MI N3 QUEUE ' • M E D I C A L S IN EENT 83 * MIN4 QUEUE •MEDICALS IN ORTHO 84 * MLOSG S 6VEVA LUE • L E N G T H OF SURGERY TO MATCH 85 * MLOST SAVEVALUE • LENGTH OF STAY TO MATCH 86 • M0O6 VARIABLE • I D E N T I F Y NEW WEEK 0 SLATES 87 * MOFF VARIABLE • I D E N T I F I E S M E D - O F F - S E R V I C E CHAIN 88 * "SPAC VARIABLE •NUMBER OF BEOS FOR MED SCHEOS 89 * MSRVC SAVEVALUE • S E R V I C E TO MATCH 90 * NOBD SAVEVALUE •COUNTS NUMBER OF 'NO B E D S ' 91 * ' NOBEO TABLE • T A B U L A T E S NUMBER OF 'NO BEDS' 92 * NOFF VARIABLE •NUMBER TO PUT BACK ON SERVICE 93 * NOWTM SAVEVALUE • T I M E USED BEFCRE A BUMP 94 * QFFSL VARIABLE • O F F S E T TO SLATE MATRIX BY SERVICE 95 * OINO QUEUE • ORTHOS IN EMERG 96 0IN2 QUEUE •ORTHOS IN GSG E T C . 97 • 01 N3 OUEUE •ORTHOS IN EENT 98 * GOP NO SAVEVALUE •ORTHOPEDICS NUMBER OPERATED 99 * OOPTM SAVEVALUE •ORTHOPEDICS OPERATING TIME 100 * ORPNO MATRIX • FOR ORTHOPEDIC NUMBERS 101 * ORPSL MATRIX • F O R ORTHOPEOIC SLATE 102 ORPSN 1 TABLE 103 * QRPSI ' TABLE 104 * PTFWK ; SAVEVALUE 105 * PWEEK : SAVEVALUE 106 * SOIST ' VARIABLE 107 * SEUSC VARIABLE 108 * SGYOl. 1 VARIABLE 109 * SHIFT VARIABLE 110 * SIXWK BVARIABLE 1 1 1 * SIEFN 1 CHAIN 112 * SLEW! CHAIN 113 * SLEW2 CHAIN 114 SLEW3 CHAIN 115 * SLEW4 CHAIN 1 16 * SLEWS CHAIN 117 * SLEW6 CHAIN 118 * SLOEN CHAIN 119 * SL0W1 CHAIN 120 * SL0W2 CHAIN 121 * SLQW3 CHAIN 122 * SLC1W4 CHAIN 123 SL0W5 CHAIN 124 * SL0W6 CHAIN 125 * SLUSC VARIABLE 126 * SR VOP VARIABLE 127 * STAI OTABLE 128 * STA3 OTABLE 129 * STA4 OTABLE 130 * TMFWK SAVEVALUE 131 * TPYOA BVSRIABLE 132 * TRYDR VARIABLE 133 * USRSL SAVEVALUE 134 VTIME VARIABLE 135 * WAIT LOGIC SWITCH 136 WA ITE LOGIC SWITCH 137 * WAI TQ VARIABLE 1 38 * WEEK SAVEVALUE 139 * WEENE OUEUE 140 WEENS OUEUE 141 • WEENU OUEUE 142 * WKDAY VARIABLE 143 * WK END BVARIABLE 144 • WMEDE OUEUE 145 * WMEOS OUEUE 146 * WMEDU OUEUE 147 WORPE OUEUE 148 * WORPS OUEUE 149 * WORPU OUEUE 150 * ViRCNC VARIABLE 151 * WTE1 OTABLE 152 * WTE3 QT ABLE 153 * WTE4 OTABLE 154 * WTS1 OTABLE 155 * WT S3 OTABLE 156 • WTS4 OTABLE 157 * i WTU1 OTABLE 158 * WTU3 OTABLE 159 * WTU4 OTARLE 160 * XFERC CHAIN • ORTHOPEDIC SLATE NUMBERS • ORTHOPEDIC S L A T E TIME •ROW OF PTS FOR THE APPROPRIATE WEEK • FIRST DAY OF PRESENT WEEK ISUNDAYI • I D E N T I F I E S S E R V I C E / A G E L OF SURGERY • FOR ' S L A T E END' CHAIN , BY SERVICE • S E R V I C E FUNCTION FOR SURGERY DOW • I D E N T I F I E S DAY OR N IGHT-SHIFT FUNCTION • T H E S E OPNS IN NEW 6TH WEEK • EENT END SLATE •EENT WEEK 1 SLATE •EENT WEEK 2 SLATE • E E N T WEEK 3 SLATE • EENT WEEK 4 SLATE •EENT WEEK 5 SLATE •EENT WEEK 6 SLATE •ORTHO END SLATE • ORTHO WEEK 1 SLATE • ORTHO WEEK 2 SLATE •ORTHO WEEK 3 SLATE •ORTHO WEEK 4 SLATE • ORTHO WEEK 5 SLATE • ORTHO WEEK 6 SLATE • S L A T E CHAIN TO USE BY WEEK • S A V E V A L U E S OF OPN STATS BY SERVICE • MEDICINE LENGTH OF STAY • E E N T LENGTH OF STAY • ORTHOPEOIC LENGTH OF STAY •ROW OF TIME FCR THE APPROPRIATE WEEK • P T S AND TIME OK THIS DAY? • DESIRED DAY AND DOCTOR'S DAY CORRESPOND? •POINTER FOR SLATES AND CHAINS •T IME AFTER SUBSTITUTING • G A T E ON SURGICAL ARRIVALS • G A T E ON EMERGENCY ARRIVALS • IDENTIFIES SERVICE/CATEGORY WAIT OUEUE • WEEK TO CHECK FOR OPEN SPOTS ON SLATE • EENT E L E C T I V E WAITS • E E N T SEMI-URGENT WAITS • E E N T URGENT WAITS • D A Y - O F - T H E - W E E K (TOMORROW! •WEEKEND? •MEDICAL ELECTIVE WAITS • MEDICAL SEMI-URGENT WAITS •MEDICAL URGENT WAITS •ORTHOPEDICS ELECTIVE WAITS • ORTHOPEDICS SEMI-URGENT WAITS • ORTHOPEDICS URGENT WAITS • I N D I C A T E S WRONG AREA OUEUE •MEOICAL ELECTIVE WAITS • E E N T E L E C T I V E WAITS •ORTHOPEDICS E L E C T I V E WAITS •MEOICAL SEMI-URGENT WAITS • E E N T SEMI-URGENT WAITS •ORTHOPEDICS SEMI-URGENT WAITS •MEDICAL URGENT WAITS •EENT URGENT WAITS •CRTHOPEDICS URGENT WAITS • TRANSFERS' CHAIN 162 163 164 165 166 167 163 169 170 171 172 173 1B2 183 184 1 85 186 1 87 188 199 190 191 192 193 194 195 196 197 193 199 200 201 2 0 ? 203 204 205 206 207 208 209 2!0 211 2 1 2 213 214 2 1 5 2 1 6 217 218 219 2 2 0 221 MATRIX SAVEVALUES MATRIX SAVEVALUE FOR EACH SERVICE. ROW 1-5 CORRESPONDS TO 01 AGNOSTIC CATEGORY. ROW 6 I S THE TOTAL OF ROWS 1-5. THE COLUMNS ARE: 1 NO. GENERATED 2 NO. ADMITTED 3 NO. OF THOSE ADMITTED REOUEST ING PARTICULAR DATE 4 NO. WHO GOT THAT DATE 5 NC. ADMITTED TO WRONG AREA 6 NO. OF THOSE RETURNED TO CORRECT AREA 174 ME CINQ ECU l . Y 175 MEDNO MATRIX H.6,6 * FOR 176 GSGNO EQU 2tY 177 GSGNO MATRIX H.6 ,6 *FOR 178 EENNO EOU 3. Y 1 79 EENNO MATRIX H.6,6 • FOR 180 ORPNO EOU 4 , Y 181 QRPNO MATRIX H.6,6 *FOR COLUMNS CORRESPOND MATRIX SAVEVALUE FOR EACH BLOCK BOOKED SERVICE ( 2 - 6 ) . TO MONDAY THROUGH FRIDAY. THE ROWS ARE: 1 NEXT DAY - I N I T I A L I Z E 2 OUTPATIENTS FOR WEEK 1 3 TIME FOR WEEK 1 4 OUTPATIENTS FOR WEEK 2 13 TIME FOR WEEK 6 NOTE: WEEKS ARE ON A CYCLE. I N I T I A L L Y OTH WEEK I S WEEK 1. THEN 2 . . . *FOR EENT SLATE EENSL EOU 9,Y EENSL MATRIX H,13,5 ORPSL EOU 10,Y ORPSL M&TRIX H,13,5 *FOR ORTHOPEDIC SLATE I N I T I A L MH9-MH10I1.1 I.2/MH9-MH10II,2) ,3/MH9-MH10(I,31,4 I N I T I A L MH9-MH10I 1,4),5/MH9-MH10I1 ,5) ,6 • ALLOW AT MOST THREE ALTERNATE BE C AREAS FOR EMERGENCY PATIENTS. THE ROW CORRESPONDS TO THE PATIENT'S S E R V I C E . THE NUMBER » INSERTED CORRESPONDS TO THE ALTERNATE AREA. COLUMNS ARE USED IN < REVERSE ORDER. 0 INDICATES NO OPTION. (EG. ROW 4...0RTH0, MAY TRY S E R V I C E 3'S BEDS...EENT, OR THE SERVICE 2 BEDS.. .ORTHO). ALTER EOU ALTER MATRIX I N I T I A L I N I T I A L 14, Y H.7,3 *ROWS AS SERVICES MH 1 4 ( 1 , 1 ) , 2 / M j S 1 4 ( l , 2 ) , 4 / M H l 4 ( l , 3 ) , 3 M H 1 4 ( 3 , 2 ) , 2 / M H i 4 ( 3 , 3 ) , 4 / M H 1 4 ( 4 , 2 ) , 2 / M H l 4 ( 4 , 3 l . 3 •COUNTS NUMBER OF CANCELLATIONS CANCL EOU 13,H * OAY TO CHECK FOR OPEN SPOTS ON SLATE CHECK EOU l.H CHKDR EOU CHKTM EOU E"ARP. EOU EMBED EOU EMGNO EOU 5, H 6, H 14,H 1 1 , H 33,H •DOCTOR TO CHECK • SURGERY TIME TO. CHECK FOR •COUNTS EMERG AND D.U. ARRIVALS TODAY •TRACKS EMERGENCY BEDS I N USE •EMERGENCY NUMBER OPERATED O 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 24 9 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 2 74 275 276 277 278 2 79 280 281 E HG TM EOU 32,H E0 D N 0 EOU 23,H EOPTM EOU 22,H GCPTM EOU 20,H MAOIS EOU 40.H MOATE EOU 7,H MOGEN EOU 38,H MEMRN EOU 41,H MLOSG EOU 9.H MLOST EOU 8,H MSRVC EOU 34,H NORD EOU 12,H NOWTM EOU 37,H OCPNO EOU 25,H OOPTM EOU 24,H PTFWK EOU 35,H PWEEK EOU 3.H SHIFT EOU 39,H TMFWK EOU * WHICH OF USRSL EOU * WEEK TO CHECK WEEK EOU INITIAL T H E • EMERGENCY OPERATING TIME • EENT NUMBER OPERATED •EENT OPERATING TIME •GENERAL SURGERY OPERATING TIME •MEDICAL AREA DISCHARGES • ADMISSION (OR ANOTHER) DATE TO MATCH • DATE GENERATED TO MATCH • MEDICAL EMGOU IN MORNING •LENGTH OF SURGERY TO MATCH • LENGTH OF STAY TO MATCH •SERVICE TO MATCH • COUNTS NUMBER OF 'NO BEDS' •TIME USED BEFORE A BUMP • ORTHOPEOICS NUMBER OPERATED •ORTHOPEDICS OPERATING TIME • ROW OF PTS FCR THE APPROPRIATE WEEK • FIRST DAY OF PRESENT WEEK (SUNDAY) •IDENTIFIES OAY OR NIGHT-SHIFT FUNCTION •ROW OF TIME FOR THE APPROPRIATE WEEK (POINTER FOR SLATES AND CHAINS) 36,H 6 WEEKS IS THE NEXT 4,H FOR OPEN SPOTS ON SLATE 2»H •TAKES VALUES FROM 0 XHSPWEEK,1/XHSUSRSL,1 ********************* BOOLEAN VARIABLES BTIME BVARIABLE VtVTIME'LE'FN241 * ENUF TIME IF THIS ONE SUBSTITUTED? 