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Grace Hospital computer simulation model Steiner, Stefan 1989

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G R A C E H O S P I T A L C O M P U T E R S I M U L A T I O N M O D E L By Stefan Steiner BMath University of Waterloo A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES INSTITUTE OF APPLIED MATHEMATICS We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA August 1989 © Stefan Steiner, 1989 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that ^he Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. of Department  / ' ^ ^ ^ ^ 0 3 The University of British Columbia Vancouver, Canada Date DE-6 (2/88) Abstract A simulation model, written in GPSS/H, was created to study utilization of Grace Hos-pital, a special-purpose maternity hospital. The model assumes that a patient's transfers and length of stay depend only on her present location and classification, and not on any past history. The model includes a sophisticated overflow policy, and allows the fac-tors used to govern a patient's transfers and length of stay to depend on her treatment stage. Also, to more accurately simulate the mid-morning peak load in the hospital, the length of stay in Postpartum depends on a patient's arrival time in Postpartum. The average census, and the number of patient-days spent in inappropriate units or lost due to overcrowding are determined for several future scenarios. It was concluded that Grace is running very close to capacity, and must continue to limit the number of admis-sions allowed. In addition, an early discharge program was shown to be very effective in alleviating the overcrowding. u Table of Contents Abstract ii List of Tables vi List of Figures ix Acknowledgement x 1 Introduction 1 2 Grace Hospital 6 2.1 Antepartum 7 2.2 Delivery Suite 7 2.2.1 Low Risk 7 2.2.2 High Risk - 7 2.2.3 Operating Rooms 7 2.2.4 Post Anaesthetic Recovery 8 2.3 Postpartum 8 2.3.1 Observation Nursery 8 2.4 Special Admissions and Discharges Policies 9 2.5 Normal Flow Through Grace - 9 3 Data Collection and Analysis 11 3.1 Adults 13 in 3.2 Babies 15 4 Computer Simulation of Grace Hospital 17 4.1 Classification of Adult Patients 17 4.1.1 Delivery Type 18 4.1.2 Geographical Region 18 4.1.3 Antepartum Complications 19 4.1.4 Postpartum Complications 20 4.2 Classification of Babies 21 4.3 Physical Divisions and Overflow Procedures 22 4.3.1 Antepartum modules 22 4.3.2 Low Risk 23 4.3.3 High Risk 23 4.3.4 Operating Rooms 23 4.3.5 Post Anaesthetic Recovery Room 24 4.3.6 Postpartum Modules 24 4.3.7 Observation Nursery 24 4.3.8 Low Risk Nursery, High Risk Nursery, Postpartum Nursery . . . . 24 4.4 Logical Division of Grace in the Model 25 4.4.1 Antepartum section 26 4.4.2 Delivery Suite 27 4.4.3 Postpartum section 27 4.5 How the Model Runs 29 4.5.1 Admissions 29 4.5.2 Determining an Adult Patient's Path Through the Hospital . . . . 31 4.5.3 Determining a Babies Path Through the Hospital 32 iv 4.5.4 Discharges 32 5 Verification and Validation 37 6 Experimentation and Results 46 6.1 Increasing the Load 47 6.2 Increase the Proportion of Patients from Outside Vancouver 49 6.3 Decrease the Average Length of Stay 50 6.4 Eliminate the Preregistration Cap 51 7 Summary and Conclusion 53 Bibliography 55 Appendices 59 A Data Analysis Tables 59 B Model Output Description 88 C Output From Standard Run 99 D The Grace Hospital Simulation Model Code 128 v List of Tables 5.1 Verification of Total Patients 40 5.2 Verification of Delivery Type Classification 40 5.3 Verification of Geographical Residence of Patients 41 5.4 Verification of AP Classification 41 5.5 Verification of PP Classification 41 5.6 Verification of Baby Classification 41 5.7 Verification of Length of Stay Averages 42 5.8 Verification of Number of Entries 42 5.9 Validation of Total Length of Stay (minutes) 43 5.10 Validation of Census and Utilization 44 6.11 Experiment 1A : Decreasing the Number of Days per Month 48 6.12 Experiment IB : Increasing the Number of Patients per Month 49 6.13 Experiment 2 : Increasing the Proportion of Patients from Outside Van-couver 50 6.14 Experiment 3 : Decrease the Average LOS in PP 51 6.15 Experiment 4 : Eliminate the Preregistration Cap 51 A. 16 Arrival Time of Day for Adult Patients 59 A.17 Arrival Day of Week for Adult Patients 60 A.18 Total LOS by AP Category 61 A. 19 Total LOS by Delivery Type 62 A.20 Total LOS by Geographical Residence 62 vi A.21 Total LOS by PP Complication 63 A.22 Total LOS by Sterilization 63 A.23 Antepartum LOS by AP Category 64 A.24 Antepartum LOS by Delivery Type 65 A.25 Antepartum LOS by Geographical Residence 65 A.26 Antepartum LOS by PP Complication 66 A.27 Antepartum LOS by Sterilization 66 A.28 Delivery Suite LOS by AP Category 67 A.29 Delivery Suite LOS by Delivery Type 68 A.30 Delivery Suite LOS by Geographical Residence 68 A.31 Delivery Suite LOS by PP Complication 69 A.32 Delivery Suite LOS by Sterilization 69 A.33 Postpartum LOS by AP Category 70 A.34 Postpartum LOS by Delivery Type 71 A.35 Postpartum LOS by Geographical Residence 71 A.36 Postpartum LOS by PP Complication 72 A.37 Postpartum LOS by Sterilization 72 A.38 Discharge Day of Week for Adult Patients 73 A.39 Discharge Time of Day for Adult Patients 74 A.40 Delivery Type by Geographical Residence 75 A.41 Delivery Type by AP Category 76 A.42 Delivery Type by PP Complication 77 A.43 Delivery Type by Sterilization 78 A.44 Geographical Residence by AP Category 79 A.45 Geographical Residence by Delivery Type 79 A.46 Geographical Residence by PP Complication 80 vn A.47 AP Category by PP Complication 81 A.48 AP Category by Sterilization 82 A.49 PP Complication by Sterilization 82 A.50 Total LOS Newborns Versus Pediatric Babies 83 A.51 Total LOS by Birthweight 83 A.52 Total LOS by Gestational Age 84 A.53 Total LOS by APGAR score . 84 A.54 Total LOS by New Baby Classification 85 A.55 New Baby Category by Mother's Antepartum Category 86 A.56 New Baby Category by Delivery Type 87 vm List of Figures 2.1 Typical Flow of Patients in Grace 10 4.2 Antepartum Section With Patient Paths 26 4.3 Delivery Suite Showing Patient Flows 28 4.4 Postpartum Section with Patient Flows 28 4.5 The Admissions Process 30 4.6 Adult Patient Movement Procedure 33 4.7 Baby Movement Procedure 34 5.8 Initialization Length Test 38 5.9 Steady State at Different Load Levels 39 ix Acknowledgement I would .like to thank my supervisor professor D. Uyeno who gave me constant support and guidance throughout the entire project, and professor S. Brumelle for his careful reading and helpful comments. In addition, I would like to thank all the staff at Grace hospital for their helpful support, but especially Dr. C.L.T. Galbraith, Medical Director, Heather Kennedy, Man-agement Information Systems, Sue Joly, Supervisor Admitting, Dr. Sidney Effer, Head Fetal/Maternal Medicine, Carol Mitchell, Director Observation Nursery and Postpartum, Karen Brennan, Director Antepartum, Fran Martin, Director Delivery Suite, Joyce Tate, and Jackie Toms, Assistant Directors Delivery Suite, and Lynda Hamblin, Assistant Ex-ecutive Director Patient Services. Most of all, thanks goes to AnneMarie for her sustained support and encouragement during this long project. x Chapter 1 Introduction The rising cost of health care is forcing hospitals to make better use of existing facilities and to justify new acquisitions. As a result, hospital administrators are interested in predicting bed requirements and studying the effects of various management policies such as restricted admissions, early discharge programs, and resource reallocation. When determining a hospital's bed requirements, hospital managers must always balance the desire for improved utilization with the need to provide a "high level" of service to patients. The tools available to aid in this decision making process include rules of thumb, analytic models, and simulation models. Maternity hospitals in particular are good candidates for models since they are usually self contained and treatment has well defined stages. Rules of thumb are the first method used to predict hospital bed requirements. These rules simply use past experience to dictate the number of beds needed by a given popula-tion. This method results in very crude estimates that ignore both the individual nature of each hospital, and the effects of varying management policies. Analytic models use a stochastic process to represent the hospital, and describe pa-tient movements and resource utilization. These models generally fall into 3 classes: simple probabilistic models, queuing models, and Markov models. Probabilistic arrival models (Cowan [7], Slutsky [28], Swartzman [29]) are concerned only with predicting admission demand. Both Cowan and Slutsky estimated the arrival load at maternity hospitals assuming a Poisson arrival distribution. Such probabilistic 1 Chapter 1. Introduction 2 models do not take into account the effects of varying admission policies. However, such models may be useful to predict input levels for more detailed models. Queuing models, (Young [36], Shonick [27], Milliken [19], Weiss et al. [35], Thompson et al. [31]), assume that a hospital is a single service unit. As a result, queuing models, like probabilistic models, fail to take into account the progression of patients through the various sections of a hospital. Also, these models do not consider a patient's diag-nosis, nor do they have a mechanism for dealing with finite capacity or with overflow situations. However, queuing models can be effective for studying certain aspects of a hospital, such as the patient arrival process, in isolation from the workings of the whole hospital. Queuing models of maternity hospitals include Milliken et al. who predicted the utilization of delivery rooms. Markov models are developed with the underlying assumption that the movement of patients from state to state is only dependent on the current state, and not on any past history. Markov models include, Thomas [30], Pendercast et al. [21], and Lane et al. [18]. The basic Markov assumption that a patient's past history has no effect is inappropriate for most hospital systems (Fetter & Thompson [11]). However, coronary and maternity services may be exceptions due to their well defined treatment phases (Weiss et al. [15], [34], Thomas [30]). Markov models ignore many of the intricacy of a hospital functioning. Semi-Markov models are similiar to Markov models, but allow the time between state changes to be a random variable. Using a semi-Markov model, Kao [16] was able to simplify Thomas' model. Similar models include those by Kao [17], Weiss, Cohen, and Hershey [15],[34]. Semi-Markov models of maternity hospitals include Weiss et al. [34]. Analytic models produce closed form solutions and can be effective tools for man-agement. However, in most cases to achieve this form of solution many simplifying assumptions must be made. Analytic models ignore the interactions among services by assuming infinite capacity. Also, analytic models usually do not have enough procedural Chapter 1. Introduction 3 detail in terms of patient categories and admission/discharge policies. In many cases this simplification results in models that are not applicable, or are unable to simulate the effects of changing a particular management policy of interest. Computer simulations allow much more detail than analytic models. They can accu-rately model complex real-world decision processes, and easily estimate the performance of an existing system under projected operating conditions. The first computer simulation of a hospital is attributed to Fetter & Thompson [32],[11],[33],[12]. This series of influential papers includes models of a maternity suite, an outpatient clinic, a surgical pavilion, and a model of a whole hospital. These mod-els were developed to study the effects of increasing the number of patients, shortening length of stay, the relationship between size and costs, and the economic implications of single rooms. The models are quite simple in nature. Patients are pre-assigned paths through the hospital, and holding times are determined only as a function of the path and the present node. In addition, these models fail to differentiate patients by diagnosis. Although they can detect the incidence of blocked transfers due to overflow situations, there is no mechanism to handle such transfers. Other models developed around the same time include those by Barr & Oddie [1], who studied bed distribution and admission policies, Fischer [13], who simulated two maternity hospitals to study the effect of dual appointments, Goldman [14], who studied bed allocation policy, Robinson [24], who looked at scheduling admissions, Beaver [2], who looked at the effects of early discharges, Duchessi [8], who predicted the cost impact of patient load and/or service mix changes, and Rising et al. [23] who modeled an outpatient clinic. Like the Fetter & Thompson simulations all of these models make many simplifying assumptions and do not consider the effect of blocked transfers or admissions waiting, going elsewhere, or preempting another patient. Early computer simulations of obstetric hospitals include Fisher [13], Barr &; Oddie [1], Beaver [2], and Chapter 1. Introduction 4 Fetter & Thompson [32],[11]. Many of these early models suffer the same drawbacks as analytic models. They either fail to classify patients ([1],[2],[11],[32]) or do not handle overflow ([13]). Also, none of the models deal adequately with special admissions and discharges. As well as these models, tools to aid the creation of models have been developed. Fetter & Mills [10] created a special simulation language, HOSPSIM, to simplify the programming of blocked transfer policies. However, there is no reported use of this capability analysing the impact of finite hospital capacity. Raz et al. [22] created DRUMS, a simulation tool that forecasts the daily demand for various resources in the hospital based on a projection of the patient volume and the proportion of patients with a similar diagnosis, but fails to take into account the intricacies of a particular hospital. Two recent more sophisticated simulation models are Cohen et al. [5], and Dumas [9]. Dumas modeled a large multi-purpose hospital. He showed that the interactions among services in terms of overflows has a significant effect on the optimal bed alloca-tion. Dumas' model also showed the effects of severly restricting off-service placements. However, Dumas assumes that unless originally misplaced patients stay in their initial assigned bed. This is not applicable to the progressive patient care setting of a mater-nity hospital. In addition, restricting off-service placements is not feasible in the case of non-elective medical care such as obstetrics. The paper by Cohen et al. provides a methodology for modeling progressive patient care hospitals. Cohen et al. assume that transfers and length of stay depend only on the current state, and the patient category unless capacity is reached. They provide a simple illustrative model that simulates the recovery process of coronary patients. Both'these models are quite detailed, but are difficult to generalize for other hospitals. This paper develops a model of a maternity hospital in the framework described by Cohen et al. However, to accurately model a maternity hospital a number of extensions Chapter 1. Introduction 5 were required. First, because of the well defined stages of obstetric treatment, patients were classified according to more than one criterion. As a patient moves from one stage of treatment to another the classification that governs the transfers and length of stay (LOS) also changes. Second, some of the length of stay calculations reflected the time of day. This was necessary to simulate the staggered discharge distribution that results from the vast majority of patients leaving the hospital between 11 a.m. and 3 p.m. r Chapter 2 Grace Hospital Grace Hospital, located in Vancouver, B.C., is a unique special-purpose health care institution administered by the Salvation Army as delegated by the British Columbia Ministry of Health. Grace is the only tertiary obstetric facility in B.C. and as such has critical responsibilities in service, education, and research. It serves as a referral centre in the province for the most complex conditions of pregnancy, along with sharing the responsibility of caring for conditions of pregnancy of intermediate complexity with a number of other facilities in the lower mainland. In addition, Grace collaborates with St. Paul's hospital to provide general maternal and newborn care for the Vancouver community. Since opening its new facility in 1982, the hospital has experienced workloads much higher than its design originally intended. It is now the busiest obstetric hospital in Canada with over 8000 births per year. Grace, as a special-purpose maternity hospital, is a progressive care facility since patients move through the different units of the hospital as their pregnancy progresses. Grace also has strong bed typing since patient care and location are intimately related. As a result, there is little flexibility in terms of policies to deal with overflows. A simulation model was needed to help administrators evaluate the various policies that may help alleviate the crowding. This chapter explains the physical division of Grace into three areas: antepartum, delivery suite, and postpartum, and some special admissions and discharge policies unique to Grace. In addition, an illustrative example showing the usually progression of patients is given. 6 Chapter 2. Grace Hospital 7 2.1 Antepartum The antepartum (AP) section provides health care and psycho-social, socio-economic and life skills programs to assist high risk acute and long-term care patients during their pregnancy. Antepartum consists of 2 modules, Holly with 26 beds in 13 double rooms and Dogwood with a variable number of beds, depending on the load, up to a maximum of 16. 2.2 Delivery Suite The delivery suite (DS) provides care to women throughout the labour and delivery process, in addition to caring for those patients requiring perinatal intensive care, surgery and post anaesthesia recovery. The delivery suite consists of 4 areas: low risk delivery, high risk delivery, the operating rooms, and the post anaesthetic recovery rooms. 2.2.1 Low Risk The low risk delivery suite is for patients with no complications. It consists of 11 birthing rooms (labour and delivery occurs in the same room), and 4 rooms used for assessment. 2.2.2 High Risk The high risk delivery suite is for patients who have some complication but do not require any surgery. High risk has 4 regular birthing rooms, and 4 intensive care rooms. 2.2.3 Operating Rooms There are 3 available operating rooms at Grace (a 4th is currently used for storage). These operating rooms are used for Caesareans, sterilizations, and all antepartum complications, Chapter 2. Grace Hospital 8 and postpartum complications requiring surgery. Two of the operating rooms are reserved for emergencies, and the other handles all elective surgery. 2.2.4 Post Anaesthetic Recovery The post anaesthetic recovery room is used for recovery after surgery and has 4 beds. 2.3 Postpartum The postpartum (PP) area provides care for mothers and newborns recovering from the delivery process. Postpartum consists of 6 modules: Arbutus, Balsam, Cedar, Dogwood, Evergreen, and Fir, and the observation nursery. Each postpartum moldule consists of 15 or 16 beds (2 double rooms and 11 or 12 single rooms) for mothers, and 15 or 16 bassinets for newborn. 1. Arbutus - 16 beds and 16 bassinets 2. Balsam - 15 beds and 15 bassinets 3. Cedar - 16 beds and 16 bassinets 4. Dogwood - 16 beds and 16 bassinets (this module is shared with AP patients) 5. Evergreen - 15 beds and 15 bassinets 6. Fir - 16 beds and 16 bassinets 2.3.1 Observation Nursery The observation nursery has 10 bassinets and provides care for both infants requiring additional observation the first few hours after birth, and infants needing extended sec-ondary level care (tertiary level care for newborn is provided at Sick Children's Nursery Chapter 2. Grace Hospital 9 in Children's Hospital). 2.4 Special Admissions and Discharges Policies Grace Hospital uses a preregistration system in an attempt to limit the number of mothers coming to deliver each month. Patients must register months ahead of time to request a place at Grace. Because of Grace's position as a tertiary care facility, all "high risk" patients are automatically granted a place. The remainder is filled up by "low risk" patients. In this manner the number of mothers coming to Grace to deliver is effectively limited to about 625 per month. Grace's preregistration system affects the whole region of Vancouver since the patients not admitted to Grace must go elsewhere. See the chapter on experiments for more analysis on this interesting situation. Grace has implemented a discharge flag system to inform doctors of the utilization of the PP modules. The flag condition is visibly displayed around the hospital and updated at 8 a.m. , 12 noon, 4 p.m. , and 10 p.m. A red flag situation means there are fewer than 15 beds unaccounted for in the PP modules, and doctors are strongly encouraged to immediately discharge any patient who can safely go home. A yellow flag means there are between 16 and 19 beds available, and a green flag signifies no crowding problem with more than 20 beds available. Beds are considered free if they are both presently unoccupied, and not assigned to a patient presently in the delivery suite. Hospital administrators feel that 15 beds is the minimum that ideally should be available at any time to insure adequate flexibility in case of a sudden large influx of patients. 2.5 Normal Flow Through Grace A typical patient preregisters before her 20th week of gestation. All the patients accepted will deliver in the delivery suite. Patients who have a vaginal delivery stay on average Chapter 2. Grace Hospital 10 • d m for antftpartBB (100/ionth) 181 >d>n for dallvtry (630/ionth) •<l»it for postpartum (10/ioath) Aatopartna an ESI 0«li»«ry Btlto Poitpartni dlacharf» Figure 2.1: Typical Flow of Patients in Grace 8-11 hours in low or high risk. Patients who have caesareans (about 22% of the total) deliver in the operating room, staying on average 1-2 hours in the operating room, and 2-3 hours in the post anaesthetic recovery area. The typical postpartum stay is 3 days for vaginal deliveries, and 5 days for caesareans. In addition to this, a third of the patients at Grace at any time are there for an antepartum complication, staying an average of 5-6 days if they are discharged before delivering (they are later re-admitted to deliver), and 2-3 days if they deliver before being discharged. The major adult patient flows are shown in Figure 2.1 Babies proceed from the delivery suite to either a postpartum nursery or the observation nursery, staying usually only until their mothers are ready to be discharged. Chapter 3 Data Collection and Analysis Although Grace Hospital collects a large amount of information on its day to day op-erations there is little central coordination of this data. Each department collects any utilization data it needs, but often the form of this data varies from department to de-partment making comparisons difficult. For example, Postpartum counts the number of days the treatment rooms are used and Antepartum calculates total patient days. The Management Information Systems (MIS) department at Grace has implemented a sys-tem that stores some of the most important information on computer, but at present it is a labourious task to obtain anything other than simple summary statistics. To create the Grace Hospital simulation model it was necessary to combine two data files— one containing patients' personal statistics, medical history and diagnosis, and the other file containing a log of all transfers through the hospital. Transfers entered into the computer are assumed to take place at the present time. However, in practice transfers are often not entered until a later time when the unit clerk is free. Also, the computer is down every day from 2 a.m. to 4 a.m. As a result, the patient transfer data was of poor quality and needed to be corrected. Handwritten records were superior because of the greater flexibility of entry. The computer is operated only by the unit clerk, whereas anyone can fill out the handwritten log. At present, the partial computerization causes some dupli-cation in the data collection. Once a reliable and flexible computer system is in place many of the current problems in data collection will be reduced. When compared with the handwritten records, about 20% of the patients in the computer log were found to 11 Chapter 3. Data Collection and Analysis 12 require some modification. As a result of this time consuming correction, only 2 months of data were used to create the model, namely July and August of 1988. This amount of data reflected over 1200 births and was enough to create the model. However, there is an implicit assumption in using this data to create a model. The length of stay (LOS) and transfers are assumed to reflect the ideal operation of the hospital, i.e. they are assumed to not be subject to capacity constraints. Fortunately July and August 1988 were relatively slow months. Therefore, the limited capacity effect is minimized in the data. The first step in analysing the data was to determine which characteristics of the patients affect their transfers and length of stay in the hospital. Brooks et al. [4] using multiple regression and 117 factors to group patients predicted bed needs. Many studies, especially those concerned with generating cost estimates, group patients according to diagnosis related groups (DRG). DRGs were developed by Fetter to produce groups of patients homogeneous with respect to some measure of resource usage. More recently, Schachtman et al. [26] suggested a case mix adjustment index for increased flexibil-ity. After consulting with Dr. Effer, head of Maternal and Fetal Medicine at Grace, the following factors were considered likely to be important. For adults, antepartum (AP) complications, delivery type, postpartum (PP) complications, location of residence, and whether or not a sterilization was performed were considered potentially significant. For babies, the characteristics examined were birth weight, gestational age, APGAR score (a medical measure of newborn health), and whether the baby is a newborn or a pedi-atric patient. It was also of interest to determine which of the adult characteristics are correlated, and which characteristics are the best predictors of their baby's health. To illustrate the manner in which the categories were chosen, consider AP complications. Dr. Effer initially suggested 9 major categories of AP complications. After examining the data it became clear that 2 of the categories, renal, and multiple births, were too small Chapter 3. Data Collection and Analysis 13 and needed to be combined with the "Other AP complication" category. In addition, a reworking of the "no significant complication", "other complication" distinction was needed due to the large number of minor complication initially classified as "other". In the following analysis the Cramer's V is used as a measure of the degree of association between characteristics. Cramer's V is based on the chi-square value, but minimizes the influence of sample size and degrees of freedom. As a result, it can be used to compare the strength of assocation of various characteristics. Cramer's V always lies between 0 and 1, with values close to 1 showing a strong assocation. 