8UMPE BVARIABLE P5 • E • XH.tCHKDR* P6 • E ' 5*8 V$BTI ME *T0 BUMP ELECTIVE OF THIS OR BUMPS BVARIABLE P5 ' E•XHSCHKDR*P6•E'4*BVSBTIME *T0 BUMP SEMIURGENT. THIS DR • TO MATCH PATIENT ON DISCHARGE CHAIN MACHO BVARIABLE BV tMAC HS4P2' E' XH$M DG EN̂ P 3 ' E 'XHSMOA TE+P9'E • XH $HLO ST • TO MATCH TRANSACTION ON ADMISSION CHAIN OR SURGERY CHAIN M AC HR BVARIABLE BV*MACHD*P11'E'XHtMLOSG MACHS BVARIABLE PI•E'XHSMSRVC *USEO IN THE ABOVE SIXWK BVARIABLE (P4'LE'XH$MDATE) •THESE OPNS IN NEW 6TH WEEK TRY'lA BVARIABLE P 13 • LE'F N240̂ P 14'LE • FN 241 *PTS AND TIME OK THIS DAY? WKENO BVARIABLE V$WKDAY*E'6*V$WKDAY'E'0 •TODAY FRICAY OR SATURDAY? *********** • VARIABLES A O I S T APRWK r. TPRI CWFEK OAS AM DSTRO ENDWK HI T B L HLONG LDI ST LOSO LOSOS M0D6 MOFF MSPAC NOFF O F F S L VARIABLE VAR IABLE VARIABLE VA R I A B L E VARIABLE VARIABLE VAR IABLE VARIABLE VARIABLE VARIABLE VARIABLE VARIABLE VARIABLE VAR IABLE VARIABLE VARIABLE VARIABLE 38»P1^2*P7 * IDENTIFIES SERVICE/SEX AGE DIST FUNCTION l(XH$USRSL+XH$WEEK-l)a6+l)^2 •IDENTIFY APPR WEEK ON MATRIX 22-P6 'PRIORITIES U:19 SU:18 EL:17 IXH$CHECK-XH$PWEEK)/7 •NUMBER OF WEEKS TO CHECK DATE (XH*CHECK-P14)a7 145«-PI*5»P6 P13-XH *PWEEK-5 P1̂ 2-2 ( P13-P2I/7 45+P1̂ 5+P8 37*P1*3 37+Pl»3+P7 XH*USRSL36+1 47+P14 Rl-3 P2-R*l Pl*6 •NEW DR REALLY ON SAME DAY? •SERVICE/CATEGORY FUNCTION OF DAYS TO REO •IS DATE IN P13 ON WEEKEND? •NUMBER OF THE HIGHEST OPERATIONS TABLE •NUMBER OF WEEKS WAITED FOR OPERATION •IDENTIFIES SERVICE/AGE LOS DIST FUNCTION •IDENTIFIES SERVICE'S LOS OUEUE •IDENTIFIES SERVICE/SEX LOS OUEUE • IDENTIFY NEW WEEK 0 SLATES •IDENTIFIES MED-OFF-SERVICE CHAIN • NUM3ER OF BEDS FOR MED SCHEOS •NUMBER TO PUT BACK ON SERVICE •OFFSET TO SLATE MATRIX BY SERVICE O 282 SD! ST VARIABLE 2 4 5 * P l * 5 t P 8 • IDENTIFIES SERVICE/AGE L OF SURGERY 283 SEUSC VAR IA9LE ( P l - 2 ) * 7 * 7 *FOR 'SLATE END' CHAIN, BY SERVICE 284 SGYOW VARIABLE 198-P1 • SERVICE FUNCTION FOR SURGERY DOW 285 stusr. VARIABLE (Pl-2)*7+(XH$WEEKtXH*USPSL-l!36«-l *SLATE CHAIN TO USE BY WEEK 2 86 SRVOP VARIABLE 16+Pl*2 • SAVEVALUES OF OPN STATS BY SERVICE 287 TRYDR VARIABLE (P13-P14I37 •DESIRED DAY AND DOCTOR'S DAY CORRESPOND? 288 VTIME VARIABLE XHtNOWTM-Pll+XHtCHKTM *TI ME AFTER SUBSTITUTING 289 WAITO VAR IABLE I P1-1»*5*P6 • IDENTIFIES SERVICE/CATEGORY WAIT QUEUE 290 WKDAY VARIABLE P3-XH SPWEEK+I •DAY-OF-THE-WEEK (TOMORROW! 291 WRONG VARIABLE 53*(P1*8)*P14 * INDICATES WRONG AREA QUEUE 292 *************************************** 293 • QUEUES AND OTABLES 294 *************************************** 295 * 296 * FOR WAITS 297 WMEOU EOU 3,0 •MEDICAL URGENT 298 WMEOS EOU 4,0 •MEDICAL SEMI -URGENT 299 WMFOE EOU 5,0 •MEDICAL ELECTIVE 300 WTU1 QTABLE WMEOU.0,2,23 301 WTSl OTABLE WMEDS.O, 2,23 302 WTFl OTABLE WMEOE.0,2.23 303 WEENU EOU 13.0 •EENT URGENT 304 WEENS EOU 14,0 •EENT SEMI-URGENT 305 WEENE EOU 15,0 •EENT ELECTIVE 306 WTU3 OTABLE WEENU,0,2,24 307 WT S3 OTABLE WEENS.0.2.30 308 WTE3 OTARLE WEENE.0.2.37 309 WORPH EOU 18,0 • ORTHOPEDICS URGENT 310 WORPS EOU 19,0 • ORTHOPEDICS SEMI-URGENT 311 WORPE EOU 20.0 •ORTHOPEDICS ELECTIVE 312 WTU4 OTABLE WORPU.0,2,19 313 ' WTS4 OTABLE WORPS,0,2.23 314 WTE4 OTABLE WOP.PE.0.2,27 315 * LENGTH OF STAY 316 LOS ME EOU 40.0 • MEDI CINE 317 • L OSMM EOU 41,0 • MEDICINE MALES 318 LCSMF EOU 42,0 •MEDICINE FEMALES 319 STAI OTABLE L0S«E,0.3,32 320 LCSEE EOU 46,0 •EENT 321 LOSEM EOU 47,0 • EENT MALES 322 LOSEF EOU 48,0 •EENT FEMALES 323 STA 3 OTABLE LOSEE.0.3,17 324 LOSOR E 01.1 49,0 • ORTHOPEDICS 325 LOSOM EOU 50,0 • ORTHOPEDICS MALES 326 LOSOF EOU 51,0 •ORThOPEDICS FEMALES 327 STA4 OTABLE LOSOR.0,3,32 328 * WRONG AREA 329 MINO EOU 61,0 •MEDICALS IN EMERG 330 MIN2 EOU 63,0 •MEDICALS IN GSG ETC. 331 MIN3 EOU 64.0 •MEDICALS IN EENT 332 MIN4 EOU 65,0 •MEOI CALS IN ORTHO 333 EINO EOU 77.0 •EENTS IN EMERG 334 EIN2 EOU 79,0 •EENTS IN GSG ETC. 335 EIN4 EOU 81.0 • EENTS IN ORTHC 336 OINO EOU 85,0 •ORTHOS IN EMERG 337 0IN2 EOU 87, 0 • ORTHOS IN GSG ETC. 338 0IN3 EOU 88,0 •CRTHOS IN EE NT 339 ******************************** *******. 340 • OTHER TABLES 341 *************************************** 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 389 39C 391 392 393 394 395 396 397 398 399 400 401 ' OPERATIONS STATISTICS GSGSN EOU l.T •GENERAL SURGERY NUMBERS GSG ST EOU 2.T •GENERAL SURGERY TIME EENSN EOU 3,T •EENT NUMBERS EENST EOU 4.T •EENT TIME EENSN TABLE XHiEOPNO.0,1,11 EENST TABLE XHJ.EOPTM, 0,60, 18 ORPSN EQU 5.T •ORTHOPEDIC NUMBERS ORPST EOU 6.T •ORTHOPEDIC TIPE ORPSN TABLE XH$OOPNO,0, 1,11 ORPST TABLE XH»00PTM,0,60,12 EMTBN EOU 35,T * EMERGENGY NUMBERS CMTRT EOU 36.T • EMERGENGY TIME EWT8N TABLE XH$EMGNO,0,1,15 EMTBT TABLE XH t EMGTM , 0, 30, 22 EMERGENCY AND DIRECT URGENT ARRIVALS EMGOU EOU 37,T EMGOU TABLE XHtEMARR.O, 1,32 •NO BEO' OCCURANCES NO BED EOU 38,T NOREO TABLE XHtNOBO.O, 1,22 *•«*««**•******««**«**««*«***«*«*«***** • USER CHAINS •*••*•**•*•*••••****•*•••*********••*•• 368 AOMMC EOU 46,C • MEDICAL ADMISSIONS 36 9 AO«SC EOU 43, C •SURGERY ADMISSIONS 370 DISCH EOU 47,C •01 SCHARGE CHAIN 371 EMRGC EOU 48,C •EMERGENCY OPERATIONS CHAIN 372 MA L T3 EOU 50.C •MEDICAL PATIENTS IN AREA 3 373 MALT4 FOU 51,C • MEDICAL PATIENTS IN AREA 4 3 74 SLEEN EOU 14.C • EENT END SLATE 375 SLFW1 EOU 8.C •EENT WEEK 1 SLATE 376 SLEW2 EOU 9,C •EENT WEEK 2 SLATE 377 SLEW3 EOU 10,C •EENT WEEK 3 SLATE 378 SLEW4 EOU 11.C •EENT WEEK 4 SLATE 379 S L EW5 EOU 12, C •EENT WEEK 5 SLATE 380 SLEW6 EOU 13,C •EENT WEEK 6 SLATE 381 SLOEN EOU 21.C •ORTHO END SLATE 382 SLOWl EOU 15,C •ORTHO WEEK 1 SLATE 393 SL0W2 EOU 16,C •ORTHO WEEK 2 SLATE 384 SLOW 3 EOU 17, C •CRTHO WEEK 3 SLATE 385 SL0W4 EOU 18,C •ORTHO WEEK 4 SLATE 336 SL0W5 EOU 19,C • CRTHO WEEK 5 SLATE 387 SL0W6 EOU 20,C • ORTHO WEEK 6 SLATE 388 XFFRC EOU 49 ,C •TRANSFERS' CHAIN ********* *********************** «**•**. • STORAGES *************************************** * • BEDS PER SERVICE STORAGE SI,165/S2,100/S3,35/S4,75 • FUNCTIONS • • • • • • • • • • • • • • • • • • f t * * * * * * * * * * * * * * * * * * * * • DAILY PATIENT ARRIVAL DISTRIBUTIONS ARNON FUNCTION P1.E3 1,FNJANMED/3,FNtANEEN/4,FNSANORP • NON-SCHEDULABLE' ARRIVALS BY SERVICE O _ •SCHEDULABLE ARRIVALS BY SERVICE 402 ARSCH FUNCTION P 1 . E 3 403 1 , F N * A S M E D / 3 , F N * A S E E N / 4 , F N t A S O R P 404 AN«EO FUNCTION R N 2 . 0 1 6 • MF DI C l NE N0N-SCHEDULA8LE 405 . 0 2 0 , 6 / . 0 6 3 . 7 / . 1 3 6 , 8 / . 2 3 5 . 9 / . 3 5 0 , 1 0 / . 4 6 6 , U / . 5 7 3 . 1 2 / . 6 6 5 , 1 3 / . 7 4 4 , 1 4 406 . 8 1 3 , 1 5 / . 8 7 4 , 1 6 / . 9 2 4 , 1 7 / . 9 6 1 , 1 8 / . 9 8 4 , 1 9 / . 9 9 6 , 2 0 / 1 , 2 1 407 . ANEEN FUNCTION RN3.D5 *EENT NON-SCHECULABLE 408 . 6 1 6 , 0 / . 9 0 7 , 1 / . 9 5 9 , 2 / . 9 3 9 , 3 / 1 . 4 409 ANORP FUNCTION RN4.D7 *0RTHOPEDIC NON-SCHEDULABLE 410 . 1 6 2 , 0 / . 3 2 4 , I / . 5 6 8 , 2 / . 7 5 7 , 3 / . 9 1 9 , 4 / . 9 7 3 , 5 / 1 . 6 411 ASMED FUNCTION RN2.D9 *MEDICAL SCHEDULABLE 412 . 2 0 5 , 0 / . 2 2 0 , I / . 2 4 5 , 2 1 . 3 1 0 . 3 / . 4 7 5 , 4 / . 7 2 5 . 5 / . 8 9 0 , 6 / . 9 6 0 . 7 / 1 . 8 413 ASEEN FUNCTION R N 3 . 0 9 *EENT SCHEDULABLE 414 . 3 13, 0 / . 3 76 , 2 / . 4 51 , 3 / . 52 8 , 4 / . 6 19 , 5 / . 7 1 2 . 6 / . 8 19, 7 / . 9 4 0 , 8 / 1 . 9 415 ASORP FUNCTION RN4.06 *ORTHOPEDIC SCHEDULABLE 416 . 2 8 6 , 0 / . 3 1 4 , 1 / . 4 2 9 , 2 1 . 6 5 7 . 3 / . 8 2 9 , 4 / 1 , 5 417 * NUMBER OF OOCTOPS PER S E R V I C E 418 1 FUNCTION RN2 .C2 * S A Y 22 MEDICAL DOCTORS, EOUAL USAGE 419 0 , 1 / 1 .23 420 3 FUNCTION RN3.C2 * SAY 10 EENT COCTORS, EOUAL USAGE 421 0 , 1 / 1 , 1 1 422 4 FUNCTION RN4.C2 • 9 ORTHOPEOIC DOCTORS, EOUAL USAGE 423 0 , 1 / 1 , 1 0 424 * PATIENT DIAGNOSTIC CATEGORY DISTRIBUTIONS 425 10 FUNCTION PI , E 3 • SELECT S E R V I C E ' S FUNCTION 426 I . F N U / 3 . F N 1 3 / 4 , FN14 427 11 FUNCTION RN2.D2 •MEDICINE 428 . 8 0 0 , 1 / 1 , 2 429 13 FUNCTION RN3 .02 • E E N T 430 . 7 8 8 . 1 / 1 , 2 431 14 FUNCTION RN4.D2 •CRTHOPEDICS 432 . 7 5 9 , 1 /1 , 7 433 20 FUNCTION PI . E 3 • S E L E C T S E R V I C E ' S FUNCTION 434 1 . F N 2 1 / 3 . F N 2 3 / 4 , FN24 435 21 FUNCTION RN2 .03 •MEDICINE 436 . 4 1 4 , 3 / . 5 8 5 , 4 / 1 , 5 437 23 FUNCTION RN3.D3 • EENT 438 . 0 3 3 , 3 / . 0 6 6 , 4 / 1 , 5 439 24 FUNCTION RN4.03 •ORTHOPEDICS 440 . 0 2 0 , 3 / . 217 , 4 / 1 , 5 441 * PATIENT SEX 442 30 FUNCTION P 1 . E 3 • • S E L E C T SERVICE 443 1 . F N 3 1 / 3 , F N 3 3 / 4 , FN 34 444 31 FUNCTION RN2,D2 •MEDICINE PROPORTIONS IN SEXES 445 . 5 6 5 , 1 / 1 , 2 446 33 FUNCTION RN3.D2 • E E N T PROPORTIONS IN SEXES 447 . 5 0 0 , 1 / 1 , 2 448 34 FUNCTION RN4,D2 • ORTHO PROPORTIONS IN SEXES 449 . 5 3 5 , 1 / 1 , 2 450 * PATIENT AGE GROUP 451 41 FUNCTION RN2.D5 452 . 0 C 8 . 1 / . 1 4 3 , 2 / . 4 4 5 . 3 / . 8 4 0 . 4 / 1 , 5 453 42 FUNCTION RN2 .05 454 . 0 0 8 . I / . 1 8 5 . 2 / . 4 0 1 , 3 / . 7 4 3 . 4 / 1 , 5 455 45 FUNCTION RN3.05 456 . 0 2 5 . 1 / . 4 2 1 , 2 / . 6 9 6 , 3 / . 9 2 2 . 4 / 1 . 5 457 46 FUNCTION RN3.D5 458 . 0 2 5 , 1 / . 3 5 9 , 2 / . 5 6 7 , 3 / . 8 5 3 , 4 / 1 , 5 459 4 7 FUNCTION RN4.D5 460 . 0 2 , l / . 4 5 . 2 / . 7 8 , 3 / . 9 6 , 4 / l , 5 461 48 FUNCTION RN4.D5 •MEDICINE MALE AGE GROUP PROPORTIONS • MEDICINE FEMALE AGE GROUP PROPORTIONS • EENT MALE AGE GROUP PROPORTIONS •EENT FEMALE AGE GROUP PROPORTIONS •ORTHO MALE AGE GROUP PROPORTIONS •ORTHO FEMALE AGE GROUP PROPORTIONS O 4 6 ? . 0 2 , 1 / . 3 2 , 2 / . 5 2 5 , 3 / . 8 1 5 , 4 / 1 , 5 4 6 3 * P A T I E N T L E N G T H OF S T A Y D I S T R I B U T I O N S 4 6 4 5 1 F U N C T I O N R N 2 . C 1 7 * M E D I C I N E 1 S T A G E G R O U P 4 6 5 0 , II. 1 2 1 . 2 / . 3 9 1 , 4 / . 6 0 0 , 6 / . 7 3 7 , 8 / . 8 1 9 ,1 0 / . 8 7 4 , 1 2 / . 9 3 3 . 1 6 / . 9 5 8 , 2 0 / . 9 7 1 . 2 4 4 6 6 . 9 8 4 , 3 2 / . 9 9 1 , 4 0 / . 9 9 4 , 4 8 / . 9 9 7 , 6 4 / . 9 9 8 , 8 0 / . 9 9 1 , 9 6 / 1 , 1 2 8 4 6 7 5 2 F U N C T I O N R N 2 . C 1 7 * M E C ! C I N E 2ND A G E G R O U P 4 6 8 0 , I / . 1 2 5 , 2 / . 3 8 8 , 4 / . 5 9 1 , 6 / . 71 7 , 8 / . 7 9 9 , 1 0 / . 8 5 2 . 1 2 / . 9 11 , 1 6 / . 9 4 2 , 2 0 / . 9 6 0 . 2 4 4 6 9 . 9 7 9 , 3 2 / . 9 8 7 , 4 0 / . 9 9 2 , 4 8 / . 9 9 5 , 6 4 / . 9 9 7 , 8 0 / . 9 9 8 , 9 6 / l . 1 2 8 4 7 0 5 3 F U N C T I O N R N 2 . C 1 7 * M E C I C I N E 3RD A G E GROUP 4 7 1 0 , 1 / . C 0 7 , 2 / . 33 0 , 4 / . 4 9 2 , 6 / . 6 1 7 , 8 / . 7 0 4 , 1 0 / . 7 6 8 . 1 2 / . 8 5 5 , 1 6 / . 9 0 9 , 2 0 / . 9 3 2 , 2 4 4 7 2 . 9 6 5 , 3 2 / . 9 3 0 , 4 0 / . 9 8 8 , 4 8 / . 9 9 5 , 6 4 / . 9 9 8 , 8 0 / . 9 9 9 . 9 6 / 1 , 1 2 8 4 7 3 5 4 F U N C T I O N R N 2 . C 1 7 * M E D I C I N E 4 T H A G E G R O U P 4 7 4 0 , 1 / . 0 0 5 , 2 / . 1 8 2 , 4 / . 3 2 7 , 6 / . 4 3 0 , 8 / . 5 5 0 , 1 0 / . 1 3 0 , 1 2 / . 7 4 2 , 1 6 / . 8 1 8 , 2 0 / . 8 7 8 . 2 4 4 7 5 . 9 2 6 , 3 2 / . 9 5 6 . 4 0 / . 9 7 3 . 4 8 / . 9 8 5 , 6 4 / . 9 9 1 , 8 0 / . 9 9 4 . 9 6 / 1 , 1 2 8 4 7 6 5 5 F U N C T I O N R N 2 . C 1 7 * M E D I C I N E 5 T H A G E G R O U P 4 7 7 0 , I / . 0 0 5 , 2 / . 11 0 , 4 / . 1 9 6 , 6 / . 2 9 1 , 8 / . 4 0 5 , 1 0 / . 4 8 7 , 1 2 / . 6 1 3 , 1 6 / . 701 , 2 0 / . 7 7 0 . 2 4 4 7 8 . 8 5 2 , 3 2 / . 9 G 0 , 4 0 / . 9 3 5 , 4 8 / . 9 6 0 , 6 4 / . 9 7 5 . 8 0 / . 9 8 4 , 9 6 / 1 , 1 2 8 4 7 9 6 1 F U N C T I O N R N 3 . C 1 5 + E E N T 1 S T A G E G R O U P 4 8 0 0 , I / . 0 7 3 , 2 / . 8 5 1 , 4 / . 9 2 0 . 6 / . 9 4 9 , 8 / . 9 6 7 , 1 0 / . 9 7 4 , 1 2 / . 9 8 6 , 1 6 / . 9 9 0 , 2 0 / . 9 9 3 , 2 4 4 8 1 . 9 9 5 , 3 2 / . 9 9 7 , 4 0 / . 9 9 3 , 4 8 / . 9 9 9 , 6 4 / 1 , 8 0 4 8 2 6 2 F U N C T I O N R N 3 . C 1 3 * E E N T 2 N D A G E G R O U P 4 3 3 0 , 1 / . 0 2 5 , 2 / . 5 6 0 , 4 / . 8 7 0 . 6 / . 9 5 7 . 8 / . 9 8 0 , 1 0 / . 9 8 9 , 1 2 / . 9 9 4 , 1 6 / . 9 9 6 , 2 0 / . 9 9 7 , 2 4 4 8 4 . 9 9 8 , 3 2 / . 9 9 9 , 4 0 / 1 . 8 0 4 8 5 6 3 F U N C T I O N R N 3 . C 1 2 * E E N T 3 R D A G E G R O U P 4 8 6 0 , 1 / . 0 3 2 , 2 / . 4 0 5 , 4 / . 7 1 2 , 6 / . 8 6 3 , 8 / . 9 2 5 , 1 0 / . 9 5 6 , 1 2 / . 9 8 2 , 1 6 / . 9 9 2 , 2 0 / . 9 9 6 , 2 4 4 8 7 . 9 9 9 , 3 2 / 1 . 4 0 4 8 8 6 4 F U N C T I O N R N 3 . C 1 5 * E E N T 4 T H A G E G R O U P 4 8 9 0 , 1 / . 0 1 4 , 2 / . 2 5 1 , 4 / . 5 6 1 , 6 / . 7 5 1 , 8 / . 8 5 1 , 1 0 / . 9 1 2 , 1 2 / . 9 5 7 , 1 6 / . 9 7 2 , 2 0 / . 9 8 1 , 2 4 4 9 0 . 9 9 0 , 3 2 / . 9 9 4 , 4 0 / . 9 9 6 , 4 8 / . 9 9 7 , 6 4 / 1 , 8 0 4 9 1 6 5 F U N C T I O N R N 3 . C 1 5 * E E N T 5 T H A G E G R O U P 4 9 ? 0 , 1 / . 0 1 8 , 2 / . 13 6 , 4 / . 4 4 0 , 8 / . 6 9 8 , 8 / . 8 4 0 , 1 0 / . 9 14 , 1 2 / . 9 6 9 , 1 6 / . 9 8 2 , 2 0 / . 9 8 9 , 2 4 4 9 3 . 9 9 4 , 3 2 / . 9 9 6 , 4 0 / . 9 9 7 , 4 8 / . 9 9 8 , 6 4 / 1 , 8 0 4 9 4 6 6 F U N C T I O N R N 4 . C 1 4 * O R T H O 1 S T A G E G R O U P 4 9 5 0 , 1 / . 1 2 2 , 2 / . 4 1 8 . 4 / . 5 6 8 , 6 / . 6 7 9 , 8 / . 7 3 7 , 1 0 / . 7 8 I . 1 2 / . 8 4 4 , 1 6 / . 9 1 3 , 2 0 / . 9 5 2 . 2 4 4 9 6 . 9 8 3 , 3 2 / . 9 9 3 , 4 0 / . 9 9 7 , 4 8 / 1 , 6 4 4 9 7 6 7 F U N C T I O N R N 4 . C 1 7 * O R T H O 2 N D A G E G R O U P 4 9 8 0 , 1 / . 0 3 7 . 2 / . 2 4 8 , 4 / . 5 2 4 , 6 / . 7 2 0 , 8 / . 7 9 6 , 1 0 / . 8 4 5 , 1 2 / . 9 0 5 , 1 6 / . 9 2 6 . 2 0 / . 9 4 0 , 2 4 4 9 9 . 9 5 7 , 3 2 / . 9 7 2 , 4 0 / . 9 8 1 , 4 8 / . 9 8 9 , 6 4 / . 9 9 4 , 8 0 / . 9 9 6 . 9 6 / 1 . 1 2 8 5 0 0 6 8 F U N C T I O N R N 4 . C 1 7 * 0 R T I I O 3 R D A G E GROUP 5 0 1 0 , 1 / . 0 2 8 , 2 / . 1 8 7 . 4 / . 3 7 0 , 6 / . 5 3 2 . 8 / . 6 2 0 , 1 0 / . 6 8 7 , 1 2 / . 7 8 3 , 1 6 / . 8 5 2 , 2 0 / . 8 8 9 , 2 4 5 02 . 9 4 4 , 3 2 / . 9 6 6 , 4 0 / . 9 7 7 , 4 8 / . 9 8 9 , 6 4 / . 9 9 5 . 8 0 / . 9 9 7 . 9 6 / 1 , 1 2 8 5 0 3 6 9 F U N C T I O N R N 4 . C 1 7 " C R T H O 4 T H A G E G R O U P 5 0 4 0 , 1 / . 0 2 8 , 2 / . 1 7 3 , 4 / . 3 0 2 , 6 / . 4 0 6 , 8 / . 4 7 2 , 1 0 / . 5 2 3 , 1 2 / . 6 0 9 , 1 6 / . 701 , 2 0 / . 7 6 6 , 2 4 5 0 5 . 8 5 3 , 3 2 / . 9 0 6 , 4 0 / . 9 3 6 , 4 8 / . 9 7 0 , 6 4 / . 9 8 4 , 8 0 / . 9 9 0 . 9 6 / 1 , 128 5 0 6 7 0 F U N C T I O N R N 4 . C 1 7 * O R T H O 5 T H A G E G R O U P 5 0 7 0 , I / . 0 0 5 . 2 / . 0 3 5 , 4 / . 0 7 8 , 6 / . 1 3 0 , 8 / . 171 , I 0 / . 2 11 . 1 2 / . 2 8 5 . 1 6 / . 3 9 2 . 2 0 / . 4 8 5 , 2 4 5 0 8 . 6 3 0 , 3 2 / . 7 2 2 , 4 0 / . 7 9 0 , 4 8 / . 8 7 5 , 6 4 / . 9 2 4 , 8 0 / . 9 5 2 , 9 6 / 1 , 1 2 8 5 0 9 * P A T I E N T P R E O P E R A T I V E L O S 5 1 0 1 2 0 F U N C T I O N P I , E 2 * S P E C I F Y BY S E R V I C E 5 1 1 3 , 1 / 4 , 1 5 1 2 * T O O B T A I N F R A C T I O N O F P T S N O T A S S I G N E D A ' R E Q U E S T E D D A T E O F A D M I S S I O N " 5 1 3 1 4 0 F U N C T I O N P 1 . E 2 * S E L E C T S E R V I C E 5 1 4 3 . F N 1 4 3 / 4 . F N 1 4 4 5 1 5 1 4 3 F U N C T I O N P 6 . 0 3 * E E N T 5 1 6 3 , 5 0 0 / 4 , 1 0 0 / 5 , 3 0 0 5 1 7 1 4 4 F U N C T I O N P 6 . D 3 * O R T H O P E D I C S 5 1 8 3 , 5 0 / 4 , 1 0 0 / 5 , 7 5 0 . 5 1 9 * O A Y S T O R E Q U E S T E D A D M I S S I O N D A T E <FROM N E X T B L O C K E O S P O T FOR D R ) \Z 5 2 0 1 6 3 F U N C T I O N R N 1 . D 2 * E E N T U R G E N T S , _ 5 2 1 . 3 3 3 , 0 / 1 , 7 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 56? 563 564 565 566 567 568 569 570 571 572 5 73 5 74 575 576 577 57R 5 79 580 581 * EENT SEMI-URGENTS 164 FUNCTinN RN1.D2 . 3 3 3 . 0 / 1 ,7 165 FUNCTION R N l . D l l * EENT EL ECT IVES . 0 6 0 . 0 / . 3 6 0 , 7 / . 4 8 0 , 1 4 / . 6 4 0 , 2 1 / . 8 0 0 , 2 8 / . 8 8 0 , 3 5 / . 9 2 0 , 4 2 / . 9 4 0 , 4 9 / . 9 6 0 , 5 6 . 9 8 0 , 6 3 / 1 ,70 168 FUNCTION RN1.D3 •ORTHO URGENTS . 2 5 , 0 / . 7 5 , 7 / 1 , 14 169 FUNCTION P N l , D 7 *ORTHO SEMI-URGENTS . 1 , 0 / . 3 . 7 / . 5 . 1 4 / . 7 , 2 1 / . 8 , 2 8 / . 9 , 3 5 / I , 4 2 170 FUNCTION RN1.08 •ORTHO E L E C T I V E S . 1 , 0 / . 2 . 7 / . 5 . 1 4 / . 6 , 2 1 / . 7 . 2 8 / . 8 , 3 5 / . 9 , 4 2 / 1 , 49 * SURGERY DAYS OF THE WEEK BY DOCTOR 201 FUNCTION XH*CHKDR,D5 * EENT 2 , 1 / 4 , 2 / 6 . 3 / 8 , 4 / 1 0 , 5 202 FUNCTION XH$CHKDR,05 *ORTHOPEDICS 2 , 1 / 4 , 2 / 6 , 3 / 7 , 4 / 9 , 5 * FUNCTIONS TO DETERMINE HOW MANY QUEUED MEDICAL PATIENTS TO ADMIT 231 FUNCTION CHtA0MMC,E3 * FN DEPENDS ON MED OUEUE LENGTH 2 6 , F N 2 3 2 / 3 3 , F N 2 3 3 / 1 5 0 , F N 2 3 4 * NUMBERS ARE BASED ON REMAINING CAPACITY 232 FUNCTION R1 .D6 6 , C / 9 . 1 / 1 0 . 2 / 1 2 . 3 / 1 5 . 4 / 5 0 ,5 •SLOW IT DOWN • SUITABLE • S P E E D IT UP •MORNING RESERVE, OWN AREA • MORNING RESERVE, OTHER AREAS •NON-MORNING R E S E R V E , OWN AREA •NON-MORNING R E S E R V E . OTHER AREAS • A N Y MORE O F F - S E R V I C E CAUSE XFER 233 FUNCTION R 1 » D 6 6 , 0 / 8 , 3 / 1 0 , 4 / 1 2 , 5 / 1 5 , 6 / 5 0 . 7 234 FUNCTION R 1 . D 6 6 , 0 / 8 , 5 / 1 0 , 6 / 1 2 , 7 / 1 5 . 8 / 5 0 , 9 • FOR EMERGENCY PATIENTS 235 FUNCTION P 1 4 . D 4 1 , 8 / 2 , 0 / 3 . 4 / 4 . 3 736 FUNCTION P 1 4 . D 4 1 , 2 0 / 2 . 0 / 3 , 7 / 4 , 4 237 FUNCTION P t 4 , D 4 1 , 0 / 2 , 0 / 3 . 0 / 4 , 0 238 FUNCTION P 1 4 . 0 4 1 , 0 / 2 , 0 / 3 . 0 / 4 , 0 239 FUNCTION P 1 4 . 0 4 1 , 2 0 / 2 . 0 / 3 , 7 / 4 , 4 • SCHEDULED PATIENTS PERMITTED PER DAY BY SERVICE 240 FUNCTION P I , 0 2 3 , 9 / 4 , 5 • SCHEDULED TIME PERMITTED PER DAY BY SERVICE 241 FUNCTION PI ,02 •DEPENDS ON NUMBER CF O R ' S 3 , 8 4 0 / 4 , 4 2 0 • NUMBER BEFORE TURNAROUNDS (DEPENDS ON NUMBER OF O R ' S I 242 FUNCTION P I , 0 2 3 , 4 / 4 , 2 • DOCTORS PER SERVICE 243 FUNCTION P I , 0 3 1 , 2 2 / 3 , 1 0 / 4 . 9 • PROPORTION NOT CANCELLING FOR LONG WAIT 245 FUNCTION P 1 . D 2 3 . 