3.1 Adults Since the preregistration system at Grace (see section 2.4 for more information) differenti-ates between patients who deliver and those admitted only for AP or PP complications it was best to generate arrivals in the model by delivery type. Examining the arrival pattern (time of day Table A.16, day of week Table A.17) it is evident that day of surgery (DOS) patients have a special arrival pattern, whereas all the other patients arrive uniformly throughout the day and week. The DOS patients arrive for scheduled caesarean sections, and they usually arrive Monday to Thursday between 6 a.m. and 2 p.m. A chi-square test strongly suggests that the interarrival time of all the patients, except the DOS mothers, is exponential. For each delivery type except DOS, the hypothesis of similarity could not be rejected at the 0.20 level. This duplicates past results [31],[2],[32],[7]. In other words, this means the arrival rate is a Poisson process, and arrivals are random events. This is a reasonable conclusion since the delivery process is very unpredictable, and labour does not wait until a convenient time to start. Of the five factors used to differentiate adult patients, delivery type was the best predictor of the total LOS in the hospital (see Tables A.20 to A.22). The Cramer's V for Chapter 3. Data, Collection and Analysis 14 delivery type was 0.4, whereas for AP complication, the next best predictor, it was 0.16. However, when making a physical distinction in Grace between the antepartum, delivery suite, and postpartum areas, the situation was more complicated. The AP complication had the strongest assocation measure with AP length of stay (Tables A.23 to A.27). AP complications, preterm labour, AP hemorrhage, and diabetes tended to have particular long lengths of stay. However, there is also a significant difference in AP LOS between undelivered and delivered patients (Table A.24). In addition, patients from B.C. also had longer AP lengths of stay, but this can be explained by their higher incidence of AP complications. In the delivery suite, the delivery type is clearly the best predictor of LOS (Cramer's V of 0.32 versus 0.15 for AP complication, Tables A.28 to A.32). Patients who have elective C-section stay the least time (since they arrive for scheduled surgery), and patients who have emergency C-section stay the longest. In postpartum, delivery type has the strongest assocation with PP length of stay (Cramer's V of 0.40, tables A.33 to A.37). However, PP complication also has an effect (Table A.36). Transfers among the 3 areas of the hospital are also affected by the classifications. For example, patients with some AP complication are far more likely than those with no complications to enter the AP. In the delivery suite, almost all vaginal births occur in low or high risk, whereas C-sections all deliver in the OR, and patients with a PP complication are more likely to visit the OR after delivering. Sterilizations are much more common for patients having an elective C-section or an instrumental birth (see Table A.43). But, since all C-section patients already have to recover from surgery (sterilizations are performed at the same time as the caesarean) sterilizations have little effect on LOS (Table A.22). For vaginal deliveries, the number of sterilizations is also reflected in the proportion of patients who transfer to an operating room after delivering. The factors used to classify adult patients are quite correlated. A patient's delivery type can be used as a predictor of all the other factors (Tables A.40 to A.43). A patient's Chapter 3. Data- Collection and Analysis 15 geographical residence is correlated with her delivery type and AP category, but does not influence sterilizations or PP complications (Tables A.44 to A.46). Her AP category is correlated with her delivery type and geographical residence, but not with whether she will have a sterilization or a postpartum complication (Tables A.47 and A.48). Finally, whether a patient has a PP complication or not does not influence whether she will have a sterilization (Table A.49). Discharge times of the adult patients was not random (Tables A.38 and A.39). The majority of discharges occur during the day, most from 11 a.m. to 3 p.m. This is no surprise since patients usually leave at their convenience. 3.2 Babies The analysis of the data collected about babies was more straightforward. They were classified by their health. Because the Sick Children's Nursery (the tertiary care nursery) is in another hospital, the most seriously ill babies are immediately discharged from Grace. To avoid this very short LOS from skewing the results, a special category of newborns was needed, namely "Short Stay" (less than 2 hours in Grace). In addition, a separate category for pediatric babies was needed. Pediatric patients have both a different arrival procedure and a much longer average LOS than newborns, (see Table A.50). Pediatric babies tend to stay longer because they must be ill to require re-admission. The remaining analysis used standard medical divisions of the health characteristics. Birthweight was divided into two classes: greater than 2500 grams and less than 2500 grams, gestational age was divided into two classes: greater than 37 weeks and less than 37 weeks, and the APGAR scores were divided into three categories: 0-3, 4-6, 7-10. All these health characteristics are highly correlated. For example, low birthweight babies tend to result from deliveries at an early gestational age, and also have a low Chapter 3. Data, Collection and Analysis 16 APGAR score. However, the analysis shows that birthweight (Cramer's V of 0.21), and gestational age (0.27) are much better predictors of LOS than APGAR score (0.11). These are results are shown in Tables A.51 to A.53. This result was confirmed when presented at a meeting of the nurses' executive. The nurses felt that the APGAR score was a very subjective measure and of little value. As a consequence, a combination of the birthweight and gestational age (combining small categories) were used to predict the LOS for the non "Short Stay" newborns. (Table A.54). All newborns are admitted at delivery, but pediatric babies arrive on their own. The pediatric babies' inter-arrival time distribution fits an exponential distribution very well (like the adult patient's arrival distibution). After determining which baby health classifications to use it was important to deter-mine which aspects of a mother could best predict their baby's health. Trying both AP category (Cramer's V of 0.35) and delivery type (Cramer's V of 0.05) it is obvious that the AP category is by far the better predictor (see Tables A.55 and A.56). Chapter 4 Computer Simulation of Grace Hospital The Grace hospital simulation model consists of 2700 lines of GPSS/H code. It is a model of the inpatient flow through Grace Hospital that allows the user to investigate how changes in the hospital would effect the resource utilization. The data input for the model includes arrival rates, transfer tables, and holding time distributions for all the patient categories. The model assumes that for an infinite capacity hospital transfers and LOS depend only on a patient's category and present location (and arrival time in some special cases), but not on their past history. However, as capacity is reached the occupancy of the various units will affect patient movements. As overflow, patients may transfer to different locations or have their LOS shortened (see section 4.3). This chapter explains the inner workings of the model: the patient classifications, the physical divisions, and the logic used to create and run the model. See appendix C for a sample output, and appendix D for a complete listing of the code. 4.1 Classification of Adult Patients Adults are classified in four ways. They are assigned a delivery type, a code for their place of residence, an antepartum condition, and a postpartum condition. There are on average 730 patients per month at Grace (620 patients who deliver and 110 AP-only or PP-only patients). The number following each category name gives the percent of this total that category represents. 17 Chapter 4. Computer Simulation of Grace Hospital 18 4.1.1 Delivery Type The following are the possible delivery types in the model. 1. spontaneous delivery - 50% 2. instrumental delivery (includes all forcep deliveries, vacuum extractions, and as-sisted breech deliveries) - 13% 3. elective caesarean section (includes day of surgery patients and regular arrivals) -8.5% 4. emergency caesarean section - 13% 5. undelivered (PP-only) - 1.5% 6. undelivered (AP-only) - 14% Abortions are ignored in the model because at Grace they represent only about one patient per month. A patient's delivery type governs the admission procedure (see sec-tion 4.5.1), and all her transfers and length of stays in the delivery suite section. In addition, the distinction between patients who will deliver and AP-only patients is im-portant in the AP section. 4.1.2 Geographical Region Patients are classified according to their place of residence. 1. Vancouver School District # 37 - 54% 2. Greater Vancouver Regional Health District (not including school district # 37) -36% Chapter 4. Computer Simulation of Grace Hospital 19 3. British Columbia (not including GVRHD) - 10% The geographical region is assigned as function of the delivery type, and is used only to determine (in conjunction with the delivery type) a mother's AP category. The geographical code is important because mothers who come to Grace from far away tend to be more ill and thus are more of a burden on the hospital. Grace, as a tertiary care centre, is obliged to accept all "high risk" patients. The high/low risk distinction must be with a preliminary diagnosis which is not always a good predictor of a patient's future problems (in fact, the "high risk" diagnosis list is outdated and is presently under review at Grace). However, at Grace, once a patient arrives the low/high risk distinction is lost. Geographical residence is correlated with higher risk and this relationship is reflected when a patient's AP category is determined. Including the geographical region as a factor in the model allows for experiments to study the effect of increasing the proportion of patients not from Vancouver coming to Grace. This indirectly causes the "high risk" proportion to also increase. 4.1.3 Antepartum Complications The following is a list of the antepartum conditions used in the model. 1. no antepartum complication or no significant AP complication (i.e. no AP compli-cation that effects LOS in the hospital) - 39% 2. preterm labour - 6% 3. premature rupture of membranes - 13% 4. intrauterine growth retardation (IUGR) - 5 to 6% 5. pregnancy induced hypertension - 6 to 7% Chapter 4. Computer Simulation of Grace Hospital 20 6. diabetes (insulin dependent diabetic mother - IDDM & gestational diabetes) - 5 to 6% 7. antepartum hemorrhage - 5% 8. other significant antepartum complication (includes twins, triplets, renal disease, urinary tract infections and many others) - 19% Antepartum conditions are randomly assigned by functions which depend on a mother's previously assigned delivery type and geographical code. The antepartum condition is used in the model to determine transfers and LOS while a mother is in the antepartum subsection of the hospital (see next section for clarification of the antepartum subsec-tion). In addition the AP condition controls the destination of the initial transfer into Grace for all mothers except those who have either come as day of surgery patients or postpartum only patients. 4.1.4 Postpartum Complications The following is a list of postpartum (PP) complications. A PP complication includes hemorrhages, infections, and other significant complications. 10 to 11% of patients who deliver have some PP complication. But, the percentage varies by delivery type. With instrumental and emergency C-sections having the highest rates. 1. spontaneous delivery without PP complication - 54% 2. spontaneous delivery with PP complication - 4.5% 3. instrumental delivery without PP complication - 12.5% 4. instrumental delivery with PP complication - 2.5% 5. elective C-section without PP complication - 9% Chapter 4. Computer Simulation of Grace Hospital 21 6. elective C-section with PP complication - 1% 7. emergency C-section without PP complication - 12.5% 8. emergency C-section with PP complication - 2.5% 9. postpartum only - 2% A mother's PP category controls her transfers from and in the PP subsection, and her LOS in the PP subsection (see next section for a clarification of PP section). The PP category is determined by using the delivery type and randomly choosing a percentage of mothers to have some PP complication The number of mothers in the PP-only category was too small to divide according to the presence or absence of a PP complication. 4.2 Classification of Babies There are five categories of babies used in the model. 1. less than 2500 grams birthweight - 5% 2. greater than 2500 grams birthweight and less than 37 weeks gestational age - 10% 3. greater than 2500 grams birthweight and greater than 37 weeks gestational age -79% 4. short stay (less than 2 hours in Grace) due to transfer to Children's Hospital - 4% 5. pediatric (i.e. not a newborn, returning baby previously discharged from Grace) -2% A baby's classification is a function of their mother's AP category, and controls all the transfers and length of stays of that baby in the hospital. Twins and triplets are Chapter 4. Computer Simulation of Grace Hospital 22 assigned a category taking into account the lower birthweight of most multiple birth babies. Short stay is a special category that had to be included for very sick babies since they are immediately transfered to Sick Children's Nursery in Children's Hospital (located next to Grace). 4.3 Physical Divisions and Overflow Procedures The physical divisions and overflow procedures used in the model resemble Grace Hospital as much as was feasible without going into unnecessary detail. Overflow refers to the situation of patient demand outstripping the resources of the simulated hospital. In most cases, the different areas in Grace have policies reflecting what occurs if a new patient requires care but there is no more space available. The overflow procedures were determined through interviews of hospital staff. There are three different overflow strategies used at Grace. A patient may go to an alternative location where they can receive similar care (HIGH and PAR use this strategy). Patients may temporarily stay in an overflow area, moving to the desired location as soon as possible (used in LOW and PP). Finally, as a last resort, overflows may cause the patient who has the least time remaining in the full area to be moved prematurely to their next location (used in LOW, HIGH, PAR, and PP). This bumping is rare in the regular operation of the hospital. If bumping increases significantly the model will still run, but patient services deteriorate. Patients may no longer be staying in their desired locations long enough to receive the care they need. 4.3.1 Antepartum modules There are two antepartum modules: Holly with 26 beds, and Dogwood with up to 16 beds. Antepartum patients are first placed in Holly. Any additional patients arriving Chapter 4. Computer Simulation of Grace Hospital 23 take up as much room in Dogwood as required, displacing a PP patient in Dogwood to another PP module if necessary. If both Holly and Dogwood are full with AP patients (a rare occurrence), new AP patients are put in Evergreen, again displacing PP patients to another PP module if needed. 4.3.2 Low Risk Low risk consists of two separate areas in the model: low risk delivery area with 11 rooms, and the assessment area (ASESS) with 4 rooms. If the 11 rooms in low risk are full, patients are put in one of the assessment rooms temporarily until a low risk room is free. If both low risk and the assessment rooms are full a new patient is temporarily placed in the PAR. If low risk, ASESS, and PAR are full when a new patient arrives the patient presently in low risk who has the least time remaining will be prematurely moved to their next location. 4.3.3 High Risk The model groups all the high risk beds together with the intensive care beds for a total of 8 places in high risk. If all the high risk beds are occupied a new patient will be sent to low risk instead. If both high risk and low risk are full when a new patient arrives the patient presently in high risk who has the least time remaining will be prematurely moved to their next location, thus freeing up a spot for the new patient. 4.3.4 Operating Rooms As in the Grace, the model has 3 operating rooms. There is no overflow area for the OR, but all non emergency procedures (including all antepartum and postpartum OR visits, and non emergency deliveries) are delayed if there are fewer than 2 ORs free. Any Chapter 4. Computer Simulation of Grace Hospital 24 delayed surgical patient waits in their present location until enough ORs are free. 4.3.5 Post Anaesthetic Recovery Room The post anaesthetic recovery area has 4 beds. Overflow from the PAR goes to high risk if possible. If high risk is also full the patient with the least time remaining in the PAR is prematurely moved to their next destination. 4.3.6 Postpartum Modules Postpartum consists of 6 individual modules (Arbutus, Balsam, Cedar, Dogwood, Ever-green, Fir) with 15 or 16 beds each, and a 6 bed treatment room called TREAT (in the hospital each module has a treatment bed). Overflow from the PP modules is rerouted to TREAT. Patients stay in TREAT only until a bed becomes free in the PP modules. If the PP modules and TREAT are full, the next scheduled to leave is prematurely sent to their next destination thus freeing up a bed in the PP modules. 4.3.7 Observation Nursery The observation nursery (OBN) has 10 bassinets. Babies arriving to find the OBN full cause the baby with the shortest time remaining to be prematurely sent to its next location. 4.3.8 Low Risk Nursery, High Risk Nursery, Postpartum Nursery The low risk nursery (LRN), and the high risk nursery (HRN) are very flexible in terms of the number of babies they can accommodate. In the model they have places for 11 and 8 babies respectively (the same as low risk and high risk delivery areas). The postpartum nursery (PPN) is similar: it is divided into six different nurseries (one for Chapter 4. Computer Simulation of Grace Hospital 25 each PP module) with 15 or 16 bassinets each. LRN, HRN, and PPN have no overflow procedures because they are never totally full. Babies stay in LRN and HRN for only short periods of time, and the PPN has the flexibility to add more bassinets if it becomes busy. 4.4 L o g i c a l D i v i s i o n o f G r a c e i n t h e M o d e l The simulation model divides Grace into three logical units: antepartum (AP), the de-livery suite (DS), and postpartum (PP). This is similar to the physical division of Grace, but some additional distinctions are made to account for differences in LOS between patients in different phases of maternity. Low risk and high risk are logically divided into low/high risk for deliveries and low/high risk moving next to antepartum. In addition it was necessary to logically partition the OR and PAR depending on whether a mother is delivering, moving next to the antepartum subsection, or proceeding to postpartum. This logical partition means a mother's stay in low/high risk or the OR or PAR uses the same facilities and overflow procedures but the LOS and transfers are governed by a dif-ferent criterion. For example, a mother entering low risk from the antepartum subsection (perhaps for false labour, i.e. she will not delivery this stay), has her LOS and subsequent transfer controlled by her AP classification. On the other hand, patients entering low risk to deliver have their LOS and transfer controlled by their delivery type. All transfer and LOS functions were created empirically from the data gathered at Grace. This way both the transfers and LOS functions could reflect some very rare events simply by assigning them a low probability. Many of the LOS distributions could have been successfully approximated by a normal curve, but the normal distribution would have had to be truncated at the low end (since LOS cannot be negative). Thus for simplicity and uniformness all functions were created empirically. Chapter 4. Computer Simulation of Grace Hospital 26 AataPartna M/PA1 tro> admitting AntaPartua Kadslaa AataParti LOV AP ••CtlOD 4iacbar|a to iallvary aalta or koia Aa.taPa.rtia 11 OH Figure 4.2: Antepartum Section With Patient Paths 4.4.1 Antepartum section The antepartum subsection in the model consists of the antepartum modules (Holly and Dogwood) and the delivery suite areas APLOW, APHIGH, APOR, and APPAR for patients returning to one of the AP modules (see Figure 4.2). In the AP modules transfers and LOS are controlled mainly by a patient's AP classification. A distinction is also made between patients who will deliver before being discharged and AP-only patients because these two groups have markedly different transfers and LOS times. AP-only patients are discharged to home from the AP section whereas mothers who will deliver must pass through the delivery suite and postpartum before leaving the hospital. In addition, because undelivered mothers are often in the AP subsection at an earlier gestational age than mothers who will deliver, undelivered mothers tend to have a longer LOS in the AP section. Patients in the AP subsection but not in an AP module (i.e. in APLOW, APHIGH, Chapter 4. Computer Simulation of Grace Hospital 27 APOR, or APPAR) have their transfers and LOS controlled solely by their AP com-plication. No distinction is made between delivered and undelivered because transfers are similar by definition (transfer must always return patient to the AP module before leaving the AP subsection), and LOS is very similar. Transfers from AP modules are normally governed by their AP category, but if a transfer is to the delivery suite then the exact location in the delivery suite is determined by a mother's delivery type (see Figure 4.6). 4.4.2 Delivery Suite The delivery suite (DS) consists of low risk (LOW), high risk (HIGH), the operating rooms (OR), the post anaesthetic recovery room (PAR), and day of surgery (DOS) beds in postpartum for mothers, and the low risk nursery (LRN), and the high risk nursery (HRN) for babies (see Figure 4.3). DOS patients arrive for scheduled elective C-sections and stay briefly in one of the postpartum modules (Arbutus if it is free) awaiting their surgery. In the DS all the LOS and transfer functions for adults are determined solely by a patient's delivery type. Transfers and LOS for babies in the DS are controlled by their health classification. 4.4.3 Postpartum section The postpartum section (PP) in the model consists of the 6 PP modules (Arbutus, Bal-sam, Cedar, Dogwood, Evergreen, Fir), the OR and PAR (called PPOR and PPPAR) if there for a PP complication, the 6 nurseries associated with the 6 PP modules (PPN), and the observation nursery (OBN) (see Figure 4.4). The PPOR and PPPAR are mostly used to perform sterilizations, but occasionally a mother returns to the OR after deliv-ering due to some PP complication (eg. hemorrhage). The transfers and LOS for adults in the PP modules are governed by a patients's PP category. In the PPOR and PPPAR Chapter 4. Computer Simulation of Grace Hospital 28 froa adalttlaf or AP DOS (PP •odala) BIOR rlak LOW r i a l <dlacaari* to \ PoatPartu or I ^ J Oparatlaf too* Post Auaatfcatic lacovtry Cdlacaara* to \ PoatPartua or W Figure 4.3: Delivery Suite Showing Patient Flows froa dclivary suit* or adiittinf PoitPtrtna OB/PAR PoatPartoa •odnlaa dlachaxft to host PP » * C t i O B Figure 4.4: Postpartum Section with Patient Flows Chapter 4. Computer Simulation of Grace Hospital 29 all transfers are the same, and the LOS is controlled by a single function for all patients since there was not enough data to separate out the different PP categories. Babies in the PP section have their transfers and LOS controlled by their health classification. 4.5 How the Model Runs This section explains the admissions process, how all transfers and length of stays are determined, and the discharge procedure. For all these tasks, the model uses empirical functions that randomly assign outcomes based on their likelihood of actually occurring at Grace. 4.5.1 Admissions As discussed earlier, Grace hospital limits the number of patients who arrive to deliver each month to about 625. To simulate this, at the start of each month the model determines how many mothers to be will arrive using a function with a small variance (between 617 and 625 patients per month). This cap on mothers indirectly also limits the number of babies born in Grace per month. However the cap has relatively little effect on the number of patients arriving for undelivered visits (either AP-only or PP-only), since if a patient has been approved to deliver at Grace or has already delivered at Grace and develops a complication she will automatically be admitted, regardless of the number already admitted that month. Similarly, the number of pediatric babies admitted per month can vary significantly. Newborn babies, on the other hand, are admitted when their mother delivers (see next section). At the start of each month the model determines the number of patients who will arrive to deliver, each patient is assigned a delivery type (spontaneous, instrumental, elective C-section, DOS emergent C-section) and all the patients not in the DOS category Chapter 4. Computer Simulation of Grace Hospital 30 ftatrtto AP o n l y p a t i t n t a w i t h p o i a i o a p r o c a a e g e n e r a t e Bjotaari t o d o l l v a r (2 g e n e r a t e PP o B l y M t l o a t e w i t h a Polaeon p r o c a a t •o as s i g n raadoi arriT»l tlat wait to aatar Oraca teaIra fcoffnpalcal r«eldeBce, AP c«tag017. PP ctt e g o r y enter Oraca Figure 4.5: The Admissions Process Chapter 4. Computer Simulation of Grace Hospital 31 are assigned a r a n d o m a r r i v a l t i m e i n the m o n t h . A l l D O S pat ients are assigned an a r r i v a l t i m e s trongly favor ing the mornings M o n d a y to T h u r s d a y . T h e s e patients t h e n wait u n t i l their assigned a r r i v a l t i m e to enter the h o s p i t a l . T h e undel ivered A P - o n l y , the u n d e l i v e r e d P P - o n l y pat ients , a n d the p e d i a t r i c babies arr ive r a n d o m l y throughout the m o n t h , a c c o r d i n g to a n e x p o n e n t i a l i n t e r a r r i v a l t i m e f u n c t i o n , m o v i n g i m m e d i a t e l y into the h o s p i t a l . T h i s procedure is s h o w n i n F i g u r e 4 . 