9 9 0 / 4 , 5 0 0 • PROPORTION OF THOSE ADMITTED NOT GENERATING EMERGENCY OPERATIONS REQUESTS 247 FUNCTION P I , 0 2 3 , 9 3 4 / 4 , 8 3 8 • PROPORTION NOT GENERATING INHOSPITAL OPERATIONS REOUESTS 248 FUNCTION P I , 0 2 3 , 9 6 8 / 4 , 8 9 7 • PATIENT LENGTH OF SURGERY DISTRIBUTIONS 261 FUNCTION RNWDIO • E E N T 1ST AGE GROUP K5 582 . 1 1 1 . 3 0 / . 2 5 9 , 3 5 / . 4 4 4 , 4 0 / . 6 3 0 , 4 5 / . 7 7 8 , 5 0 / . 8 5 2 . 5 5 / . 8 8 9 , 6 0 / . 9 2 6 . 7 0 / . 9 6 3 , 9 0 583 1 ,110 584 262 FUNCTION R N 1 . 0 2 3 * EENT 2ND AGE GROUP 585 .0 51 ,2 5 / . 15 3 , 3 0 / . 271 , 3 5 / . 3 5 6 , 4 0 / . 4 2 4 , 4 5 / . 4 7 5 . 5 0 / . 5 2 5 . 5 5 / . 5 7 6 , 6 0 / . 6 1 0 . 6 5 586 . 6 4 4 , 7 0 / . 6 7 8 , 7 5 / . 7 1 2 , 8 0 / . 7 4 6 , 8 5 / . 7 8 0 , 9 0 / . 8 1 4 , 1 0 0 / . 8 4 7 , 1 1 0 / . 8 8 1 .120 587 . 9 1 5 , 1 3 0 / . 9 3 2 . 1 4 0 / . 9 4 9 , 1 5 0 / . 9 6 6 , 1 6 0 / . 9 8 3 , 1 7 0 / 1 , 200 588 263 FUNCTION R N 1 . 0 1 7 *EENT 3RD AGE GROUP 589 . 0 5 1 , 3 0 / . 1 0 3 , 4 0 / . 1 5 4 , 5 0 / . 2 0 5 , 5 5 / . 3 3 3 , 6 0 / . 4 1 0 . 6 5 / . 4 6 2 , 7 0 / . 5 9 0 . 7 5 / . 6 4 1 , 8 0 590 . 6 9 2 , 8 5 / . 7 4 4 , 9 0 / . 7 9 5 , 9 5 / . 8 2 1 , 1 0 0 / . 8 7 2 , 1 1 5 / . 9 2 3 , 1 3 0 / . 9 7 4 , 1 6 0 / 1 . 210 591 264 FUNCTION R N l . D l l *EENT 4TH AGE GROUP 592 . 0 4 2 , 2 5 / . 1 2 5 , 4 0 / . 2 5 0 , 5 0 / . 4 1 7 , 5 5 / . 5 8 3 , 6 0 / . 7 0 8 . 6 5 / . 7 9 2 , 7 0 / . 8 7 5 . 8 0 / . 9 1 7 , 9 0 593 . 9 5 8 , 1 0 0 / 1 , 1 2 0 594 265 FUNCTION R N 1 . 07 *EENT 5TH AGE GROUP 595 . 1 6 7 , 3 0 / . 3 3 3 . 4 5 / . 5 0 0 . 5 5 / . 6 6 7 , 6 0 / . 8 3 3 , 6 5 / . 9 1 7 , 7 0 / 1 . 8 0 596 266 FUNCTION RN1.D6 *CRTHO 1ST AGE GROUP 597 . 1 , 2 0 / . 2 , 3 0 / . 4 , 4 C / . 6 , 5 0 / . 9 , 6 0 / 1 , 70 598 267 FUNCTION RN1.Q14 *ORTMO 2ND AGE GROUP 599 . 0 9 7 . 3 0 / . 1 6 1 , 4 5 / . 2 9 0 . 5 0 / . 4 1 9 , 5 5 / . 5 1 6 , 6 0 / . 6 1 3 , 6 5 / . 6 7 7 , 7 0 / . 7 4 2 . 7 5 / . 7 7 4 . 8 0 600 . 8 3 9 , 9 0 / . 9 0 3 , 1 0 0 / . 9 3 5 , 1 1 0 / . 9 6 8 , 1 2 0 / 1 . 1 3 0 601 268 FUNCTION RN1.D17 *0RTHO 3RD AGE GROUP 602 . 0 6 8 , 1 5 / . 136, 3 0 / . 2 2 7 , 4 5 / . 3 1 8 , 5 0 / . 4 0 9 , 5 5 / . 5 0 0 , 6 0 / . 5 9 1 , 6 5 / . 6 8 2 , 7 0 / . 7 5 0 , 7 5 6 03 . 8 1 8 , 8 0 / . 8 6 4 . 9 0 / . 8 8 6 . 1 0 0 / . 9 0 9 . 1 1 5 / . 9 3 2 , 1 3 0 / . 9 5 5 , 1 4 5 / . 9 7 7 , 1 6 0 / 1 , 2 0 0 604 269 FUNCTION RN1.D12 *GFTHO 4TH AGE GROUP 605 . 0 3 3 , 3 0 / . 0 6 7, 4 0 / . 2 C , 4 5 / . 3 6 7 , 5 0 / . 4 3 3 , 6 0 / . 5 3 3 , 7 0 / . 6 0 0 , 8 0 / . 7 6 7 , 9 0 / . 8 3 3 , 1 0 0 606 . 9 0 0 , 1 2 0 / . 9 6 7 , 1 3 5 / 1 ,150 607 270 FUNCTION R N l . D l l *CRTHO 5TH AGE GROUP 6 08 . 07 I , 3 0 / . 1 4 3 , 4 5 / . 2 8 6 , 6 0 / . 3 5 7 , 7 5 / . 4 2 9 , 9 0 / . 5 7 1 , 1 0 5 / . 6 4 3 . 1 2 0 / . 7 1 4 , 1 3 0 609 . 8 5 7 , 1 4 0 / . 9 2 9 , 1 8 0 / 1 , 2 4 0 it, 10 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 611 * EXPLANATION OF G A R Y EVENT P R I O R I T I E S (,12 *«*****************+******************* 613 * 614 * THE SLATE-UPDATING 'BOOKKEEPER* IS HIGHEST PRIORITY - 2 1 . 615 * 616 * THE DETERMINATION OF ADMISSION REQUESTS TO APPEAR ON THIS DATE I S 617 * HIGHEST PRIORITY OF THE PATIENT-RELATED EVENTS INITIATED - 1 9 . 618 * A PATIENT BEING GIVEN CHARACTERISTICS AND BEING FILED IS RAISED 619 « TO PRIORITY 20 SO THAT IT IS DONE BEFORE WORKING ON ANOTHER. 620 * . 621 * DISCHARGES ARE SECOND PRIORITY - 16 622 * 1 623 * TRANSFERS ARE NEXT - 14 624 * 625 * MORNING EMERGENCIES ARE NEXT - 12 626 * 627 * THE AOMISSION PROCESSING FOR THIS CATE IS PRIORITY 10. ALL ADMITTED 628 * PATIENTS ARE CONSIOEREO I N GENERATING EMERGENCY AND INHOSPITAL OPERATIONS 629 * 630 * ALL NCN-MORNING EMERGENCIES COME THEN - 6 631 * 632 * OR DATA IS CALCULATED LAST - 2 633 * 634 * A TIMER TRANSACTION COMPLETES EACH DAY - PRIORITY 1 635 * 536 * * * * * * * * * * * * * * * » » . « » * » * * * * * * • . • * * « * . * . • • * « * 637 * TRANSACTION TO UPDATE SLATE F I L E EACH WEEKENO 638 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 639 GENERATE 1 . . . 1 , 2 1 . 2 *GENERATE SINGLE ENTITY AS BOOKKEEPER 640 SUN ASSIGN 2 . 6 *SET PARAMETER 2 TO LOOP T I L L SATURDAY 641 DAY ADVANCE 1 * L E T DAY PASS 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 638 689 690 691 692 693 694 695 696 697 698 699 700 701 LOOP 2,CAY FIRST THING EACH SATURDAY MSAVEVALUE 9-1 0* 11.1-5 .7 , NH 1,VtM006 USRSL,PI,H WEEK,5,H PTFWK.VtAPRWK.H TMFWK,XH$PTFWK,H TMFWK+ , 1 ,H •DECREMENT P2 (UNTIL 0) AND GO TO DAY ASSIGN SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE • ADD 1 WEEK TO NEXT SURGERY DATES •ADD 1 MOD 6 TO XHSUSRSL VIA PI •RESET XHtUSRSL •HENCE, WORKING 5 WEEKS AWAY •IDENTIFY ROW FOR APPROPRIATE WEEK'S PTS •SET THIS THE SAME — _. •APPROPRIATE WEEK'S TIME IS I ROW LATER MSAVEVALUE 9-10,XHtPTFWK,1-5,0,MH *FOR WHOLE WEEK, « PTS SET TO 0 MSAVEVALUE 9-10,XHiTMFWK,1-5,0,MH *FOR WHOLE WEEK.TIME SET TO 0 SAVEVALUE MDATE. XH$PWEEK ,H •FIRST DAY OF PRESENT WEEK TO MDATE MDATE*,47,H •FRIDAY OF WEEK TO BE BROUGHT IN 1,4 •P1=HIGHEST SERVICE P1.2.NDAY •DON'T 00 SERVICE 2 VtSEUSC,ONFIL,ALL,BV$SIXWK •UNLINK THAT WEEK TO FILE l.TOMOV •DECREMENT SERVICE NUMBER AND REPEAT PWEE K* ,7 ,H •FIRST DAY OF NEW SLATE WEEK 1 •OVER SATURDAY ,SUN 'ANOTHER WEEK...GO TO SUNDAY SAVEVALUE ASS IGN TCMOV TEST NE UNLINK LOOP NDAY SAVEVALUE ADVANCE TRANSFER • BRINGING APPROPRIATE PART OF END CHAIN TO 5TH WEEK CHAIN ONFIL SAVEVALUE SAVEVALUE ASSIGN SAVEVALUE SAVEVALUE SAVEVALUE CHKDR,P5,H WEEK,5,H 15,1,V$SGYDW PTFWK.VtAPRWK.H TMFWK,XHtPTFWK.H TMFWK*,1,H •DOCTOR TO CHECK FOR THIS PATIENT • WORK ING 5 WEEKS AWAY • P15=DAY OF WEEK FOR THAT OOCTOR •IDENTIFY ROW FOR APPROPRIATE WEEK'S PTS • SET THIS THE SAME •APPROPRIATE WEEK'S TIME IS I ROW LATER IS THERE SPACE CN THAT DAY? ASSIGN ASSIGN ASSIGN ASSIGN TEST NE MARK TEST GE TRANSFER SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE UMLINK TRANSFER OFFFO DEPART TRANSFER NLONG SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE SAVEVALUE UNLINK ASSIGN ASSIGN LINK ASSIGN ASSIGN LINK 13, MH*V$OFFSL(XH$PTFWK,P15 I •P13 = PTS FOR DATE BEING CHECKED 13*, 1 •P13=PTS IF THIS ONE ADDED 14, MH*V$0FFSL(XH$TMFWK,P15 I *P14=TIME FOR DATE BEING CHECKED 14*,P11 BV$TRYDA,1,DAYES 13 V IHLONG,7,NLONG .FN245,,NLONG CANCL*,l,H MSRVC.P1.H M0GEN.P2 ,H MDATE,P3,H ML0ST,P9,H MLOSG.Pll.H • P14=TIME IF THIS ONE ADDED •TES1ING FOR SPACE •NO SPACE, MARK PRESENT DAY •WAITED OVER 7 WEEKS UNSUCCESSFULLY? •YES, MANY CANCEL • ONE MORE • WANT SERVICE TO MATCH •WANT DATE GENERATED TO MATCH •WANT ADM DATE TO MATCH • ALSO MATCH LENGTH OF STAY _ * AL SO MATCH LENGTH OF SURGERY ADMSC. OFFFQ. I . BV SMACHR * « FA ILD *TAKE OFF ADM CHAIN .DSPOS * REMOVE FROM MODEL : VtWAITQ * BETTER TAKE FROM WAIT QUEUE ,DSPOS *R EMOVE FROM MOOEL MDATE.P3..H *NOT TOO LONG, ADM DATE TO MATCH MSRVC.Pl.H *WANT SERVICE TO MATCH MDGEN, P2 »H •WANT DATE GENERATED TO MATCH ML0ST.P9.H * AL SO MATCH LENGTH OF STAY MLOSG.Pll.H *ALSO MATCH LENGTH OF SURGERY ADMSC,UPWK,1.BVtMACHR,.FAILO *GET PT OFF ADM CHAIN 3*,7 *ADD 1 WEEK TC ADMISSION DATE 4*,7 •ADD 1 WEEK TO SURGERY DATE V$SEUSC,6 •BACK ON SLATE END CHAIN 3*. 7 *AD0 1 WEEK TO ADM DATE 4*.7 *ADC 1 WEEK TO SURGERY DATE ADMSC i 3 *BAGK ON ADMISSION CHAIN • THERE IS SPACE FOR THESE OA YE S MSAVEVALUE VSOFFSL* , XHt PTFWK. PI 5 , 1. MH *ADD 1 TO PTS THAT WEEK/DOW/SERV ICE UPWK to 702 MSAVEVALUE VtOFFSL+.XHtTMFWK,PI 5.P11.MH *A00 SURGERY TIME SIMILARLY 703 TEST GE MH*V$OFFSL(XH$PTFWK,PI 5 I,FN242,PUT1 * 2 * PTS PER OR SLATE07 70* MS AVEVALUE VtOFFSL +,XHtTMFWK,PI 5.15,MH *AOD TURNAROUND BEFORE NEXT PT 705 PUT1 LINK V*SLUSC,5 *PUT ON SLATE USER CHAIN 706 »***.*************»**********+*****.*** 707 * PATIENT GENERATION SECTION 70B ***•*»«*«»»*»**«*»•«*«********«***»«*** 70" * 710 * EACH DAY AN ENTITY IS GENERATED AN0 MARKED WITH THE TIME. 711 * IT IS THEN SPLIT INTO THE APPROPRIATE NUMBER OF PATIENTS FOR EACH SERVICE 712 * FOR THAT OAY. THESE PATIENTS HAVE PARAMETERS AS FOLLOWS! 