5 . W h e n a new adult pat ient enters t h e m o d e l t h e y are assigned a geographica l residence, a n A P category, a n d a P P category. T h e geographica l residence is a f u n c t i o n of a pat ient 's del ivery type. T h e A P category is d e t e r m i n e d b y b o t h the del ivery t y p e a n d the geographica l residence. A n d the P P category fol lows a lmost d irect ly f r o m the del ivery type . 4.5.2 Determining an Adult Patient's Path Through the Hospital A l l the i n i t i a l transfers of adul t pat ients , except P P - o n l y a n d D O S pat ients , into the h o s p i t a l ( from a d m i t t i n g ) are either to the a n t e p a r t u m section or to the del ivery suite. A P - o n l y pat ients a lmost a l l enter the A P sect ion, whereas o n l y a certa in p r o p o r t i o n (depending o n their A P category) of the pat ients w h o w i l l del iver go to the a n t e p a r t u m section. D O S pat ients proceed direct ly to a day of surgery b e d i n P P to wait for their surgery. P P - o n l y pat ients go d i r e c t l y i n t o the P P m o d u l e s . T h e procedure used to determine a pat ient ' s movements i n each of the three areas: a n t e p a r t u m , del ivery suite, a n d p o s t p a r t u m is the same except t h a t i n each area a dif-ferent factor controls a l l the act ions. In the a n t e p a r t u m section actions are control led by a pat ient 's A P category a n d whether or not she w i l l deliver. I n the delivery suite a l l transfers a n d L O S are governed b y the del ivery type , a n d i n P P everyth ing is control led by a pat ient 's P P category. O n c e a pat ient has m o v e d to a new l o c a t i o n her l e n g t h of stay a n d next dest inat ion are d e t e r m i n e d r a n d o m l y assigning p r o b a b i l i t i e s to each event that reflect the e m p i r i c a l Chapter 4. Computer Simulation of Grace Hospital 32 data. She then tries to find a place in the desired location, following the overflow policies set forth in section overflow if necessary. Once the prescribed time has elapsed, the patient moves to her next destination again determining the LOS and next transfer etc. until she is discharged from the hospital. Babies are born, in the model, when a mother visits an OR while in the DS section (so long as they have not delivered already), or when a mother is in LOW or HIGH risk and will transfer next to PP. Note, the model will not allow C-section patients to transfer to the PP without first visiting the OR to insure that all caesareans occurring in an operating room. In addition, a proportion of all the deliveries result in a stillbirth. In this case, no baby enters the model and the mother will stay her PP LOS in the AP modules so that she does not have to be around other patients who have just delivered healthy babies (this policy is also used at Grace for compassionate reasons). Since an operating room must always be available for emergencies, all elective surgical procedures will be delayed if fewer than 2 ORs are free. The only elective surgery patients not delayed are those who were prematurely moved out of their previous location due to overcrowding. This exception is allowed only for model simplicity. 4.5.3 Determining a Babies Path Through the Hospital The logic used to move babies is very similar but simpler than the procedure used for the adults because the babies are classified in only one way. All movements and LOS are controlled by a baby's health category (see section 4.2). Figure 4.7 is a flow chart showing the logic used to move babies through the model. 4.5.4 Discharges The majority of patient discharges from Grace occur from the morning to early afternoon. This discharge pattern causes a load peak in the mid-morning since patients arrive more Chapter 4. Computer Simulation of Grace Hospital 33 Figure 4.6: Adult Patient Movement Procedure Chapter 4. Computer Simulation of Grace Hospital newborn d e l i v e r e d 3 f p e d i a t r i c baby [ generated with a V Poieeon proceee assign health category based on mother's AP coa p l i c a t l o n enter Greco f i n d LOS and next t r a n s f e r (depends on health category) stay prescribed length of t l a e i n deelred l o c a t i o n Figure 4.7: Baby Movement Procedure Chapter 4. Computer Simulation of Grace Hospital 35 or less uniformly throughout the day and night. Discharges from Postpartum To simulate this mid-morning peak in the PP modules the model generates a mother's PP LOS in a special manner taking into account a patient's arrival time in the PP section. Since most discharges occur shortly after 10 a.m. this time was used as a starting point. In the PP modules a patient's LOS is determined by adding together three separate times. First, the difference between the current time of day (in the model) and the next 10 a.m. is calculated. Added to that is the number of days (24 hour periods) the patient has been assigned. Then, so that not all the patients are discharged at 10 a.m. , a random amount of time to reflect their actual discharge time is added (not greater than 24 hours, and usually between 0 and 4 hours). Both the number of days, and the additional random time after 10 a.m. are determined from the empirical functions built up from the hospital data. For example, a patient who arrives at 3 a.m. , is to stay 3 days, and is to be discharged at 12 noon will be assigned an LOS of (600 - 180) + (3 * 1440) + (720 - 600) = 4860 minutes. To simulate the flag system at Grace (see section 2.4 for details) the model discharges some patients early from the PP modules if there are less than 15 beds unaccounted for PP. The model will discharge 50% (the rest were deemed to be medically or otherwise unable to be discharged early) of the patients in these last 15 beds starting with the patients who are next to leave normally. Discharges From All Other Locations All the other discharges including undelivered mothers from antepartum, all baby dis-charges, and the occasional patient discharged directly from DS simply follow when a patient's LOS in that location is finished (i.e. in the model they will tend to occur at Chapter 4. Computer Simulation of Grace Hospital 36 random times). The direct discharges from the DS are small in number and occur ran-domly throughout the day at Grace as in the model. In the AP modules the model does not stagger the discharge times as in Grace. As a result, the model does not create an mid-morning peak in the AP modules and underestimates the 10:30 census (see valida-tion section). To include this effect in the model would have increased the complexity of the already complex functioning of the AP section and as a result was set aside as a possible future improvement. Mothers and babies are usually discharged together at Grace. Thus the postpartum nurseries have a mid-morning peak like the postpartum modules. In the model, again for simplicity sake, mothers and babies are treated separatly once the baby is born. The PP nurseries were not a pressing bottleneck at Grace and as result the model's underestimated 10:30 census in PPN was of little consequence. Chapter 5 Verification and Validation After completing the development of a simulation model it is necessary to verify and validate the model. Verification includes debugging the code to make sure the model behaves in a manner consistent with your expectations whereas validation determines whether a model is an accurate representation of the "real world." A standard run of the model was used for this purpose. This standard run consists of a 10 month initialization period to fill up the hospital and reach a steady state (the model starts with the hospital empty) followed by 20 months of data collection. The initialization period is more than adequate for the model to reach a steady state. Figure 5.8 shows the total PP census per month for three distinct runs. After five months, the total monthly PP census in all the runs fluctuates only mildly from the same mean. Other measures of utilization exhibited similar behaviour. This strongly suggests that a steady state has been reached. A gener-ous initialization period of ten months was used since the model is relatively inexpensive to run. In addition, to demonstrate that the steady state level varies depending on the load, consider Figure 5.9. Figure 5.9 shows the total PP census per month. Again, the runs swiftly settle down and flucuate very little. However, as expected, different load levels result in different means. Both these tests suggest that the model is stable, and therefore it is possible to obtain estimates of the stationary distribution. All the months in the standard run have 31 days. For the comparison with the hospital data, the 20 months of model output data was scaled down to 2 months. This limited the effect of the model's variability. The model is stochastic, and 2 month runs show this fluctuation. For 37 Chapter 5. Verification and Validation Figure 5.8: Initialization Length Test Chapter 5. Verification and Validation 39 MONTH Figure 5.9: Steady State at Different Load Levels Chapter 5. Verification and Validation 40 adult total baby total model 1454 1259 hospital 1455 1262 % diff. 0.0 -0.2 Table 5.1: Verification of Total Patients spont-aneous instru-mental elec. C-sec dos emer. C-sec undel AP only undel PP only model 730 188 31 93 189 201 23 hospital 741 184 29 90 188 200 23 % diff. -1.5 +2.1 +6.9 +3.3 +0.5 +0.5 0.0 Table 5.2: Verification of Delivery Type Classification two months runs the major performance measures such as total LOS and census varied only up to 20%. But, overflow measures, such as the number of entries in TREAT can vary by up to 200%. Verification of the Grace Hospital simulation model was extensive, and involved com-paring July and August 1988 hospital data (the data used to create the model) with model outputs. Comparisons were made by examining many factors. The first compari-son was the number of patients: total number of patients (see Table 5.1), the number of patients in each delivery category (Table 5.2), the number from each geographical resi-dence code (Table 5.3), the number in each antepartum category (Table 5.4), the number in each postpartum category (Table 5.5), and the number of babies in each health cat-egory (Table 5.6). All the patient totals are very similar with the exception of some smaller categories that are more subject to variability. Comparisons were also made on the length of stay average (table 5.7) and number of entries (Table 5.8) in AP, LOW, HIGH, OR, PAR, DOS, PP, LRN, HRN, OBN, and Chapter 5. Verification and Validation 41 Vancouver GVRHD B.C. model 791 526 137 hospital 798 520 137 % diff. -0.9 + 1.1 0.0 Table 5.3: Verification of Geographical Residence of Patients no AP preterm rupture hyper- dia- IUGR AP other AP comp. labour membrane tension betes hem. comp. model 569 86 191 80 94 81 77 276 hospital 575 77 186 78 98 86 73 282 % diff. -1.1 + 11.7 +2.7 +2.6 -4.3 -6.2 +5.5 -2.2 Table 5.4: Verification of AP Classification spont. spont. inst. inst. elec-C elec-C em-C em-C PP (no) (yes) (no) (yes) (no) (yes) (no) (yes) only model 675 55 158 30 111 13 155 33 23 hospital 681 60 157 28 106 13 153 35 21 % diff. -0.9 -9.1 +0.6 +7.1 +4.7 0.0 +1.3 -6.1 +9.5 Table 5.5: Verification of PP Classification -< 2500g y 2500g & -< 37 weeks y 2500g & y 37 weeks short stay pediatric model 64 136 982 54 22 hospital 58 134 1002 45 23 % diff. +10.3 +1.4 -2.0 +20.0 -4.5 Table 5.6: Verification of Baby Classification Chapter 5. Verification and Validation 42 AP LOW HIG OR PAR DOS PP LRN HRN OBN PPN model 5714 499 668 97 108 608 5075 113 117 3058 4944 hospital 5780 487 683 97 111 634 5054 112 119 3012 4925 % diff. -1.2 +2.5 -2.2 0.0 -2.8 -4.3 +0.4 +0.9 -1.7 +1.5 +0.4 Table 5.7: Verification of Length of Stay Averages AP LOW HIG OR PAR DOS PP LRN HRN OBN PPN model 431 1247 490 404 385 93 1216 . 669 507 192 1194 hospital • 418 1245 485 386 369 90 1236 681 491 199 1206 % diff. +3.1 +0.2 + 1.0 +4.7 +4.3 +3.3 -1.6 -1.0 + 1.0 -3.6 -1.0 Table 5.8: Verification of Number of Entries PPN. All the LOS averages and number of entries generated by the model are within 5% of the hospital's numbers. This is a close correspondence. It should be noted that although the model has separate transfer and LOS functions in each location depending on patient classification, the verification was only done on the totals for all classes. The totals were used for simplicity, assuming that if both the number in each class and the overall LOS and transfer tables are correct then the individual LOS and transfer distribution will also be correct. Further verification consisted of performing chi-square tests to compare: adult and baby transfer tables, LOS distribution in all the locations in the hospital, the interarrival distribution of all patients to deliver, and the daily arrival distribution of DOS patients. The hypothesis that the model's transfer tables were the same as the hospital's transfer tables could not be rejected at the 0.1 level. The results for the LOS distributions, the interarrival time distribution of patients to deliver and the arrival distribution of DOS patients were also very good. The hypothesis that the model's output is the same as the observed data from Grace could not be rejected at the 0.05 level. As a result of these and many other less formal tests the model was passed Chapter 5. Verification and Validation 43 delivery AP LOS delivery PP LOS AP only total LOS PP only total LOS newborn total LOS pediatric total LOS model 1459 5244 7467 4248 5318 15136 hospital 1470 5112 7272 4104 5256 15785 % diff. -0.8 +2.6 +2.7 +3.5 +1.2 -4.3 Table 5.9: Validation of Total Length of Stay (minutes) through the verification process. The first phase of the validation was completed during the development of the model by ensuring a "high face validity". This was achieved primarily by conducting exten-sive interviews to make sure the inner workings and important subtleties of Grace were accounted for in the model. In addition, all assumptions and problems were presented for discussion to hospital department heads to ensure a wide base of input. After the development, the model was further validated both by comparing the output with his-torical data, and by sensitivity analysis. Fortunately, Grace Hospital collects extensive data on a daily basis for their existing management system. However, it was impor-tant for validation to compare the model's output with data from a source other than the one used to create the model. Comparisons made include total LOS time in the hospital for undelivered patients, newborns, and pediatric patients (see Table 5.9). The LOS for patients who deliver is broken down into time before delivery (AP LOS), and time after delivery (PP LOS). The total length of stay values are very similar, showing the close correspondence between the model and the hospital. The model's output was also compared with the hospital data for average 10:30 a.m. census figures for PP, AP, and OBN, and the number of entries into TREAT the PP temporary overflow area (AP census includes both Holly & Dogwood). The results are shown in Table 5.10. The hospital's antepartum 10:30 census figures are consistently under estimated by the model Chapter 5. Verification and Validation 44 AP 10:30 PP 10:30 OBN 10:30 # entries census census census in TREAT model 28.2 80.7 6.6 27 hospital 31.2 79.5 6.5 16 % diff. -10.6 + 1.5 +3.1 +69.0 Table 5.10: Validation of Census and Utilization because the model does not take into account the effect of patients mainly leaving the AP during the day (i.e. after the 10:30 census), but arriving uniformly day and night. This arrival/discharge distribution creates a peak load in the hospital at around 10:30 a.m. with the average number of patients dropping to about 29 at midnight. As discussed in the previous chapter, this effect is difficult to add to the model because of the complexity of the AP section, and a lack of data. In the postpartum module the model generates LOS times taking into account a patient's arrival time in PP. This enables the model to stagger discharge times as in Grace (see section 4.5.4). Thus the model's 10:30 PP census is very close to the hospital's averages. The arrival/discharge distribution is taken into account in the PP section because it involves many patients and has a large effect (the average midnight census in PP drops to 72 patients). The large percentage discrepancy in the number of entries to the treatment room was expected since TREAT is an overflow area for the PP modules. The PP modules have room for about 90 patients (depending on how many AP patients are in DOG) so TREAT only shows the peaks over this value. The validation process also included sensitivity analysis. Sensitivity analysis checks the model's reaction to a change in the inputs, and in this study was combined with the experimentation, see the next chapter for details. In all cases, the model reacted to the change in a "reasonable" way (e.g. the average utilization increased slightly when a few more patients were allowed to enter the hospital). The true test of the model's ability to accurately simulate the functioning of Grace Chapter 5. Verification and Validation 45 Hospital lies in the future. The model can be used to predict the consequences of changing some aspect of the hospital. If the change actually takes place, the model's predictions can be compared with the new data from the hospital. If the model has taken into account all the important aspects of the hospital the predictions should be close to the actual data. However, the verification and historical validation was excellent. The model's output was in very close correspondence with the data from the hospital. With such excellent results it is possible to move to the experimentation phase confident that the model will accurately reflect the hospital. Chapter 6 Experimentation and Results The administration of Grace Hospital must constantly evaluate the strengths and weak-nesses of new management policies. Using the Grace Hospital Simulation Model, the evaluation of possible future strategies can be done with much more confidence. Four different scenarios of interest to management at Grace were simulated. 1. Increase the load in terms of patients per month. 2. Increase the proportion of patients residing outside of Vancouver. 3. Decrease the average length of stay in the PP. 4. Remove the limit on the number of patients entering the hospital per month (i.e. remove the preregistration cap). The following performance measures were determined for all the experiments. 10:30 AP census - the average number of patients in the antepartum modules at 10:30 a.m. days in LOW overflow - the number of total patient days spent in the temporary overflow areas of low risk (e.g. in the assessment room or in the PAR). 10:30 PP census - the average number of patients in the postpartum modules at 10:30 a.m. patients in TREAT - the number of PP patients temporarily in a treatment room. 46 Chapter 6. Experimentation and Results 47 days lost in PP - the total number of patient days lost due to early discharge from PP. Either caused by a red flag condition (see section 4.5.4) or because new patients arrive to find PP totally full. 10:30 OBN census - the average number of babies in the observation nursery at 10:30 a.m. Note: all tables show percentage increase or decrease from the standard run in brack-ets. Of particular interest are the number of patients days spent in temporary overflow from LOW, and the number of patient days lost due to crowding in PP. If these values increase much more than the standard levels, the congestion in the hospital becomes unacceptably high. Patients would be unable to receive the care they require. When examining the results, note that simulation models can show the effects of changing certain inputs, but cannot determine optimal conditions. All the experiments used a standard run length: 10 months initialization followed by 20 months of data collection. The 20 months of data was then scaled down to one month. 6.1 Increasing the Load Increasing the patient load per month at Grace can occur in two ways, either more patients could be admitted per month, or the number of days in a month could decrease. The standard run of the model is based on months with 31 days (since July & August 1988 each have 31 days). But, Grace Hospital uses the same preregistration limit regardless of the number of days in the month. Therefore, in months with fewer days, more patients are treated per day. The results in shorter months with the same preregistration limit are shown in Table 6.11. There could be a large effect. For example, in months with 28 days the combined PP and AP average census figures increase by 8.2 patients or 7.5%. If Chapter 6. Experimentation and Results 48 10:30 AP days in 10:30 PP patients days lost 10:30 OBN census LOW overflow census in TREAT in PP census standard 28.2 3.4 80.7 13.4 25.9 6.6 30 days 29.2(3.5) 4.7(39) 83(2.8) 23.6(76) 40.3(55) 6.4(-3) 28 days 31.3(11) 6.4(88) 85.8(6.3) 83.2(522) 89.7(246) 7.0(6) Table 6.11: Experiment 1A : Decreasing the Number of Days per Month the load per month were the same in February as in July or August the crowding would be unacceptable. However, maternity demand has a pronounced seasonal variation. This variation was not incorporated in the model because only July and August data were available. February is a slow month at Grace. Even though the preregistration limit is not changed fewer patients come to Grace. On the other hand, some months with 30 days (e.g. September) have a similar demand pattern as July or August. Assuming a similar demand, the effects of not changing the preregistration cap in months with 30 days are noticeable. For example, the number of days lost in PP due to overcrowding increases by 55%. Consequently, it is recommended that the preregistration limit reflect the number of days per month. Three different experiments were run showing the effects of increasing the number of patients admitted per month. The number of patients arriving to deliver was increased by 10, 20, and 50 per month, with a corresponding percentage increase in the number of AP-only, PP-only, and pediatric patients. Normally about 620 patients per month deliver at Grace, so these increases are relatively small. However, Table 6.12 shows that the increases have a significant effect. For example, only 10 more patients per month causes the number of patients who must temporarily use a treatment room to jump by 114%. Increasing the number of patients per month by 50 raises the combined AP and PP average census by 7%. Both these experiments reflect the fact that that Grace is Chapter 6. Experimentation and Results 49 10:30 AP days in 10:30 PP patients days lost 10:30 OBN census LOW overflow census in TREAT in PP census standard 28.2 3.4 80.7 13.4 25.9 6.6 + 10 29.2(3.5) 4.1(21) 81.7(1.2) 28.6(114) 33.2(28) 6.5(-l) + 20 29.8(5.7) 4.2(23) 83(2.8) 29.2(118) 43.1(66) 6.7(1) + 50 30.8(9.2) 5.3(56) 85.7(6.2) 59.1(342) 74.6(188) 7.1(7.6) Table 6.12: Experiment IB : Increasing the Number of Patients per Month already running close to capacity. A relatively small increase in load results in a large decrease in service. 6.2 Increase the Proportion of Patients from Outside Vancouver Population trends predict that in the coming years there will be a large decrease in the number of births in Vancouver, and an increase in births in the rest of the province. Thus, because of Grace's role as a tertiary care facility, adminstrators are predicting an increase in the relative proportion of patients from outside Vancouver arriving at Grace. Importantly, this redistribution also results in a higher proportion of "high risk" patients since patients only come from far away if they are likely to develop a complication. To simulate this prediction, two new experiments were run. First, the relative'proportion of patients from Vancouver was decreased by 10 percentage points (at present about 55% of patients are from Vancouver proper). The proportion of patients from the GVRHD and B.C. increased by 5 percentage points each. The second experiment decreased the patients from Vancouver by 20 percentage points (down to 35% of total patients) again spreading the increase evenly among the other regions. Both of these experiments did not change the total number of patients arriving to deliver each month. However, the numbers of AP-only, PP-only, and pediatric patients were increased, to reflect the higher Chapter 6. Experimentation and Results 50 10:30 AP days in 10:30 PP patients days lost 10:30 OBN census LOW overflow census in TREAT in PP census standard 28.2 3.4 80.7 13.4 25.9 6.6 45% Van. 28.7(1.8) 3.9(15) 81.1(0.5) 10.8(-24) 28.5(10) 6.8(3) 35% Van. 29.3(3.9) 3.2(-5) 81.6(1.1) 14.9(11) 29.9(15) 6.8(3) Table 6.13: Experiment 2 : Increasing the Proportion of Patients from Outside Vancouver proportion of patients from GVRHD and B.C. that require this additional care. The results are shown in Table 6.13. The impact on the hospital was not very large. For example, with 20 percentage points less patients from Vancouver the combined AP and PP census increased by only 1.8%. 6.3 Decrease the Average Length of Stay An early discharge program is an effective way to accomplish a decrease in the average LOS in PP. Early discharge programs have an added benefit. Caring for patients in their own homes may be more cost effective and more comfortable for the patient. Two experiments were run to gauge changes in hospital utilization when the average LOS in PP was decreased. At present, the average length of stay in the PP section is 3.1 days for spontaneous deliveries, 3.3 days for instrumental deliveries, and 5.2 days for C-sections. The first experiment decreased the average LOS for spontaneous and instrumental de-liveries to 3 days, and decreased the average LOS for C-sections to 5 days. The second experiment further decreased the average LOS for C-sections to 4 days. The results are shown in Table 6.14. As expected the utilization figures for AP, LOW, and OBN did not noticeably change. In contrast, the PP utilization measures changed markedly. For example, lowering the average LOS of C-sections to 4 days decreases the number of days lost in PP due to overcrowding by a very substantial 573%. Even decreasing the average Chapter 6. Experimentation and Results 51 10:30 AP days in 10:30 PP patients days lost 10:30 OBN census LOW overflow census in TREAT in PP census standard 28.2 3.4 80.7 13.4 25.9 6.6 5 day CS 28.2(0) 3.8(13) 78.7(-2.5) 7.9(-68) 13.3(-94) 6.7(1.5) 4 day CS 28.2(0) 3.2(-5) 74.3(-8.6) 1.3(-968) 3.8(-573) 6.6(0) Table 6.14: Experiment 3 : Decrease the Average LOS in PP LOS of all patients by only about 0.2 days decreases the number of days lost in PP by 94%. This result shows that the benefits of an early discharge program can be substan-tial. More experiments would be needed to determine how many more patients could be accommodated while maintaining the old utilization level. 