713 * PI SERVICE AS FOLLOWS: 714 * 1-MEDICINE 715 * 2-GENERAL SURGERY 716 * 3-E.E.N.T. 717 * 4-0RTH0PEDICS 718 * P2 TIME I DAY) OF ADMISSION REOUEST 719 * P3 TIME OF ADMISSION 720 * P4 TIME OF (NEXT) OPERATION 721 * P5 NUMBER OF OOCTOR 722 * EG. 1-9 FOR ORTHOPEDICS 723 * P6 PATIENT DIAGNOSTIC CATEGORY: 724 * 1-EMERGENT 725 * 2-DIRECT URGENT 726 * 3-URGENT 727 * 4-SEMI-URGENT 728 * 5-ELECTIVE 729 * P7 SEX: 730 * 1-V6LE 731 * 2-FEMALE 732 * P8 AGE GROUP: 733 * 1- 0-14 734 * 2- 15-34 735 * 3- 35-54 736 * 4- 55-74 737 * 5- 75 OR ABOVE 738 * P9 LENGTH OF STAY 739 * P10 PRF-OPERATIVE LOS 740 * PI I LENGTH OF (NEXT) SURGERY 741 * P12 REQUESTED ADMISSION DATE (SURG.OATE FOR SURGICAL SERVICES) 742 * P13 WORK...FOR DISCHARGES OR TRANSFERS, TIME OF DISCHARGE 743 * P14 WORK...FOR TRANSFER AN 0 DISCHARGE PATIENTS, AREA IN 744 * P15 WORK 745 * 746 * 747 GENERATE 1,,,,19,15 *DAILY.FIRST THING DONE RE. PATIENTS 748 ASSIGN 1,4 *P1=HIGHEST HOSPITAL SERVICE 749 MARK 2 *P2=TIME OF ADMISSION REOUEST 750 REAL TEST NE P1.2.L00P1 . *OCN'T 00 SERVICE 2 751 SPLIT FNtARNCN,PTS1 *MAKE NON-SCHEDULABLE REOUESTS 752 SPLIT FNtARSCH.PTSZ * MAK E SCHEDULABLE REQUESTS 753 LOOPl LOOP I,REAL *DECREMENT SERVICE AND GO TO REAL 754 OUT TERMINATE *R EMOVE XACT GENERATING PTS FROM MODEL 755 * SEGMENT ASSIGNING CHARACTERISTICS TO PATIENTS 756 PTS1 ASSIGN 6.1,10 *P6=PT DIAGNOSTIC CATEGORY (VIA FN10) 757 TRANSFER .CHAR *G0 ASSIGN OTHER CHARACTERISTICS 758 PTS2 ASSIGN 6,1,20 »Pfc=PT DIAGNOSTIC CATEGORY (VIA FN20) 759 CHAR ASSIGN 5.1.PI *P5=NUMBER OF PATIENT'S DOCTOR (VIA FN*l) ^ 760 ASSIGN 7,1,30 *P7=PATIENT SEX. (VIA FN30) LL 761 ASSIGN B.l.VtAOIST *P8=PATIENT AGE GROUP (VIA FN*V»ADIST) ^ 76? ASSIGN 9, l , V t L D I S T *P9 = PATIENT"S L OF STAY (VIA FN*V$L0IST) 763 MSAVEVALUE P l + , P 6 , l , l . M H •ADD 1 TO » GENERATED (SERVICE/CATEGORY) 764 MSAVEVALUE P1+,6,1,1,MH • ADD 1 TO # GENERATED (BY SERVICE) 765 TEST GE P6,3,EMERG •SEND EMERG AND DIRECT URGENTS TO HANDLE 766 PRIORITY VSCTPRI,BUFFER • PROCEED IN ORDER BY CATEGORY 767 PRIORITY 20 • RAISE TO PROPER CATEGORY 768 OUEUE VtWAI TO •GATHER WAIT TIME STATS (SERVICE/CATEGORY 76 9 TEST NE P I , 1, MEDIC •SEND MEDICAL REQUESTS TO HANDLE 770 TRANSFER ,SURG •SEND SURGICAL REQUESTS TO HANDLE 771 ***************** ********************* 772 • SURGICAL REOUEST HANDLING 773 ************************************** 774 7 75 w • CONSIDER E.E.N.T.,ORTHOPEDICS,UROLOGY, AND GYNECOLOGY TO BE PROPERLY BLOCK 776 * BOOKED BY DAY FOR DOCTOR, GENERAL SURGERY BY SUB-SERVICE. AND NEURO/PLASTICS 777 * NOT AT ALL. 778 * 779 8LN0T TERMINATE • TEMPORARY 780 BLSRV TERMINATE •TEMPORARY 781 SURG ASSIGN 10,1.120 • P10=PRE-0PERATIVE LOS (VIA FN120 I 782 TEST GE P10.P9,CANDO • IF PRE-OP LOS IS * L' LOS, CAN BE DONE 783 ASSIGN 9.P10 • IF NOT, PUT PRE-OP LOS IN LOS SPOT 734 ASSIGN 9*,1 •AND ADD I 785 CANDO ASSIGN U . l . V t S D I S T • P I 1= LENGTH OF NEXT SURG (VIA FN*V*SDIST» 786 TEST G P I , 2,BLSRV •FOR SERVICE 2 GO BLOCK BOOK BY A/B/C. 73 7 TEST L P1, 7,BLNQT • FOR SERVICE 7 GO TREAT AS NOT BLOCK BOOK 788 SAVEVALUE CHKDR.P5.H • DOCTOR TO CHECK IN XHSCHKDR 789 TRANSFER .FN140,, NOREQ •XFER PROPORTICN NOT REQUESTING A DATE 790 * ASSIGN A REQUESTED DATE TO AN APPROPRIATE PROPORTION OF PATIENTS 791 ASSIGN 12,l,V»DSTRQ • P12=DAYS TO REO. DATE FROM NEXT BLOCK 792 ASSIGN 13,1 ,V$SGYDW • P13=0CCT0R« S DAY OF WEEK FOR SURGERY 793 ASSIGN 12+,MH*VtOFFSL(1.P13I *P 12=REQUESTEO DATE CF SURGERY 794 MARK 13 • IS S EQ. DAT E PCSS I BLE7 P13=PRESENT TIME 795 ASSIGN 13*,P10 •P13=EARL1EST POSS DATE FOR PRE-OP LOS 796 TEST G P13.P12.FEAS • IF THIS DATE 'LE' REQ. DATE O.K. 797 A S SIGN 12+. 7 •OTHERWISE INCREMENT REO. DATE SO O.K. 798 FEAS SAVEVALUE CHECK,P12.H • CHECK DATE (FOR SURGERYI FROM REO. DATE 799 TRSNSFER . TRY • GO TRY TO PLACE ON SLATE 800 * NO PARTICULAR DATE REQUESTED FOR THESE PATIENTS 801 NOREO MARK 13 •P13=PRESENT TIME 302 ASSIGN 15,0 • ZERO P15 803 ASSIGN 15-.P13 •P15=-PRESENT TIME 804 ASSIGN 14,1 .VSSGYDW • P14=D0CT0R>S DAY OF WEEK OF SURGERY 805 ASSIGN 13.MH*V»0FFSL« 1.P14) •NEXT DATE OF SURGERY FOR DOCTOR 806 ASSIGN 15-.P10 •P15=-VE OF NEXT POSSIBLE TIME 807 ASSIGN 15*,P13 • P15=FREE MARGIN TO NEXT SLATED DAY 808 TEST L P15.0,AFEAS • I F NEGATIVE, CUST FIX 809 ASSIGN 13 + , 7 • INCREASE BY 1 WEEK 810 AFEAS ASSIGN 15.0 •CLEAR NUMBERS FROM P15 811 ASSIGN 13+.7 •START CHECKING SPOT I WEEK FR EARLIEST 812 SAVEVALUE CHECK. PI 3.H • CHECK DATE WAS COMPUTED IN P13 813 814 * SEGMENT READY TO TRY A PARTICULAR DAY 815 * AT THIS POINT , XHJCHKOR AND XHSCHECK MUST BE SET 8 1 6 817 A TRY SAVEVALUE WEEK ,V tCWEEK ,H • WEEK CHECKED DETERMINED FROM CHECK DATE 818 TEST GE XHSWEEK.6.LO0K • IF 'L» 6 WEEKS AWAY. LOOK AT SLATE 819 * THESE ONES 6 OR MORE WEEKS AWAY, PUT ON SLATE END 820 ASSIGN 4,XH*CHECK *P4=CHECK DATE FOR SURGERY 821 ASSIGN 3.P4 • SAME TO P3 822 8?3 824 825 826 82 7 828 829 830 831 832 833 834 835 836 837 838 839 340 841 842 843 844 845 346 847 34 8 849 850 851 852 853 854 855 856 857 858 859 860 861 862 963 864 865 865 867 e68 869 870 971 872 873 874 875 876 877 878 879 880 881 ASSIGN TEST LE ASSIGN ASSIGN ASSIGN P0S1 SPLIT TRANSFER SLCH1 L INK 3-.P10 P6,0,P0S1 13, P6 6,0 6-.P13 l . S L C H l .FILE V$SEUSC,6 LOOK FOR THESE MUST LOOK AT DESIRED SPOT ON SLATE *P3 = ADMISSI0N DATE I SURG - PREOP) * WANT POSITIVE CATEGORY •PUT ANY NEGATIVE CATEGORY IN P13 •SET TO 0 •NOW POSITIVE •CREATE COPY FOR SLATE CHAIN •ORIGINAL TO ADMISSION FILE •LINK TO SLATE-END CHAIN BY DOCTOR ASSIGN SAVEVALUE SAVEVALUE SAVEVALUE ASSIGN ASSIGN ASSIGN SAVEVALUE ASSIGN SAVEVALUE TEST NE TEST LE 15.1,V$SGYDW •P15=SURGERY DCW FOR DOCTOR PTFWK.VtAPRWK.H •IDENTIFY ROW FOR APPROPRIATE WEEK'S PTS TMFWK,XH$PTFWK,H •SET THIS THE SAME TMFWKt-.l.H *APPROPRIATE WEEK'S TIME IS 1 ROW LATER 13, MH*VtOFFSL(XHtPTFWK,Pl5) •P13=PTS FOR DATE BEING CHECKED l 3 * » l •P13=PTS IF THIS ONE ADDED 14, MH^VtOFFSL(XH$TMFWK,Pl5) *P14=TIME FOR DATE BEING CHECKED N P U T M . D I A - U h T t I i r nrmnr- . OW , P14.H 14+.P11 CHKTM.PH.H BVtTRYDA,1.GOTDA P6.3.N0TUR •TIME BEFORE A BUMP •P14=TIME IF THIS ONE ADDED •SETTING SURGERY TIME TO TRY TO FIND • I F TRUE, THE DAY IS GOOD •UNLESS P6 IS 3 (OR SET NEG) NOT URGENT NOE NOS THE FOLLOWING SECTION OEALS WITH URGENT PATIENTS TEST GE XH$WEEK,2,US00N • I F TRYING 'L' 2 WEEKS AWAY. DO SOON URGENTS OVER 2 WEEKS AWAY TRY TO BUMP UNLINK VtSLUSC.BUMPD.l.BV*BUMPE..NOE *0/W TRY TO BUMP ELECTIVE OF THIS DR TRANSFER .GOTDA • PUT THIS ONE ON IN HIS PLACE V$SLUSC,BUMPD,1,BVJBUMPS,,NOS •NO EL - TRY TO BUMP SEMI-URGENT ,GOTDA *PUT THIS ONE ON IN HIS PLACE CHECK*,7,H *NOONE TO BUMP, SO TRY 1 WEEK LATER TRY • +G0 TRY AGAIN UNLINK TRANSFER SAVEVALUE TRANSFER THESE TO BE TREATED AS URGENTS FOR WITHIN 2 WEEKS USOON MARK ASSIGN ASSIGN TEST LE THWK SAVEVALUE TRANSFER NEWK TEST L ASSIGN ASSIGN PROPR SAVEVALUE WANTD SAVEVALUE 1 3 •START CHECKING AT EARLIEST POSSIBLE TIME 1 3 * » 1 ^TRY TOMORROW ADM AT EARLIEST 1 3 * ' P 1 ° •NOW HAVE EARLIEST DAY OF SURGERY P13.MH^V$0FFSLf 1,5),NEWK *DATE BY THIS FRIDAY? V.EEK,0,H ,WANTD V*ENDWK,3,PR0PR 13,XHtPWEEK 13*.8 WEEK,I,H CHECK. PI 3.H •BY FRIOAY, SO IT IS THIS WEEK •WANT TO FIND A DOCTOR •WAS DATE SET ON WEEKEND? HAVE DATE, FIND CORRESPONDING DOCTOR •YES, SO SET TO NEXT MONDAY •HAVE PROPER CATE NEXT WEEK •CHECK DATE IS EARLIEST POSSIBLE SAVEVALUE GETDA ASSIGN ASSIGN TEST NE SAVEVALUE TRANSFER CHKDR,1,H •COULD 1ST DOCTOR POSSIBLY 00? 