6.4 Eliminate the Preregistration Cap The final experiment demonstrates that Grace could not operate without limiting the number of admissions. In July and August of 1988 an average of 190 patients per month were rejected by the preregistration system. Therefore, the model was run with an 10:30 AP census days in LOW overflow 10:30 PP census patients in TREAT days lost in PP 10:30 OBN census standard 28.2 3.4 80.7 13.4 25.9 6.6 nocap 28.8(2.1) 18(532) 90.5(12) 257(1927) 167.4(646) 7.1(7.5) Table 6.15: Experiment 4 : Eliminate the Preregistration Cap additional 190 patients delivering each month. All patients rejected must be "low risk" since all "high risk" patients are automatically admitted. To minimize their effect, all of these new patients were assigned a spontaneous delivery with no AP or PP complications. This is clearly an underestimate since not all initially diagnosed "low risk" patients will remain complication free. In addition, the experiment did not increase the arrival rates Chapter 6. Experimentation and Results 52 of the AP-only, PP-only, and pediatric patients that would undoubtedly also occur from this influx of new patients. The results (Table 6.15) are purely academic since Grace would not consider eliminating their highly successful preregistration system. Without the cap the number of patient-days lost in PP due to overcrowding increases by 646%, and the number of visits to the treatment room increases by an incredible 1927%. Clearly the preregistration cap is needed to keep the load at Grace Hospital under control. Chapter 7 Summary and Conclusion A successful model of Grace Hospital needs to take into account many complexities, including the interactions among the various units, the progressive nature of the delivery process, and the discharge time distribution. The model was based on a simulation model methodology presented by Cohen, Hershey, and Weiss [5]. It assumes that under no capacity constraints movements depend only on patient's present location, and not on any past hostory. Overflow results in either patients temporarily staying in an alternative unit, moving to another acceptable unit, or displacing another patient prematurely. In contrast to previous models, this simulation uses a classification system that varies the factor that governs transfers and LOS depending on a patient's stage of delivery. The phases of treatment in obstetrics are well defined into antepartum, delivery, and postpartum. Classifications in the model include antepartum complication, delivery type, and postpartum complication. For example, in antepartum a patient's behaviour is best determined by her antepartum complication. In the delivery suite, on the other hand, a patient's delivery type is most important. As an additional improvement over past models a patient's LOS in postpartum depends on the time of day at which she enters PP. By including this extra factor in the LOS calculation the model is able to accurately simulate the mid-morning peak load. This addition could be used in other models that simulate hospitals with a similar arrival and discharge pattern. The model was time consuming to create, and is very complex. However, by con-ducting numerous interviews at Grace the model was created to accurately reflect the 53 Chapter 7. Summary and Conclusion 54 operation of the hospital. However, verification and validation were very successful and the model is now a valuable management tool. It has been used to study several sce-narios of interest: increasing the load, changing the patient mix, decreasing the LOS, and eliminating the preregistration system. Measures of utilization include the average census, and the number of patient-days spent in inappropriate units or lost due to over-crowding. The results show that Grace is operating very close to capacity. A relatively small increase in load results in a large increase in congestion. Also, an early discharge program was shown to significantly alleviate the overcrowding. The specific numerical results themselves are applicable only to Grace, but the simulation methodology used to overcome problems maybe of interest in other applications. The model will be used to evaluate other prospective changes in management policies. Grace Hospital is far too complex for a simulation model to include every detail. In fact, a simulation model should include only important and relevant details. However, improvements to the present model may result by including some or all of the following: 1. Staffing considerations - an important factor in day to day operation of a hospital. 2. Seasonal variations in load 3. Scheduling procedure for the operating room - difficult to include in the model of a progressive care hospital. 4. Patient movements to reflect time of day at which they occur 5. Regional effects - especially important for the preregistration system. Bibliography [1] Barr, A. and Oddie, J. "Hospital Beds for Maternity Patients", Medical Care, 1966, Vol. 3-4 (July-Sept), pp.180-184. [2] Beaver, M.W. "Maternity Unit Admissions Policy and the Use of Simulations", Brit. J. Prev. Soc. Med., 1970, Vol. 24, pp. 169-176. [3] Blumberg, M.S. "DPF Concept Helps Predict Bed Needs", The Modern Hospital, 1961, Vol. 97, pp. 75-81. [4] Brooks, G.H., Beenhakker, H.L. "A Technique for Prediction for Future Hospital Bed Needs", Hospital Management, 1964, pp. 47-50. [5] Cohen, M.A., Hershey, J.C., Weiss, E.N. "Analysis of Capacity Decisions for Pro-gressive Patient Care Hospital Facilities", Health Services Research, 1980, Vol. 15, pp. 145-160. [6] Conway, R.W., "Some Tactical Problems in Digital Simulation", Management Sci-ence, 1963, Vol. 10 (1), pp. 47-61. [7] Cowan, P., Roth K., "Determining Maternity Case Load by Means of a Poisson Process", Brit. J. Prev. Soc. Med., 1964, Vol. 18, pp. 105-108. [8] Duchessi, P. "A Methodology for Determining a Hospital's Expected Costs for Changes in Patient Load and Service Mix", Management Science, 1987, Vol. 33 (1), pp. 73-85. 55 Bibliography 56 [9] Dumas, M.B., "Hospital Bed Utilization: An Implemented Simulation Approach to Adjusting and Maintaining Appropriate Levels", Health Services Research, 1985, Vol. 20:1, pp. 43-61. [10] Fetter, R.B., Mills, R.E. "HOSPSIM: A Simulation Modeling Language for Health-care Systems", Simulation, 1975, March, pp. 73-80. [11] Fetter, R.B., Thompson, J.D. "The Simulation of Hospital Systems", Operations Research, 1965, Sept.-Oct., pp. 689-711. [12] Fetter, R.B., Thompson, J.D. "A Decision Model for the Design and Operation of a Patient Care Hospital", Medical Care, 1969, Vol. 7 (6), pp. 450-462. [13] Fischer, OR., "The Use of Computer Simulation Techniques in Determining Ob-stetrical Bed Needs", Masters of Public Health Thesis, Yale University, 1968. [14] Goldman, J., Knappenberger, H.A., Eller, J.C. "Evaluating Bed Allocation with Computer Simulation", Health Services Research, 1968, Vol. 2-3, pp. 119-129. [15] Hershey, J.C, Weiss, E.N., Cohen, M.A. "A Stochastic Service Network Model with Application to Hospital Facilities", Operations Research, 1981, Vol. 29 (1), pp. 1-22. [16] Kao, E.P.C. "A Semi-Markov Model to Predict Recovery Progress of Coronary Pa-tients", Health Services Research, 1972, Vol. 7, pp. 191-208. [17] Kao, E.P.C. "Modeling the Movement of Coronary Patients within a Hospital by Semi-Markov Processes", Operations Research, 1973, Vol. 22, pp. 683-699. [18] Lane, D., Uyeno, D., Stark, A., Gutman, G., McCashin, B., "Forecasting Client Transitions in British Columbia's Long-Term Care Program", Health Services Re-search, 1987, 22:5, pp. 671-706. Bibliography 57 [19] Milliken, R.A., Rosenberg, L., Milliken, G.M. "A Queueing Theory Model for the Prediction of Delivery Room Utilization", American Jnl. of Obstet. and Gyn., 1972, Vol. 114 (5), pp. 691-699. [20] Nie, N.H., Hull, C.H., Jenkins, J.G., Steinbrenner, K., Bent, D.H. SPSS - Statistical Package for the Social Sciences 2nd ed., 1975 McGraw-Hill. [21] Pendergast, J.F., Vogel, W.B. "A Multistage Model of Hospital Bed Requirements", Health Services Research, 1988, 23:3, pp. 381-399. [22] Raz, T., Kachitivichyanukul, V., Paul, E., Lee, J., "Drums - A Simulation Tool for Hospitals", Industrial and Management Engineering, University of Iowa, 1984. [23] Rising, E.J., Baron, R., Averill, B. "A Systems Analysis of a University Health-Service Outpatient Clinic", Operations Research, 1973, Vol. 21 (4), pp. 1030-1047. [24] Robinson, G.H., Wing, P., Davis, L.E. "Computer Simulation of Hospital Patient Scheduling Systems", Health Services Research, 1968, Vol. 4, pp. 130-141. [25] Schriber, T.J. Simulation using GPSS, 1974, John Wiley & Sons. [26] Shachtman, R.H., Snapinn, S.M., Quade, D., Freund, A.D., Kronhaus, A.K., "A Method for Constructing Case-Mix Indexes, with Application to Hospital Length of - Stay", Health Services Research, 1986, Vol. 20 (6), pp. 737-762. [27] Shonick, W., Jackson, J.R. "An Improved Stochastic Model for Occupancy-Related Random Variables in General-Acute Hospitals", Operations Research, 1973, Vol. 21 (4), pp. 952-965. [28] Slutsky, A.S. "Mathematical Models Used in Forecasting Maternity Facilities Needs", Hospital Administration in Canada, 1977, March, pp. 54-60. Bibliography 58 [29] Swartzman, G., "The Patient Arrival Process in Hospitals: Statistical Analysis", Health Services Research, 1970, Vol.5, pp. 320-329. [30] Thomas, W.H., "A Model for Predicting Recovery Process of Coronary Patients", Health Services Research, Fall 1968, pp. 185-213. [31] Thompson, J.B., Avant, O.W., Spiker, E.D. "How Queueing Theory Works for the Hospital", The Modern Hospital, 1960, Vol. 94 (3), pp. 75-78. 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Appendix A Data Analysis Tables Table A.16: Arrival Time of Day for Adult Patients DEL DELIVERY TYPE C R O S S T A B U L A T I O N O F BY AT ADMISSION TIME OF DAY (HRS) COUNT ROW PCT DEL SPONTANEOUS INSTRUMENTAL ELEC C-SECTION EM C-SECTION PP-ONLY AP-ONLY DOS (ELEC-C) COLUMN TOTAL CHI-SQUARE D.F. 175.32025 42 STATISTIC 0-2 3-5 6-8 9-11 12-14 15-17 18-20 21-23 ROW TOTAL 1| 2 3| 4| 5| 6 1 7 8| 91 1 80 136 1 110 I 8 4 I 82 1 7 3 85 1 741 12.3 1 10.8 18.4 I 14.8 I 11-3 | 11.1 | 9.9 11.5 | 51.1 19 1 18 51 1 34 1 1 3 I 1 2 1 1 6 22 1 185 10. 3 | 9.7 27.6 | 18.4 I 7.0 | 6.5 | 8.6 11.9 | 12.8 I 1 4 1 3 I 1 I 4 I 3 1 I 1 7 | 5.9 23.5 | 17.6 | 5.9 I 23.5 | 17.6 5.9 I 1 -Z 26 I 1 8 21 I 37 I 2 7 I 2 7 I 1 2 20 I 188 13.8 | 9.6 11.2 1 19.7 I 14.4 | 14.4 | 6.4 10.6 | 13.0 3 1 4 1 4 I I 4 I 4 2 I 2 1 14. 3 1 19.0 j 19.0 I | 19.0 | 19.0 9.5 1 1 4 25 1 8 16 I 19 I 3 2 I 3 ' I 3 4 30 I 195 12.8 1 4 1 8.2 | 9.7 | 16.4 | 15.9 I 17.4 15.4 | 13.5 1 1 32 1 19 I 3 7 I 7 l 5 1 1 102 I 1 0 31.4 | 18.6 | 36.3 | 6.9 I 4.9 1.0 1 7 o 164 126 264 226 194 167 147 161 1449 11.3 8.7 18.2 15.6 13.4 11.5 10. 1 11.1 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F. < 5 0.0000 1.478 16 OF 56 ( 28 ex) CRAMER'S V VALUE 0.14201 SIGNIFICANCE 59 Appendix A. Data Analysis Tables Table A.17: Arrival Day of Week for Adult Patients DEL DELIVERY TYPE C R O S S T A B U L A T I O N BY ADAY O F ADMISSION OAY OF WEEK COUNT ROW PCT ADAY SUNDAY DEL MONDAY TUESDAY WEDNES-DAY 1| Z| 3| 41. THURSDAY FRIDAY SATURDAY 5| B| 7| ROW TOTAL 1 I 92 85 107 122 1 16 99 120 I 741 SPONTANEOUS | 12.4 11.5 14.4 16.5 15.7 13.4 16.2 | 51.1 2 I 27 31 30 21 27 30 19 I 185 INSTRUMENTAL | 14.6 16.8 16.2 11.4 14.6 16.2 10. 3 I 12.8 3 I 1 6 3 3 2 2 I 1 7 ELEC C-SECTION | 5.9 35.3 17.6 17.6 11.8 11.8 I 1-2 4 I 22 23 23 23 40 29 28 I 188 EM C-SECTION | 11.7 12.2 12.2 12.2 21 . 3 15.4 14.9 | 13.0 5 I 3 4 2 3 4 4 1 I 2 1 PP-ONLY | 14.3 19.0 9.5 14.3 19.0 19.0 4.8 I 1 4 6 I ie 18 35 35 34 31 26 I 195 AP-ONLY | 8.2 9.2 17.9 17.9 17.4 15.9 13.3 | 13.5 9 I 7 18 22 25 23 6 1 I 102 DOS (ELEC-C) I 6.9 17.6 21.6 24.5 22.5 5.9 1.0 I 7.0 COLUMN 168 179 225 232 247 201 197 1449 TOTAL 11.6 12.4 15.5 16.0 17.0 13.9 13.6 100.0 CHI-SQUARE D.F. 66.60179 36 STATISTIC SIGNIFICANCE VALUE MIN E.F. CELLS WITH E.F.< 5 1 .971 14 OF 49 ( 28.6%) SIGNIFICANCE CRAMER'S V 0.08753 Appendix A. Data Analysis Tables 61 Table A. 18: Total LOS by AP Category AP2 ANTE PARTUM COMPLICATION C R O S S T A B U L A T I O N BY HOSOAYS O F DAYS SPENT IN HOSPITAL (ROUNDED UP) COUNT ROW PCT AP2 2| 5| 8 DAYS ROW OR MORE TOTAL 7| 8| 0 1 43 I 3 2 I 102 l 247 I 64 1 6 1 I 1 1 11 I 571 NO ANTEPARTUM | 7.5 I 5.6 | 17.9 | 43.3 | 11.2 | 10.7 I 1 9 1.9 | 39.4 1 I 3 I 5 I 8 I 17 I 17 I 7 1 2 18 I 7 7 PRETERM LABOUR | 3.9 I 6.5 | 10.4 | 22. 1 | 22. 1 I 9 ' 1 2.6 23.4 | 5.3 2 I 2 I 5 I 16 I 66 1 40 I 29 1 1 5 13 I 186 RUPTURE | 1 . 1 I 2.7 | 8.6 | 35.5 1 21.5 | 15.6 I 8 1 7.0 I 12.8 3 I 1 I 5 I 10 I 25 I 1 0 I 8 I 6 13 1 7 8 HYPERTENSION | 1 . 3 I 6.4 | 12.8 | 32. 1 | 12.8 | 10.3 I 7 7 16.7 1 5.4 4 I 2 1 1 1 6 I 33 I 1 6 1 ' 5 I 5 20 1 98 DIABETES I 2.0 1 1 0 I 6.1 | 33.7 I 16.3 | 15.3 I 5.1 20.4 | 6.8 S I 2 I 2 I 15 I 29 I 1 3 I 1 3 I 3 9 1 86 IUGR | 2.3 I 2 3 | 17.4 | 33.7 | 15.1 | 15.1 I 3-5 10.5 | 5.9 6 I 3 I 9 I 8 I 14 I 6 1 1 2 I 3 16 1 7 1 AP HEMORRAGE | 4.2 I '2.7 I 11.3 1 19.7 I 8.5 1 16.9 I 4.2 22.5 1 4.9 7 1 7 I 1 2 1 37 1 56 I 44 I 6 3 I 1 9 24 1 282 OTHER I 2.5 1 4.3 | 13.1 | 19.9 | 15.6 | 29.4 1 6.7 8.5 | 19.5 COLUMN 63 71 202 487 210 228 64 124 1449 TOTAL 4 . 3 4.9 13.9 33.6 14.5 15.7 4.4 8.6 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F. < 5 266.50232 49 0.0000 3.087 15 OF 64 ( 23 .4%) STATISTIC VALUE SIGNIFICANCE CRAMER'S V 0.16209 Appendix A. Data Analysis Tables 62 Table A.19: Total LOS by Delivery Type DELTYPE DELIVERY TYPE OF MOTHER C R O S S T A B U L A T I O N O F BY HOSDAYS DAYS SPENT IN HOSPITAL (ROUNDED UP) COUNT ROW PCT DELTYPE 21 <l 5| 8 DAYS ROW OR MORE TOTAL 7| 8| 1 I 9 I 3 5 I 157 I 358 108 1 28 I 1 0 36 1 741 SPONTANEOUS I 1 .2 I 4.7 | 21.2 | 48. 