15,l,VtSGYDW •FIND THIS DOCTOR'S DAY OF THE WEEK 14,MH*VtOFFSL{I.P15) •NEXT DAY OF SURGERY FOR THAT DOCTOR U t T B v n o . n n * w n i / _ -v/^ n • . — — . . . . . . V RYDR.O,DAYOK CHKDR*,I,H ,GETDA DATE AND DOCTOR CORRESPOND, SEE IF THE DAY IS OK •TO DAYOK IF THIS ONE MIGHT DO •TRY NEXT DOCTCR •GO TO GET HI S DAY DAYOK SAVEVALUE SAVEVALUE SAVEVALUE ASSIGN ASSIGN ASSIGN ASSIGN TEST NE PTFWK,VtAPRWK.H TMFWK,XHtPTFWK.H TMFWK*,I ,H •IDENTIFY ROW FOR APPROPRIATE WEEK'S PTS •SET THIS THE SAME •APPROPRIATE WEEK'S TIME IS 1 ROW LATER 13. MH*V$OFFSL(XH$PTFWK,P15) *P13 = PTS FOR DATE BEING CHECKED l 3 + ' 1 'PTS IF THIS ONE ADDED 14, MH*V$0FFSL(XHJTMFWK,P15) • P14=TIME FOR THAT DATE l * + . p l l *TIME IF THIS ONE ADDED BVtTRYDA,1,GOTDA * I F TRUE, GOT DAY - 1 882 TEST NE P15.5.WKDON * I F THAT WAS FRIDAY, WEEK DONE 883 NEWDR SAVEVALUE CHKDR*,1,H * ADD 1 TO CHECKED DOCTOR 88 * ASSIGN 15, l ,VtSGYDW *P15=SURGERY DOW OF THIS DOCTOR 335 ASSIGN 14, MH*VtOFFSLCI.P151 *NEXT DATE OF SURGERY FOR THAT DOCTOR 886 TEST NE VtO ASA M, 0, NE WOR * I F THIS DR ON SAME DAY GO FOR ANOTHER 887 SAVEVALUE CHECK*,1,H ' TO TRY DAY LATER 888 TRANSFER ,DAYOK *G0 SEE IF THIS DAY IS OK 889 WKOON SAVEVALUE WEEK + . l . H ' * TRY NEXT WEEK 890 * TREAT SPECIALLY IF THIS IS TOO FAR AWAY 891 TEST GE XHt WEE K, 3 , CL0S1 *ARE THERE NO SPOTS NEARBY7 892 SAVEVALUE CHKDR,P5,H *N0 , GET PROPER DOCTOR AGAIN 893 ASSIGN 15, l ,VtSGYDW 'H I S DAY OF THE WEEK FOR SURGERY .894 SAVEVALUE CHECK,MH*V$OFFSL11.P15),H ' H I S NEXT SURGERY DAY 895 SAVEVALUE CHECK*, 14,H * 2 WEEKS AWAY 896 TRANSFER ,TPY * FE WILL NOW BUMP ANOTHER 897 * ST ILL CLOSE ENOUGH 898 CLOS l SAVEVALUE CHECK* ,3 ,H 'ADVANCE DAY FRIDAY TO MONDAY 899 SAVEVALUE CHKDR, 1 ,H ' START AGAIN WITH FIRST DOCTOR 900 ASSIGN 15,1 ' TH I S DOCTOR'S DAY OF THE WEEK 901 TRANSFER ,CAYOK . ' G O SEE IF THE DAY IS OK 902 * 903 * THE FOLLOWING SECTION DEALS WITH NON-URGENT PATIENTS 904 * 905 NOTUR SAVEVALUE CHECK* , 7.H ' FOR SEMI-U AND EL , TRY 1 WEEK LATER 906 TRANSFER ,TRY 'GO TRY AGAIN 907 * 908 * 8UMPE0 PATIENTS ARE HANDLED HERE 939 * 910 RUMPD SAVEVALUE CHECK,P4,H * DAY BUMPED PT STARTED FROM 911 SAVEVALUE CHKDR,P5.H *DR THIS PATIENT WAS SLATED FOR 912 ASSIGN 15, l .VtSGY0W 'THAT DOCTOR'S DAY OF THE WEEK 913 SAVEVALUE PTFWK.VtAPRWK.H ' I DENT IFY ROW REMOVED FROM 914 SAVEVALUE TMFWK,XHtPTFWK.H ' S E T THIS THE SAME 915 SAVEVALUE TMFWK+.l.H ' I DENT IFY ROW FOR TIME REMOVED 916 TEST GE MH'VtOFF SL(XHtPTFWK.PI 51.FN242.NRTPN *1 OR MORE PER OR THERE? 917 MSAVEVALUE VtOFFSL-.XHtTMFWK.P15.15.MH 'REMOVE TURNAROUND WHICH FOLLOWS 918 NRTRN MSAVEVALUE VtOFFSL - .XHtPTFWK.P15 . l.MH 'REMOVE PATIENT 919 MSAVEVALUE VtOFFSL- ,XHtTMFWK,P I 5,PI I,MH 'REMOVE HIS TIME 920 SAVEVALUE CHECK* ,7 .H ' TRY 1 WEEK FROM THAT SPOT 9?1 SAVEVALUE MDATE. P3 .H * ADM DATE I FOR MATCHING FROM ADM CHAIN) 922 SAVEVALUE MSRVC.P l .H 'WANT SERVICE TO MATCH 923 SAVEVALUE MDGEN,P2,H 'WANT DATE GEN ERA TEO TO MATCH 924 SAVEVALUE ML0ST.P9.H * ALSO MATCH LENGTH OF STAY 925 SAVEVALUE MLOSG.P l l .H 'ALSO MATCH LENGTH OF SURGERY 926 UNLINK ADMSC,TRY,1,BVSMACHR,,FAIL0 'GET PT OFF ADMISSION CHAIN 927 « THEN GO TRY IT FOR LATER WEEK 928 TRANSFER .CSPOS ' TH I S COPY OF PT NOT NEEDED 929 * 930 * PATIENTS HERE HAVE GOTTEN A OAY OK FOR SURGERY 931 » 932 GOTDA ASSIGN 4,XHtCHECK 'SURGERY DATE TO P4 933 ASSIGN 3.P4 'SAME TO P3 934 ASSIGN 3- .P10 *P3=ADMISSION DATE (SUBTR PRE-OP» 935 ASSIGN 15, l ,VtSGYDW *P15=00CTCR"S SURGERY DOW 936 SAVEVALUE PTFWK.VtAPRWK.H ' I DENT IFY ROW FOR APPROPRIATE WEEK'S PTS 937 SAVEVALUE TMFWK,XHtPTFWK.H ' S E T THIS THE SAME 938 SAVEVALUE TMFWK*,1,H 'APPROPRIATE WEEK'S TIME IS 1 ROW LATER 939 MSAVEVALUE Vt OFFS L* ,XHt PT FWK, PI 5, I, MH 'ADD I TO PATIENTS SLATEO THERE ^ 940 MSAVEVALUE VtOFF S L * . XH1 TMFWK, P15, PI 1, MH 'ADD SURGERY TIME TO THAT SLATED J " , 941 TEST GE MH*VtOFFSL«XHtPTFWK,P15 I .FN242,PUT2 * 2 * PER OR SLATEO THERE? 942 MSAVEVALUE V S O F F S L * . X H i T M F W K , P I 5 ,15 ,MH * A 0 0 TURNAROUND BEFORE NEXT PT 943 PUT2 TEST LE P 6 . 0 . P 0 S *WANT POSIT IVE CATEGORY 944 ASSIGN 1 3 , P 6 *PUT ANY NEGATIVE CATEGORY IN P13 945 ASSIGN 6 , 0 * S E T TO 0 946 ASSIGN 6 - . P 1 3 *NOW POSITIVE 947 POS SPLIT 1 .SLCH2 * CREATE COPY FOR S L A T E CHAIN 948 TRANSFER . F I L E *ORIGINAL TO ADMISSION F I L E 949 SLCH2 LINK V t S L U S C . 5 *PUT ON SLATE CHAIN BY OOCTOR 950 * PATIENTS HERE ARE Ft LEO ON ADMISSION OUEUE 951 F I L E LINK ADMSC.3 *0N ADMISSION CHAIN BY DATE 1353 ************.**.*****.************* *.*«**«* 953 * MEDICAL REQUEST HANDLING 954 j . * * * * * * * * * * * * * * * * * * * * * * . * * . * « * » . * * * * * . * * * . * * . 955 * 956 * PUT THESE RE3UESTS ONTO THE MEDICAL ADMISSIONS CHAIN 957 * 958 MEDIC LINK ADMMC.FIFO *CNTO MEDICAL ADMISSION CHAIN 959 «****.« ***.** ************ ********* *.*»*.*** 960 * TRANSACTION TO INSTIGATE ADMISSIONS 96 1 A************************************** 962 * 963 * FOR SURGICAL ADMISSIONS. ADMIT ALL SCHEDULED FOR TODAY (ACCORDING 964 * TO THEIR S L A T E ) . MEDICAL ADMISSIONS GET SPECIF IED NUMBER OF 965 * REMAINING B E D S . LAST FEW ARE SAVED FOR EMERGENCIES. 966 * 967 GENERATE 1 , , , , 1 0 +SINGLE TRANSACTION PER DAY TO INSTIGATE 968 MARK 3 * T O D A Y ' S DATE IN P3 969 UNLINK A D M S C , A D M S . A L L , 3 * A L l SURG. ADMISSIONS TODAY TO ADMS 970 ASSIGN I .FN231 •NUMB ER MED S TO ADMIT 971 UNLINK ADMMC.ADMM,PI * ADMIT MEDICAL PATIENTS 972 TERMINATE *REMOVE INSTIGATING TRANSACTION 973 ************************************** 974 * SURGERY ADMISSION PATH 975 ***«******+*****••********»*********** 976 * 977 * FOR NOW, ALLOW ONLY INTO A BED OF THE PROPER SERVICE AREA. IGNORING SEX 978 * BASED ON AVERAGE NUMBERS ENTERING EMERGENCY AND INHOSPITAL OPERATIONS 979 * PER DAY, NOW GENERATE•THESE REQUESTS. SAY EMERGENCIES ARE NEXT DAY, 980 * INHOSPITAL REQUESTS AS SOON AS POSSIBLE FROM 2 DAYS AWAY. 991 * ' 9f>2 ADMS GATE LR WAIT * ALLOWED TO BE PROCESSED? 993 TEST L R * 1 , 1 , A 0 K *ROOM IN S E R V I C E ' S BEDS ? 984 SAVEVALUE N 0 B 0 * , 1 , H *ONE MORE 'NO BED' 985 ASSIGN 13, P6 +XATEGORY IN P13 986 ASSIGN 6 , 0 *WANT TO SET NEGATIVE 987 ASSIGN 6 - . P 1 3 *NOW NEG, PROCESSED AS URGENT 998 * 'NO B E D S ' TRY CVER 989 ASSIGN 13.XHSPWEEK * F I P S T DAY OF PRESENT WEEK IN P13 990 ASSIGN 1 3 * . 7 *ADVANCE THAT TO NEXT WEEK 991 LOGIC S WAIT *STCP FURTHER ADMISSIONS NOW 992 PRIORITY 1 9 , B U F F E R * F I N I S H WITH OTHERS FIRST 993 PRIORITY 20 *RE STORE PRIORITY 994 LOGIC R WAIT *ALLOW FURTHER ADMISSIONS NOW 995 * NEED TO LOCATE THEM ON SURGERY SLATE 996 TEST L P13,P4 .THSWK *WH1CH WEEK SURGERY? THIS OR NEXT 997 SAVEVALUE W E E K . l . H *CHECK 1 WEEK AWAY FOR SURGERY TIME 998 TRANSFER , O F F S G * NEED PT OFF SURGERY CHAIN 999 THSWK SAVEVALUE W E E K . O . H *CHECK ON THIS WEEK'S SLATES 1000 OFFSG SAVEVALUE M 0 A T E . P 3 . H * F I P S T , TAKE CATE TO MATCH 1001 SAVEVALUE M S R V C . P 1 . H *WANT SERVICE TO MATCH 1002 1003 1004 1005 I 006 1007 IOOR I 009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1 019 1020 1021 1022 1023 1024 1025 1026 1 027 1028 1029 1 03 0 1031 1032 1033 1034 1035 1036 1037 1038 1039 1 04 0 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 105? 1053 1054 1055 1 056 1057 1058 1 059 1060 1061 SAVEVALUE HOG-EN,P2.H * WANT DATE GENERATEO TO MATCH SAVEVALUE ML0ST,P9,H *ALSO LENGTH GF STAY SAVEVALUE MLOSG.Pll.H 'FINALLY, LENGTH OF SURGERY UNLINK VtSLUSC.OSPOS,l.BVtMACHR,.FAILO 'GET PT OFF SURGERY CHAIN SAVEVALUE CHKDR,P5.H * DR THIS PATIENT WAS SLATED FOR ASSIGN 15,l,VtSGY0W * THAT OOCTOR'S DAY OF THE WEEK SAVEVALUE PTFWK.VtAPRWK.H 'IDENTIFY ROW REMOVED FROM SAVEVALUE TMFWK,XHtPTFWK.H 'SET THIS THE SAME SAVEVALUE TMFWK*,I ,H * IDENTIFY ROW FOR TIME REMOVAL TEST GE MH'VtOFFSLIXHtPTFWK.Pl 5) .FN242.NRMTN *2+ PER OR THERE? MSAVEVALUE VtOF FS L- .XHtTMFWK, PI 5, 15, MH 'REMOVE TURNAROUND WHICH FOLLOWS NRMTN MSAVEVALUE VtOFFSL-,XHtPTFWK,P15,1,MH 'REMOVE PATIENT MSAVEVALUE VtOFFSL-,XHtTMFWK.P15.P11.MH 'REMOVE HIS TIME ASSIGN 4*.7 * ADO 1 WEEK TO ATTEMPTED OPERATION DATE SAVEVALUE CHECK,P4.H 'PUT THIS DATE IN CHECK OATE TRANSFER .TRY 'GO TRY, SAME RULES AS NEW REQUESTS IF THERE IS A BED... ACK LOGIC S PR I ORIT Y DEPART WAIT 10,BUFFER VtWAITO 'NO MORE ADMISSIONS JUST NOW 'RESET PRIORITY LEVEL 'LEAVE WAITING TIME OUEUE GENERATE EMERGENCY AND INHOSPITAL OPERATION REQUESTS TRANSFER SPLIT MARK ASSIGN TEST GE ASSIGN LINK NOEMG TRANSFER SPL! T ASSIGN INHRO MARK ASSIGN TEST GE TEST LE SAVEVALUE TRANSFER NEWEK TEST L ASSIGN ASSIGN PROPE SAVEVALUE WCNTD SAVEVALUE .FN247,,NOEMG I, NOEMG 4 4*,1 P9,2,DSPOS I I , 1,V$SDIST EMRGC,4 ,FN248,,N0INH I . NOINH I I . 1.V1SDIST 13 13*.2 P9,3,DSPOS 'SEND PROPORTICN NOT GENERATING EMERG OP 'OBTAIN ENTITY TO FOLLOW THIS PATH 'PRESENT DAY IN P4 •HENCE EMERG CP TOMORROW 'IGNORE IF LOS 1 L ' 2 DAYS *P1 l^LENGTH OF EMERG SURGERY * PUT ON EMERGENCY CHAIN FOR TOMORROW 'SEND THE PROPORTION NOT PLACING INH REO 'GET ENTITY TO EFFECT INHOSPITAL REQUEST »P11 = LENGTH OF SURGERY 'PRESENT DAY IN P13 'EARLIEST POSS DAY 2 AWAY 'IGNORE IF LOS 'L' 3 DAYS P13.MH*VtOFFSL(l,51,NEWEK 'DATE BY THIS FR IOAY? WEEK,0,H .WONT D VtENDWK,3,PR0PE 13,XHtPWEEK 13*.8 WEEK.l ,H CHECK,PI 3,H HAVE DATE. FIND CORRESPONDING DOCTOR 'YES, SO IT IS THIS WEEK 'WANT TO FINO A DOCTOR 'WAS DATE SET CN WEEKEND? 'YES, SO SET TO NEXT MONDAY 'HAVE PROPER DATE NEXT WEEK 'THIS GIVES CHECK DATE SAVEVALUE GETSG ASSIGN ASSIGN TEST NE SAVEVALUE TRANSFER CHKDR, l.H 15,1.VSSGYDW 'CAN 1ST DOCTOR POSSIBLY DO 'FIND THIS DR'S DAY OF WEEK 14,MH*VtOFFSLI1.P15) 'FIND HIS NEXT SURGERY DAY VtTRYDR.O,DAYKO CHKDR*,I,H ,GET SG ' I F HIS TIME IS OK TO CHECK, TO DAYKO •OTHERWISE, TRY NEXT DOCTOR 'GO TO GET HI S OAY DATE AND DOCTOR CORRESPOND, SEE IF THE DAY IS OK DAYKO SAVEVALUE PTFWK.VtAPRWK.H 'IDENTIFY ROW FOR APPROPRIATE WEEK'S PTS TMFWK,XHtPTFWK.H 'SET THIS THE SAME TMFWK+.l.H 'APPROPRIATE WEEK'S TIME IS I ROW LATER 13, MH*VtOFFSLIXHtTMFWK,P15) *P13 = TIME FOR THAT DAY 13+.P11 *ACD TIME OF THIS ONE TOO P13.FN241 ,GTDAY *GCT DAY IF TIME OK THERE P15.5.WKOUN 'WEEK DONE IF THAT WAS FRIDAY C.HKDR + . l . H *AOD 1 TO CHECKED DOCTOR 15,l,VtSGYDW *DR'S SURGERY CAY OF THE WEEK IN P15 14, MH*VtOFFSLI 1.P151 'NEXT DAY OF SURGERY FOR THAT DOCTOR SAVEVALUE SAVEVALUE ASSIGN ASSIGN TEST G TEST NE NWDOC SAVEVALUE ASSIGN ASSIGN K> O 1062 TEST NE VtDASAM.O.NWDOC *G0 FOR ANOTHER IF THIS DR SAME DAY 1063 SAVEVALUE CHECK*,1,H •TO TRY DAY LATER 1064 TRANSFER .DAYKO *G0 SEE IF THIS DAY IS OK 1065 * PATIENTS HERE HAVE GOTTEN A DAY FOR THEIR INHOSPITAL SURGERY I 066 WKOUN SAVEVALUE WEEK*,1,H •TRY NEXT WEEK 1067 * TREAT SPECIALLY IF TOO FAR AWAY 1068 TEST GE XHtWEEK,2,CL0S2 •ARE THERE NO SPOTS NEARBY? 1069 MARK 4 • NO, SO MAKE THIS OPERATION EMERGENCY 1070 ASSIGN 4*,I •FOR TOMORROW I 071 LINK EMRGC.4 •PUT ON EMERGENCY CHAIN 1072 * THESE ARE SOON ENOUGH 1073 CL0S2 SAVEVALUE CHECK*,3,H •ADVANCE DAY FRIDAY TO MONDAY I 074 SAVEVALUE CHKDR,I .H • START AGAIN WITH FIRST DOCTOR 1 075 ASSIGN 15,1 • THIS DOCTOR'S DAY OF THE WEEK 1076 TRANSFER ,DAYKO •GO SEE IF THE DAY IS OK 1077 GTOAY ASSIGN 4.XHSCHECK • SURGERY DATE TO P4 1078 ASSIGN 13,P3 •PRESENT OAY TC P13 1 079 ASSIGN 13+.P9 •P13=TIME OF DISCHARGE NOW 1 080 TEST L P4.P13.DSPOS • OISPOSE IF SURG TIME SET BEYOND DISCHARG 1081 ASSIGN 6,0 •ENSURE NO BUMPING 1082 ASSIGN 15,1.VtSGYDW •P15=SURGERY CAY OF WEEK 1033 SAVEVALUE TMFWK,VtAPRWK.H •SET AS ROW FOR APPROPRIATE WEEK'S PTS 1 084 SAVEVALUE TMFWK+,1,H •APPROPRIATE WEEK'S TIME IS 1 ROW LATER 1085 MSAVEVALUE VtOFFSL* .XHtTMFWK ,P15,Pll.MH *ADD SURGERY TIME TO SLATED TIME 1086 MSAVEVALUE VtOFFSL*,XHtTMFWK ,P15,15,MH *ADD TURNAROUND BEFORE NEXT PT 1 087 LINK VtSLUSC,5 • PUT ON SLATE USER CHAIN 1098 * I 089 * NOW THE PATIENT ENTERS A HOSPITAL BED 1090 * 1091 NOINH ENTER PI •ENTER BEDS FCR SERVICE 1 092 LOGIC R WAIT •CAN ALLOW OTHERS NOW 109 3 SAME MSAVEVALUE P1+,P6,2,1,MH • ADD 1 TO PATIENTS ADMITTED 1094 MSAVEVALUE PI*,6,2,l.MH •ADD 1 TO PATIENTS ADMITTED I 095 TEST NE P12.0.NOTRQ • I F 0, NOT A PT WHO REQUESTED DATE 1096 MSAVEVALUE PI*.P6,3,l.MH • COUNT AS REQUESTING 1097 MSAVEVALUE P1*,6,3,1,MH •COUNT AS REQUESTING 1098 TEST E P12 , P4,NOTRO • I F EQUAL. GOT THE RIGHT DAY 1099 MSAVEVALUE PI*.P6,4,l.MH •COUNT SUCCESSFUL ONES 1100 MSAVEVALUE PI*.6,4,l.MH • COUNT SUCCESSFUL ONES 1101 NOTRO ASSIGN 13.P3 •P13=TIME OF ACMISSION 1102 ASSIGN. 13*.P9 *P13=TIME OF DISCHARGE (ADD LOS) 1103 QUEUE VtLOSQ • ENTER OUEUE FOR LOS I 104 OUEUE VtLOSQS • ENTER QUEUE FCR LOS BY SEX I 105 ASSIGN 15,0 • ZERO P15 FCR C PE RATI ON COUNT 1106 PRIORITY 16 • PRIORITY LEVEL FOR DISCHARGES 1107 ASSIGN 14,PI •AREA TO DISCHARGE FROM 11 08 LINK CISCH,13 • PUT ONTO DISCHARGE CHAIN 1 109 DSPOS TERMINATE • FOR UNWANTED TRANSACTIONS 1110 FAILO TRACE • FOR FAILURE TO OBTAIN MATCH 1 111 UNTRACE 1112 TERMINATE 1113 ************************************** 1114 * MEDICINE ACMISSIONS PATH 1115 ************************************** 1116 • 1117 * FOR NOW, 00 NOT CAUSE ANY TRANSFERS TO OTHER HOSPITAL SERVICES, 1118 * HENCE NO OPERATIONS (EMERGENCY OR INHOSPITALI 1119 * I 120 ADMM ENTER PI •ENTER BEDS FOR SERVICE 1121 MARK 3 • ADMISSION TODAY. . . TO P3 1122 DEPART VJWAITQ *L E AVE WAITING TIME QUEUE 1123 TRANSFER ,SAM E *G0 COMPLETE AS SURGICAL H24 A************************************** 1125 * EMERGENCY ADMISSIONS UNIT 1126 *************************************** 1127 EMERG SAVEVALUE EMREO*.l.H *A0O I TO EMERG BEOS IN USE 1128 SAVEVALUE EMARR • »1 , H *0NE MORE HERE TODAY 1120 MARK 3 *A0MISSION TODAY...TO P3 1130 MSAVEVALUE P1*.P6,2,1,MH "ADO 1 TO PATIENTS ADMITTED 1131 MSAVEVALUE P1*.6,2,1,MH *ADD 1 TO PATIENTS ADMITTED 113? * DIFFERENTIATE DAY SH I FT ARRIVALS AND OTHERS (FOR PROCESSING SEOUENCE I 1133 TRANSFER .200..M0RNG "TRANSFER TO ARRIVE IN MORNING 1134 PRIORITY 6,BUFFER "PRIORITY FOR NON-MORNING EMERGENCIES 1135 GATE LR WAITE * ALLOWED TO PROCEED? 1136 SAVEVALUE SHIFT,237,H *FOR NON-MCRNING FUNCTION (OWN BEDSI 1137 TRANSFER ,BRING *G0 BRING THEM IN 1138 MORNG PRIORITY 12,BUFFER 'PRIORITY FOR MORNING EMERGENCIES (6-111 1139 GATE LR WAITE "ALLOWED TO PROCEED? 1140 SAVEVALUE SHIFT,235,H *FOR MORNING FUNCTION (OWN BEDS I 1141 • TEST E PI,1,BRING *A MEDICAL PATIENT? 1142 SAVEVALUE MEMRN+ »1» H *YES, COUNT 1143 * PROCESSING BEGINS AGAIN HERE 1144 BRING LOGIC S WAITE *STOP OTHERS NOW 1145 TEST NE Pl.l.NOEIN * SEND EMERG MECICAL REQUESTS TO PROCESS 1146 * GENERATE EMERGENCY AND INHOSPITAL OPERATION REQUESTS 1147 TRANSFER .FN247,,NOEOP *SENO PROPORTION WITH NO EMERG OP REQUEST 114B ASSIGN ll.l.VSSOIST * PI1 = LENGTH OF SURGERY 1149 SPLIT 1,NOEOP "OBTAIN ENTITY TO FOLLOW THIS PATH 1150 MARK 4 *SAY PRESENT OAY OPERATION 1151 LINK EMRGC.LIFO *PUT ON HEAD OF EMERG CHAIN FOR TODAY 1152 NOEOP TRANSFER .FN248,,NOEIN "SEND THOSE NOT PLACING INHOSPITAL OR REO 1153 ASSIGN ll.l.VSSDIST *P11=LENGTH OF SURGERY 1154 SPLIT l.NOEIN "OBTAIN ENTITY TO FOLLOW THIS PATH 1155 TRANSFER , INHRQ "GO HANDLE INHOSPITAL OR REQUEST 1156 * NOW TRY TO PLACE IN PROPER BEDS 1157 * IF IMPROPER, MAY ARRANGE FOR TRANSFER TOMORROW MORNING 1158 NOE IN LOGIC P. WAITE * ALLOW OTHERS NOW 1159 QUEUE VILOSQ "ENTER THE QUEUE FOR LOS 1160 OUEUE VtLOSOS- "ENTER QUEUE FOR LOS BY SEX 1161 ASSIGN 14,PI , *P14 = BFD AREA 1162 TEST LE R*14,FN*XH$SHIFT,PUT IN "PUT PT IN IF ANY ROOM THERE 1163 SAVEVALUE SHIFT*,1,H * NOW READY FOR 'OTHER AREA' CHECK 1164 ASSIGN 15,3 "UP TO 3 ALTERNATE AREAS 1165 ALT ASSIGN 14,MHtALTER(PI,P151 *P14 = ALTERNATE BED AREA 1166 TEST NE P14,0,NMALT "IF 0, NO MORE ALTERNATIVES 1167 TEST LE R*l 4,FN" XHSSHI FT.ALTOK "ALTERNATE OK IF ROOM THERE 1168 LOOP 15.ALT "ANOTHER ALTERNATIVE? 1169 ASSIGN 14.0 "NO ROOM, STAY IN EMERG 1170 TRANSFER ,NMALT "WILL NEED TRANSFER 1171 * TRANSFERS ARE FROM P14 AREA ... 0 IS EMERG 1172 * THESE PATIENTS ARE PUT IN THE WRONG AREA 1173 ALTCK ENTER P14 "PUT PATIENT IN ALTERNATE AREA 1174 SAVEVALUE EM8E0-,1,H * REMOVE FROM E*ERG BED 1175 MSAVEVALUE P1+,P6,5,1,MH "INCREMENT NUMBER IN WRONG AREA 1176 MSAVEVALUE Pl*.6,5.1,MH "INCREMENT NUMBER IN WRONG AREA 1177 OUEUE VSWRONQ "CCUNT PATIENTS BY WRONG AREA 1178 TEST NE P14,2,T0VER "IN OVERFLOW AREA OR NOT? [V 1179 TEST NE Pl.l.MDOFF "MEDICALS HANDLED SPECIALLY J~ 1180 TEST LE R*14,FN239,CNSTA "IF MORE SPACE THERE, NO XFER 1181 TRANSFER ,NMALI "IF LESS, AN IN-HOSPITAL XFER 1182 1183 1184 1185 1196 1 187 1188 1189 1 190 1191 1192 1193 1194 1195 1 196 1197 1 198 I I 99 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 TOVER TRANSFER .250..NMALI TRANSFER .CNSTA MEOICAL PATIENTS IN SURGICAL AREAS MOOFF ASSIGN ASSIGN PRIORITY ASSIGN LINK 13,P3 13*,P9 14 15,0 VtM0FF,13 THESE MUST TRANSFER SOON V.tWRONQ 15,0 13,P3 13*,P9 14 XFERC, FIFO IN PROPER AREA P14 EMBED-,l.H 13,P3 13+ ,P9 15,0 16 0ISCH.13 *******•****>***»*****»»***»*****»**»*,*. INHOSPITAL TRANSFERS NMALT QUEUE NMAL1 ASSIGN ASSIGN ASSIGN PRIORITY LINK * THESE PLACED PUTIN ENTER SAVEVALUE CNSTA ASSIGN ASSIGN ASSIGN PRIORITY LINK •25* ATTEMPT TRANSFER TO PROPER AREA •READY TO DISCHARGE GET SPECIAL CHAINS •P13=TIME OF ADMISSION • P13=TIME OF DISCHARGE • IN CASE OF TRANSFER •ZERO OPERATION COUNT • INCREASING DISCHARGE ORDER • COUNT PTS STAYING IN EMERG • ZERO P15 FOR OPERATION COUNT •P13=TIME OF ADMISSION *P13=TIME OF DISCHARGE • SET PRIORITY LEVEL FCR TRANSFERS •PUT ON CHAIN TO TRANSFER ASAP •ONE MORE PT IN APPROPRIATE WARO •REMOVE 1 FROM EMERGENCY BEDS •P13=TIME OF ADMISSION *P13=TIME OF DISCHARGE • ZERO P15 FOR OPERATION COUNT • PRIORITY LEVEL FOR DISCHARGES •PUT ONTO THE 01SCHARGE CHAIN GENERATE I , . ,.14,3 • TRANSACTION TO INSTIGATE TRANSFERS DAILY UNLINK XFERC,TRYIN,ALL • UNLINK ALL TRANSACTIONS TO TRYIN MARK 3 •TODAY'S DATE TO P3 TEST NE BV1WKEND,l.WEOK ' •WEEKENDS OK IDON'T XFERI SAVEVALUE WEEK.O.H •THIS WEEK SAVEVALUE PTFWK.VtAPRWK.H •GIVES ROW FOR PATIENTS ASSIGN 1,3 •EENT BEDS ASSIGN 2.MH^V10FFSL(X HtPTFWK » VtWKDAY) *# OF BEDS NEEDED THERE ASSIGN 2-.1 • ALLOW I LESS TEST G VtNOFF,O.DOORT •DOES EENT GET BEDS? UNLINK MALT3,BACKl,VtNOFF .BACK * S END LONG-STAY MEDS BACK DOORT ASSIGN 1.4 •DO ORTHOPEDICS ASSIGN 2,MH^VtOFFSL(XHtPTFWK,VtWKDAY) *# OF BEOS NEEDED THERE TEST G VtNOFF,O.WEOK •DOES ORTHO GET BEOS? UNLINK MALT4,BACKl,VtNOFF • BACK •SEND LONG-STAY MEDS BACK WEOK TERMINATE • REMOVE INSTIGATOR TRANSACTION BACKl TEST E Rl.O.TXFER •ANY BEDS IN MED AREA? LI NK VtM0FF,13 • I F NOT, STAY PUT TRYIN PRIORITY TEST E LINK 14,BUFFER R+l.O.TXFER XFERC,LIFO • THESE GET INTO RIGHT BED NOW TXFER ENTER PI TEST E P14.0.NEMG SAVEVALUE EMBED- ,1 ,H TRANSFER ,TOOIS NEMG LEAVE P14 MSAVEVALUE P1 +, P6, 6, I , MH MSAVEVALUE PI*.6.6.l.MH TODIS ASSIGN 13.P3 ASSIGN 13*,P9 DEPART VtWRONQ • RESET PRIORITIES FOR TRANSFER • TRANSFER PT IF ANY ROOM THERE • I F NOT, BACK ON XFER CHAIN •ONE MORE PATIENT THERE •UNLESS P14=0, NOT FROM EMERG •REMOVE 1 FROM EMERG BEDS •PROCEED TO ARRANGE DISCHARGE • OUT OF ALTERNATE AREA'S BED •AO.D 1 TO NUMBER CORRECTED • AOO 1 TO NUMBER CORRECTED • P13=TIME OF ADMISSION • P13 = TIME OF DISCHARGE •COUNT PATIENTS FROM WRONG AREA K> PNJ CO 1242 1243 1244 1245 1246 1247 1248 1249 12 50 1251 1252 125 3 1254 1255 1256 1257 1258 1259 1260 1261 1 26? 1263 1264 1265 1266 1267 1268 1269 1270 1271 127? 1273 12 74 1275 1276 1277 1278 1279 1280 1231 1 282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 PRIORITY ASSIGN LINK 16 14,PI D I S C H , 1 3 "PRIORITY LEVEL FOR DISCHARGES •AREA TO DISCHARGE FROM •PUT ONTO THE DISCHARGE CHAIN TRANSACTION TO INSTIGATE DISCHARGES GENERATE 1.... 16, 13 MARK 13 UNI INK DISCH,LEAVE,ALL, 13 UNLINK XFERC,LEAVP,ALL, 13 UNLI NK MALT3,LEAVP,ALL, 13 UNLINK MALT4,LEAVP,ALL, 13 TERMINATE LEAVP PRIORITY 16,BUFFER LEAVE DEPART VtLOSO DEPART VtLOSOS TEST NE P14.P1.N0NEM DEPART VtWRONO TEST E P14.0.N0NEM SAVEVALUE EM3ED-,1,H TRANSFER .ONOUT NCNEM LEAVE P14 CNOUT TEST E P14.1.8YE SAVEVALUE MAD I S * , l . H BYE TERMINATE * O P E R A T I N G R O O M O A T A *****•*«*«»*«** 4«, • TRANSACTION PER DAY TO INSTIGATE DISCH • TODAY'S DATE IN P13 • ALL PTS TO BE DISCHARGED TODAY TO LEAVE •INCLUDE THOSE WAITING FOR XFER • HEOICAL PATIENTS STILL OFF-SERVICE • MEDICAL PATIENTS STILL OFF-SERVICE • REMOVE INSTIGATOR FROM MODEL • MUST RAISE PRIORITY FOR THESE •LEAVE THE QUEUE FOR LOS • LEAVE THE OUEUE FOR LOS BY SEX •PATIENT IN RIGHT AREA? • NO, COUNT PATIENTS FROM WRONG AREA •STIL L IN EMERG BEO IF 0 • REMOVE FROM THERE • SEND ON OUT •REMOVE ONE PT FROM THAT BEO POOL • A MEDICAL AREA DISCHARGE? •YES, COUNT •REMOVE PATIENT FROM MODEL L F V E L 0F^TIMI <Nr*TH4N ?FnIvE ™ C A L - T H E A T R E S W O U L D I N V O L V E A M O R E M I C R O LhVEL OF T I M I N G T H A N I D A Y , I T I S N O T E E I N G D O N E IN D E T A I L . i n n J L . c P ! 0 ™ * T D 0 C T 0 R , S T I M E E S T I M A T E S W O U L O I f P R O V E , AS W O U L D T H E A R E U S E D ^ H E N C E A C T U A L ( N O T E S T I M A T E D ! TZi DFSTR^BU^IONS M E A N T U R N A R O U N D I S C O N S I D E R E D T O B E 15 M I N U T E S . I F 4 O P E R A T I O N S W E R F DONF F O R E X A M P L E , T H E R E W E R E 3 T U R N A R O U N D S - O N E O V E R L U N C H , SO 2* 15 ISAOOFn T H I S I S D O N E F O R E A C H O P E R A T I N G ROOM R E P R E S E N T E D . GENERATE ASSIGN MARK SAVEVALUE TEST G ROOM TEST NE ASSIGN SAVEVALUE ASSIGN SAVEVALUE UNLINK LOOP TRANSFER ZPOSL ASSIGN TABULATE ASSIGN TABULATE LOOP NOWEM SAVEVALUE SAVEVALUE UNLINK TERMINATE t.,.,2.5 1.4 4 WEEK,0,H P4,XHiPWEEK,NOWEM PI,2,NOWEM 5.VISRV0P P5.0.H 5-.1 P5,0,H VtSLUSC,PRFRM,ALL, 1. ROOM ,NOWEM 2, V»H!TBL P2 2-, 1 P2 I,ROOM EMGTM.O.H EMGNO.O.H EMRGC, AFTER «ALL«4, •SINGLE TRANSACTION FOR OR RECORDS •Pl=HOSPITAL SERVICE, 4 IS HIGHEST • TODAY'S DATE IN P4 •DOING THIS WEEK'S OPERATIONS •ON WEEKEND, CNLY EMERGENCIES •DON'T DO SERVICE 2 • P5=SERVICE'S CP TIME SAVEVALUE •SET IT TO 0 •P5 = S ERVICE'S NUMBER OP SAVEVALUE •SET IT TO 0 4,.ZROSL "FOR THIS DATE/SERVICE. REMOVE •DECREMENT SERVICE AND GO TO ROOM • AFTER THE LAST SERVICE *P2 = NUM8ER OF HIGHEST TABLE OF SERVICE •RECORD 0 TIME • SUBTRACT 1 • RECORD 0 PATIENTS •DECREMENT SERVICE AND GO TO ROOM •SET EMERG OP TIME TO 0 •SET EMERG OPERATED NUMBER TO 0 ,ZROEM •ALL TODAY'S EMERG OPN OFF THAT CHAIN • REMOVE INSTIGATING TRANSACTION to 1302 ZROEM TABULATE EMTBN •RECORD 0 PATIENTS 1303 TABULATE EMTBT •RECORD 0 TIME 1304 TERMINATE • REMOVE INSTIGATING TRANSACTION 1305 • 1306 * HERE THE PATIENT'S OPERATION IS ADDEO INTO RECORDS 1307 * 1308 PRFRM PRIORITY 2.BUFFER •RESET PRIORITY 1309 ASSIGN 13,V$SRV0P •P13=SAVEVALUE OF SERVICE OP TIME 1310 SAVEVALUE P13+,Pll,H •ADO LENGTH OF THIS SURGERY I 311 ASSIGN 13 + .1 •P 13=SAVEVALUE OF SERVICE'S OPERATED NO, 1312 SAVEVALUE P13* ,1 ,H •ADD 1 SURGERY 1313 TEST G XH*13,FN242»NOTRN •IF 'LE* 2» PER OR, NO TURNAROUND TIME 1314 ASSIGN 13-,1 • BACK TO TIME SAVEVALUE 1315 SAVEVALUE P13+.15.H •ADD 15 MINUTES TURNAROUND 1316 NOTRN TEST E WtPRFRM.O.NOMR •SOME MORE UNLESS NO MORE UNLINKED 1317 ASSIGN 14,PI • REAL SERVICE OF THIS PATIENT 1318 ASSIGN 1.4 •HIGHEST SERVICE 1319 TAB ASSIGN 13,V $HITBL • P13=NUMBER OF HIGHEST TABLE OF SERVICE 1320 TEST NE PI.2.ONTAB • DCN'T DO SERVICE 2 1321 TEST NE XH*VSSRVOP,0,SKIP • DO\"T RETABULATE IF 0 1322 TABULATE P13 • TABULATE TIME FOR THIS SERVICE 1323 ASSIGN 13- ,1 •SUBTRACT 1 1 324 TABULATE P13 •TABULATE NUMBERS FOR THIS SERVICE 1 325 SKIP LOOP 1 ,TAB • SUBTRACT I FROM SERVICE. GO TO TAB 1326 ONTAB ASSIGN 1.P14 •RESTORE REAL SERVICE 132 7 AFTER PRIORITY 2,BUFFER • RESET PRIORITY 1328 SAVEVALUE EMGTM-.Pll ,H *AOD LENGTH OF SURGERY 1329 SAVEVALUE EMGNO+,l,H •ADO 1 SURGERY 1330 TEST E WtAFTER,0,NOMR •SOME MORE UNLESS NO MORE UNLINKED EMG. 1331 TABULATE EMTBN •TABULATE TODAY'S EMERGENGY OP NUMBER 1 332 TABULATE EMTBT • TABULATE TODAY'S EMERGENGY OP TIME 1333 NOMR TERMINATE 1334 .it****************.******************* 1335 * PRINTER TRANSACTION 1336 1337 GENERATE 91,,91,,2.1 1338 PR I NT . .CN • CLOCK 1339 PR INT ,.U.N . •USER CHAINS 1340 PR INT ..S.N •STORAGES 1341 PR I NT ..O.N ' •QUEUES 1342 PRINT 38.38.T.N •NOBED TABLE 1343 PRINT 1,4,MH,N •SERVICE MATRICES 1344 PRINT 40.41.XH.N •MEDICAL AREA COUNTERS I 345 TERMINATE 1346 1347 * TIMER TRANSACTION 1348 ***** * * * * * * ***************t************ 1349 GENERATE I *CNE PER DAY. LAST THING 1350 TABULATE EMGDU •TODAY'S EMERG AND D.U.PATIENTS 1351 SAVEVALUE EMARR.O.H •RESET FOR TOMORROW 1352 TABULATE NOBEO • TOOAY'S 'NO BEO' CANCELLATIONS 1353 SAVEVALUE NOBO.O.H •RESET FOR TOMORROW 1354 TERMINATE I •REMOVE AND COUNT 1355 * 1 356 START 91,NP 1357 RESET 1358 START 91,NP 1 359 RESET 1360 SAVE • SAVE 1/2 YEAR MODEL 1361 START 91, NP 11362 RESET 1363 START 91.NP 1364 RESET 1365 SAVE 2C 1366 START 91,NP 1367 RESET 1368 START 91, NP 1369 RESET 1370 SAVE 3C 1371 START 91 ,NP t 372 RESET 1373 START 91,NP 1374 RESET 1375 SAVE 4C 1376 START 91,NP 1377 RESET 1378 START 91,NP 1379 RESET 1380 SAVE 5C 1381 START 91,NP 13 82 RESET 1383 START 91 ,NP 1384 RESET 13 85 SAVE 6C 1386 START 91,NP 1397 RESET 1383 START 91,NP 1389 RESET 1390 SAVE 7C 1391 START 91 ,NP 1392 RESET 1393 START 91.NP 1394 RESET 1395 SAVE 8C 1 396 START 91,NP 1397 RESET 1398 START 91,NP 13 99 RESET 1400 SAVE 9C 1401 START 91,NP 1402 RESET 1403 START 91,NP 1404 * 1405 RESET 1406 GENERATE 1...1. 1407 "SAVEVALUE 1-4, 1- 1408 SAVEVALUE CANCL »< 1409 SAVEVALUE 40-41, 1410 TE RMINATE 1411 SAVE 10C 1412 * 1413 END •SAVE 1 YEAR MODEL •SAVE 1 1/2 YEAR MODEL •SAVE 2 YEAR l>CDEL • 2 1/2 YEAR MOOEL •3 YEAR MODEL •3 1/2 YEAR MCDEL •4 YEAR MODEL •4 1/2 YEAR MODEL • END OF 5 YEAR RUN • TRANSACTION TO CLEAR SAVEVALUES •ZERO ACCUMULATED NUMBERS FOR PTS • ZERO CANCELLATION COUNTER •ZERO MEOICAL AREA COUNTERS •SAVE ALSO 5 YEAR MODEL

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