3 14.6 1 3.8 I ' 3 4.9 | 51.1 2 I 1 I 2 I 18 I 95 47 1 1 3 I 4 5 1 185 INSTRUMENTAL I .5 I 1.1 1 9.7 | 51.4 25.4 I 7-0 I 2.2 2.7 I 12.8 3 I 1 1 1 2 20 I 7 3 I 1 3 11 I 119 ELEC C-SECTION I 1 1 I 1 . 7 16.8 | 61.3 | 10.9 9.2 | 8.2 4 I 1 1 I 1 I 5 18 I 98 1 3 3 32 I 168 EM C-SECTION I I 5 | •5 I 2.7 9.8 I 52. 1 1 17.6 17.0 I 13 0 5 I 4 I 4 I 2 I 4 3 I 3 I 1 1 2 1 PP ONLY I 19.0 I 19 0 | 9.5 | 19.0 14.3 | 14.3 | 4.8 I 1-< 6 I 49 I 2 9 I 24 1 23 14 I 1 3 I 3 40 1 195 AP ONLY I 25. 1 I ' 4-9 I 12.3 | 11.8 7.2 I 6 - 7 I 1 -5 20. 5 | 13.5 COLUMN 63 71 202 487 210 228 64 124 1449 TOTAL 4.3 4.9 13.9 33.6 14.5 15.7 4.4 8.6 100.0 :HI-SQUARE D F . SIGNIFICANCE MIN E.F. CELLS WITH E.F. < 5 1166.45168 35 0.0000 0 .913 7 OF 48 ( 14 .6X1 STATISTIC CRAMER'S V VALUE 0.40125 SIGNIFICANCE Table A.20: Total LOS by Geographical Residence C R O S S T A B U L A T I O N O F GEOGRAPHICAL REGION OF MOTHER BY HOSDAYS DAYS SPENT IN HOSPITAL (ROUNDED UP) HOSDAYS COUNT ROW PCT 2| 3I 4| 5| 6| 8 DAYS ROW OR MORE TOTAL 7| 8| 1 I 31 I 4 3 I 130 I 265 117 I 128 I 4 2 38 I 794 VANCOUVER I 3.9 I 5.4 | 16.4 | 33.4 14.7 | 16. 1 I 5.3 4.8 I 54.8 2 I 26 I 2 1 I 59 I 186 75 I 80 I 1 9 53 I 519 GVRHD I 5.0 I 4.0 | 11.4 | 35.8 14.5 I 15.4 I 3 7 10.2 I 35.8 3 I 6 I 7 I 1 3 1 36 18 I 20 I 3 33 I 136 REST OF B c I 4.4 I 5.1 | 9.6 | 26.5 13.2 | 14.7 | 2.2 24.3 I 9.4 COLUMN 63 71 202 487 210 228 64 124 1449 TOTAL 4.3 4.9 13.9 33.6 14.5 15.7 4.4 8.6 100.0 CHI-SQUARE O F . SIGNIFICANCE MIN E.F. CELLS WITH E.F < 5 70.64686 14 0.0000 5.913 NONE STATISTIC CRAMER'S V VALUE 0.15613 SIGNIFICANCE Appendix A. Data Analysis Tables 63 Table A.21: Total LOS by PP Complication POST PARTUM COMPLICATION C R O S S T A B U L A T I O N O F BY HOSDAYS DAYS SPENT IN HOSPITAL (ROUNDED UP) PP2 NONE SOME COUNT ROW PCT COLUMN TOTAL CHI-SQUARE D.F. 26.30579 7 STATISTIC CRAMER'S V 2I 3| <l 5| 6| 8 DAYS ROW OR MORE TOTAL 7| B| 58 1 70 1 193 I 444 179 I 197 I 56 105 I 1302 4.5 1 5.4 | 14.8 | 34 . 1 13.7 I 15.1 I 4-3 8. 1 | 89.9 - + 5 1 1 1 9 I 43 31 I 3 1 I 8 19 I 147 3 4 1 .7 | 6.1 1 29.3 21 . 1 | 21.1 | 5.4 12.9 | 10. 1 - 4 63 71 202 487 210 228 64 124 1449 4.3 4.9 13.9 33.6 14.5 15.7 4.4 8.6 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F < 5 0.0004 6.391 NONE VALUE 0.13474 SIGNIFICANCE Table A.22: Total LOS by Sterilization STERILIZATION (YES/NO) HOSDAYS C R O S S T A B U L A T I O N O F BY HOSDAYS DAYS SPENT IN HOSPITAL (ROUNDED UP) COUNT ROW PCT 'I 3| 4| 5| 8 DAYS ROW OR MORE TOTAL 7| 8| 1 1 63 1 7 1 I 199 I 470 194 1 204 I 62 114 I 1377 NO STERILIZATION | + -4.6 I 5.2 | 14.5 | 34 . 1 14. 1 | 14.8 I 4.5 8.3 I 95.0 2 1 1 1 3 I 17 16 1 Z4 I 2 10 I 7 2 STERILIZATION | + - I I 4.2 | 23.6 22. 2 | 33.3 I 2.8 13.9 | 5.0 COLUMN 63 71 202 487 210 228 64 124 1449 TOTAL 4.3 4.9 13.9 33.6 14.5 15.7 4.4 8.6 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F. < 5 35.46473 7 0.0000 3. 130 3 OF 16 ( 18 .8%) STATISTIC VALUE SIGNIFICANCE CRAMER'S V 0.15645 Appendix A. Data Analysis Tables 64 Table A.23: Antepartum LOS by AP Category AP2 ANTE PABTUM COMPLICATION DELHRS C R O S S T A B U L A T I O N O F -BV DELHRS HOURS SPENT IN DELIVERY I ROUNDED UP) COUNT ROW PCT <2.4 HRS 4.B HRS 7.2 HRS 9.6 HRS 12 HRS 14.4 HRS 16.8 HRS 19.2 HRS 21.6 HRS 24 HRS OR MORE 1| 2| 3| 4| 5| 6| 7| 8| 9| 101 ROW TOTAL 0 I 37 120 111 85 59 45 30 25 1 20 39 1 571 NO ANTEPARTUM | 6 . 5 21 .0 19.4 14.9 10.3 7.9 5 .3 4 .4 | 3.5 6 .8 I 39.4 1 1 4 10 14 7 8 8 1 4 1 3 18 1 7 7 PRETERM LABOUR | 5.2 13.0 18.2 9. 1 10.4 10.4 1.3 5.2 1 3.9 23.4 1 5 .3 2 1 3 10 25 22 10 20 15 24 | 16 41 | 186 RUPTURE | 1.6 5.4 13.4 1 1 8 5.4 10.8 8. 1 12.9 I 8.6 22 .0 | 12.8 3 1 4 5 6 11 4 8 10 8 I 2 22 1 7 8 HYPERTENSION | 5. 1 6 .4 7.7 14. 1 5. 1 10.3 12.8 7.7 | 2.8 28 .2 | 5.4 4 1 11 14 15 12 7 11 5 3 I 6 14 1 98 DIABETES | 11.2 14 . 3 15.3 12.2 7. 1 11.2 5. 1 3. 1 | 6. 1 14 . 3 | 6 .6 5 1 8 15 12 11 9 9 6 1 1 5 10 1 86 IUGR 1 9 .3 17.4 14.0 12.8 10.5 10.5 7.0 1.2 | 5.8 11.6 1 5.9 B | 3 17 14 5 7 6 4 4 1 2 9 1 7 ' AP HEMORRAGE | 4.2 23 .9 19.7 7.0 9 .9 • 8 .5 5.6 5.6 1 2.8 12.7 | 4 .9 7 1 25 92 50 23 22 13 14 10 I 10 23 1 282 OTHER 1 8 .9 32.6 17.7 8 2 7.8 4.B 5.0 3 .5 | 3 .5 8.2 | 19.5 COLUMN 95 283 247 176 128 120 85 77 64 176 1449 TOTAL 6.6 19 5 17.0 12. 1 8 7 8 .3 5 .9 5 .3 4.4 12. 1 100.0 CHI-SQUARE D.F. 209.79450 83 STATISTIC SIGNIFICANCE 0.0000 CELLS WITH E.F .< 5 3.136 13 OF 80 ( 16.3X) SIGNIFICANCE CRAMER'S V 0.14382 Appendix A. Data Analysis Tables 65 Table A.24: Antepartum LOS by Delivery Type DELTYPE DELIVERY TYPE OF MOTHER DELHRS C R O S S T A B U L A T I O N O F BY DELHRS HOURS SPENT IN DELIVERY (ROUNDED UP) COUNT ROW PCT DELTYPE 1 SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION 5 PP ONLY 6 AP ONLY COLUMN TOTAL <2.4 HRS 4.8 HRS 7 2 HRS 9 6 HRS 12 HRS 14.4 HRS 18.8 HRS 19.2 HRS 21.6 HRS 24 HRS ROW OR MORE TOTAL 1 2| 3| 4 5| 6| 7 8 9 10| 17 133 | 146 | 117 77 I 6 1 I 48 38 31 7 3 I 741 2.3 17.9 | 19.7 | 15.8 10.4 1 8.2 | 6.5 5. 1 4.2 9.9 | 51 . 1 1 B 1 18 1 16 25 1 2 0 1 21 18 17 41 1 185 .5 4.3 | 9.7 | 8.6 13.5 1 10.8 | 11.4 9.7 9.2 22 2 | 12.8 5 62 1 16 I 9 3 1 1 1 1 1 1 I 119 4.2 68.9 | 13.4 | 7.6 2.5 1 8 | .8 .8 •8 1 8 2 8 1 40 I 18 1 1 1 2 8 1 13 15 10 45 1 188 4.3 I 21.3 | 9.6 5.9 1 1 4 9 | 6.9 8.0 5.3 23.9 | 13.0 14 3 1 1 I 1 1 | 1 1 1 21 86.7 14.3 | 4.8 | 4.8 4.8 I I 4.8 | 1.4 58 49 1 26 I 15 9 I 1 0 1 2 5 6 15 1 195 29.7 25. 1 I 13.3 | 7.7 4 6 1 5.1 | 1.0 2.6 3.1 7.7 | 13.5 95 283 247 176 126 120 85 77 64 176 1449 6.6 19.5 17.0 12. 1 8.7 8.3 5.9 5.3 4 4 12. 1 100.0 CHI-SOUARE D.F. 707.01833 45 STATISTIC CRAMER'S V SIGNIFICANCE 0.0000 CELLS WITH E.F.< 5 VALUE 0.31239 0.928 10 OF 60 ( 16.7%) SIGNIFICANCE Table A.25: Antepartum LOS by Geographical Residence C R O S S T A B U L A T I O N O F GEOGRAPHICAL REGION OF MOTHER BY DELHRS HOURS SPENT IN DELIVERY (ROUNDED UP) COUNT ROW PCT <2 .4 HRS 4 1| .8 HRS 7 2| 2 HRS 9 3| .6 HRS 4 12 HRS 14. 5| 4 HRS 16 6| 8 HRS 7 19.2 HRS 21 8| 6 HRS 24 HRS OR MORE 9| 10| ROW TOTAL VANCOUVER 47 1 5.9 | 165 1 20.8 | 154 1 19.4 | 91 11.5 66 I 8.3 | 7 1 I 8.9 | 49 8.2 34 1 4.3 1 34 1 83 1 4.3 | 10.5 | 794 54.8 GVRHD 32 1 6.2 1 94 1 18 1 | 7 7 I 14.8 | 69 13.3 51 1 9 8 | X I 3 ' 6.0 34 I 6.B | 24 I 70 1 4.6 1 13.5 | 519 35.8 REST OF B.C. 16 1 11.8 I 24 1 17.6 | 16 I 11.8 | IB 11.8 ..! 1 12 I 8 8 | 37- ..! 1 6 1 23 1 4.4 | 16.9 1 136 9.4 COLUMN TOTAL 95 6.6 283 19.5 247 17.0 176 12. 1 126 8.7 120 8.3 B5 5.9 77 5.3 64 176 4.4 12.1 1449 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 27.73489 18 0. 0662 6 .007 NONE SIGNIFICANCE CRAMER'S V 0.09783 Appendix A. Data Analysis Tables 66 Table A.26: Antepartum LOS by PP Complication POST PARTUM COMPLICATION APDAYS C R O S S T A B U L A T I O N O F BY APDAYS DAYS SPENT IN ANTE PARTUM (ROUNDED UP) COUNT ROW PCT STATISTIC CRAMER'S V VALUE 0.09274 SIGNIFICANCE 8 DAYS ROW OR MORE TOTAL o | 1| 2| 3| 4| 5| 6| 7| 8 PP2 1 985 I 111 | 51 I 29 I 25 I 20 I \ I 63 NONE 75.7 | 8.5 | 3.9 I 2.2 | 1.9 I •5 I •1 I •3 1 4.8 2 127 I 10 I 3 I 1 I I 2 I I I 1 3 SOME 86.4 | 6.8 | 2.0 | 7 | I 4 | I 7 | 2.0 COLUMN 1112 121 54 30 25 22 14 5 66 TOTAL 76.7 8.4 3.7 2.1 1 . 7 .5 .0 . 3 4 .6 CHI-SQUARE D.F. SIGNIFICANCE MIN E .F. CELLS WITH E.F.< 5 12.46286 8 0 1317 0. 507 6 OF 18 ( 33.3%) 1302 89.9 147 10. 1 Table A.27: Antepartum LOS by Sterilization STERILIZATION (YES/NO) APDAYS C R O S S T A B U L A T I O N O F BY APDAYS DAYS SPENT IN ANTE PARTUM (ROUNDED UP) STER COUNT ROW PCT °l 21 6| 8 DAYS ROW OR MORE TOTAL 7| 8| NO STERILIZATION 2 STERILIZATION COLUMN TOTAL CHI-SQUARE D.F. 6.30764 8 STATISTIC 1053 I 1 1 7 I 52 I 30 23 I 22 I 14 1 5 I 61 1 1377 76.5 I 8.5 | 3.8 | 2.2 1.7 I 6 | 1.0 1 4 | 4.4 | 95.0 59 I 4 I 2 I 2 I I 1 I 5 I 7 2 81.9 I 5.6 I 2.8 | 2.8 I I 1 I 6.9 | 5.0 1112 121 54 30 25 22 14 5 66 1449 76.7 8.4 3.7 2.1 1 . 7 .5 .0 . 3 4.6 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 0.6128 0 .248 8 OF 18 ( 44.4%) VALUE SIGNIFICANCE CRAMER'S V 0.06598 Appendix A. Data Analysis Tables 67 Table A.28: Delivery Suite LOS by AP Category ANTE PARTUM COMPLICATION C R O S S T A B U L A T I O N BY APDAYS DAYS SPENT IN ANTE PARTUM (ROUNDED UP) APDAYS AP2 COUNT ROW PCT 0| 2| 3| 1| 5| 8 DAYS ROW OR MORE TOTAL 7| 8| 0 I 507 33 9 I S 1 4 | 3 1 2 I 1 6 I 571 NO ANTEPARTUM I B B S 5 . 8 1.6 | 1.1 | • 7 I •5 1 .4 | .2 1 . 1 | 3 9 . 4 1 I 42 7 10 I 2 I 3 1 1 I 12 I 7 7 PRETERM LABOUR I 5 4 . 5 9 . 1 1 3 . 0 | 2 . 6 | 3 . 9 | 1.3 I 1 5 . 6 I 5 . 3 2 I 132 31 3 I 3 I 5 I 4 1 1 1 1 6 I 186 RUPTURE I 7 1 . 0 16. 7 1.8 | 1.6 I 2 . 7 | 2 . 2 1 5 I . 5 3 . 2 | 1 2 . 8 3 I 49 8 8 I 1 I 4 1 2 1 1 I 1 4 1 7 8 HYPERTENSION I 6 2 . 8 1 0 . 3 1 0 . 3 I 1.3 I 5 . 1 | 2 . 6 | 1.3 I 1 . 3 5. 1 1 5 . 4 4 I 70 7 5 I 3 I 1 I 2 | 1 9 | 98 D I A B E T E S I 7 1 . 4 7 . 1 5 . 1 | 3 . 1 I 1.0 | 2 . 0 | 1.0 9 . 2 1 6 . 8 5 I 64 7 1 I 3 I 1 I 3 I 1 7 1 86 IUGR I 7 4 . 4 8 . 1 1 .2 | 3 . 5 I 1.2 | 3 . 5 I I 8 . 1 1 5 . 9 6 I 32 6 11 I 3 I 3 I 4 I 1 I 1 10 1 7 1 AP HEMORRAGE I 45 . 1 8 . 5 1 5 . 5 | 4 2 I 4 . 2 | 5 . 6 | 1.4 | 1 .4 14. 1 | 4 . 9 7 I 216 22 7 1 12 1 5 I 2 I 6 I 12 1 282 OTHER I 7 6 . 6 7 . 8 2 . 5 | 4 3 | 1.8 I • 7 I 2 1 I 4 . 3 1 1 9 . 5 COLUMN 1112 121 54 30 25 22 14 5 66 1449 TOTAL 76 . 7 8 . 4 3 . 7 2. 1 1 . 7 1.5 1 .0 .3 4 . 6 1 0 0 . 0 C H I - S Q U A R E D . F . 2 3 7 . 2 4 8 4 3 56 S T A T I S T I C S I G N I F I C A N C E 0 . 0 0 0 0 VALUE MIN E . F . C E L L S WITH E . F . < 5 0 . 2 4 5 45 OF 72 ( 62.5%) S I G N I F I C A N C E C R A M E R ' S V 0 . 1 5 2 9 4 Appendix A. Data Analysis Tables 68 Table A.29: Delivery Suite LOS by Delivery Type DELTYPE DELIVERY TYPE OF MOTHER C R O S S T A B U L A T I O N O F BY APDAYS DAYS SPENT IN ANTE PARTUM (ROUNDED UP I COUNT ROW PCT DELTYPE SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION 5 PP ONLY 6 AP ONLY COLUMN TOTAL 8 DAYS ROW OR MORE TOTAL 'I 2| 3| 4I 5| B| 7| 8| 641 1 55 | 10 I 3 1 5 1 5 I 4 I 2 1 16 1 741 86.5 | 7.4 1.3 I .4 1 • 7 I 7 | •5 I 3 1 2.2 1 51 . 1 164 I 16 I 1 I 1 I 1 1 I I I 2 1 185 88.6 | 8.6 | 5 I •5 I 1 5 | 1 1.1 | 12.8 113 I 1 I I 1 I I | | 5 I 119 95.0 I •8 I I I 1 I 1 1 4 2 I 8.2 144 I 21 I 14 I 2 I 2 1 I I 1 1 4 I 188 76.6 | 11.2 7.4 | 1.1 | 1.1 | I 1 5 1 2.1 | 13.0 21 I I I 1 I I 1 1 I 21 100.0 I I I I I 1 1 I 1.4 29 I 28 29 I 24 I 18 I 16 I 10 I 2 1 39 I 195 14.9 | 14.4 14.9 | 12.3 | 9.2 | 8.2 | 5.1 | 1.0 | 20.0 | 13.5 1112 121 54 30 25 22 14 5 66 1449 76.7 8.4 3.7 2. 1 1. 7 1.5 1.0 . 3 4.6 100.0 CHI-SQUARE D.F. SIGNIFICANCE CELLS WITH E.F.< 5 652.00767 40 STATISTIC 0.072 30 OF 54 ( 55.6%) SIGNIFICANCE CRAMER'S V 0.29999 Table A.30: Delivery Suite LOS by Geographical Residence GEOG GEOGRAPHICAL REGION OF MOTHER APDAYS C R O S S T A B U L A T I O N O F BY APDAYS DAYS SPENT IN ANTE PARTUM (ROUNDED UP) COUNT ROW PCT GEOG VANCOUVER GVRHD REST OF B.C. Ol 1| 2| 4| 5| 6| COLUMN TOTAL CHI-SQUARE D.F. 84.82282 16 STATISTIC CRAMER'S V VALUE 0. 17108 SIGNIFICANCE 8 DAYS ROW OR MORE TOTAL 7| 8| 652 I 6 4 I 23 I 13 9 I 7 I 4 I 1 21 82. 1 I 8.1 | 2.9 | 1.6 1.1 I 9 I •5 I •1 2.6 387 I 4 3 I 22 1 13 10 I 1 0 I 4 I 3 27 74.6 I 8.3 | 4.2 I 2.5 1.9 I 1 9 1 •8 I •6 5.2 73 I 1 4 1 9 I 4 6 1 5 1 6 I 1 18 53.7 1 10.3 | 6.6 | 2.9 4.4 1 3.7 | 4.4 | .7 13.2 1112 121 54 30 25 22 14 5 66 76.7 8.4 3.7 2. 1 1 . 7 1.5 1.0 . 3 4.6 SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 0.0000 0 .469 7 OF 27 ( 25.9%) 794 54.8 519 35.8 136 9.4 1449 100.0 Appendix A. Data. Analysis Tables 69 Table A.31: Delivery Suite LOS by PP Complication POST PARTUM COMPLICATION DELHRS C R O S S T A B U L A T I O N O F BV DELHRS HOURS SPENT IN DELIVERY (ROUNDED UP) COUNT ROW PCT <2.4 HRS 4.8 HRS 7 2 HRS 9 .6 HRS 12 HRS 14.4 HRS 16 8 HRS 19.2 HRS 21 6 HRS 24 HRS ROW OR MORE TOTAL PP2 1| 2| 3| 4 5| B| 7 B| 9| 10| 1 90 1 268 1 229 I 159 114 1 103 I 71 7 1 I 55 1 142 1 1302 NONE 6.9 | 20.6 | 17.6 | 12.2 B.8 1 7.9 | 5.5 5.5 | 4.2 1 10.9 | 89.9 2 1 5 1 15 I 18 1 17 12 1 1 7 1 14 6 I 9 1 34 1 147 SOME 3 4 | 10.2 | 12.2 | 11.6 8.2 | 11.6 | 9.5 4.1 1 6.1 | 23. 1 1 10. 1 COLUMN 95 283 247 17B 126 120 85 77 64 176 1449 TOTAL B.B 19.5 17.0 12. 1 8.7 8.3 5.9 5.3 4.4 12. 1 100.0 CHI-SQUARE O.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 35.73344 9 0 .0000 6 .493 NONE STATISTIC CRAMER S V VALUE 0.15704 SIGNIFICANCE Table A.32: DeUvery Suite LOS by Sterilization STERILIZATION (YES/NO) C R O S S T A B U L A T I O N O F BY DELHRS HOURS SPENT IN DELIVERY (ROUNDED UP I COUNT ROW PCT DELHRS <2.4 HRS 4.8 HRS 7.2 HRS 9.6 HRS 12 HRS 14.4 HRS 16.8 HRS 19.2 HRS 21.6 HRS 24 HRS ROW OR MORE TOTAL 1| 2| 3| 4| 5| 6| 7| 8| 9| 10| NO STERILIZATION 2 STERILIZATION COLUMN TOTAL 93 B.B 258 18.7 235 17.1 188 12.2 1 IB 8.4 1 18 83 B O 74 5.4 2 2.8 25 34 . 7 12 16.7 8 11.1 10 13.9 2 2.8 2 2.8 3 4.2 95 6.6 283 19.5 247 17.0 176 12. 1 126 8.7 120 8.3 85 5.9 77 5.3 63 4.6 1 1 .4 64 4.4 169 12.3 7 3 .7 176 12. 1 1377 95.0 72 5.0 1449 100.0 CHI-SQUARE D.F. 19.15566 9 STATISTIC SIGNIFICANCE 3. 180 4 OF SIGNIFICANCE CELLS WITH E.F.< 5 20 ( 20.OX) CRAMER'S V 0.11498 Appendix A. Data Analysis Tables 70 Table A.33: Postpartum LOS by AP Category ANTE PARTUM COMPLICATION C R O S S T A B U L A T I O N BY PPDAYS O F - -DAYS SPENT IN POST PARTUM (ROUNDED UP) PPDAYS COUNT ROW PCT AP2 4| 5| 8 DAYS ROW OR MORE TOTAL 7| 8| 0 1 6 33 203 160 65 23 I 3 1 2 I 495 NO ANTEPARTUM 1 1.2 6 . 7 41.0 32.3 13. 1 4.6 | •6 | .4 | 40. 1 1 1 2 3 12 21 5 5 I 2 1 2 1 5 2 PRETERM LABOUR 1 3.8 5.8 23. 1 40.4 9.6 9.6 | 3.8 | 3.8 1 4.2 2 1 1 6 67 50 26 20 I 1 I 2 1 , 7 3 RUPTURE 1 6 3.5 38. 7 28.9 15.0 11.6 | •6 I 1 .2 | 14.0 3 1 1 9 24 16 9 8 1 1 I 2 I 7 0 HYPERTENSION 1 1.4 12.9 34.3 22.9 12.9 11.4 | 1.4 | 2.9 I 5.7 4 I 1 3 23 20 21 11 I 4 1 2 I 84 DIABETES 1 3.8 27 .4 23.8 25.0 13.1 | . 4.8 | 2.4 I 6.8 5 1 1 2 38 15 14 6 I 1 1 1 I 7 8 IUGR 1 1.3 2.6 48. 7 19.2 17.9 7.7 | 1.3 | 1.3 I B.3 6 1 1 14 7 12 5 I 4 I 1 I 44 AP HEMORRAGE 1 2.3 31.8 15.9 27.3 11.4 | 9.1 | 2.3 | 3.6 7 I 4 10 48 52 82 32 I 6 I 3 | 237 OTHER 1 1.7 4.2 20.3 21 .9 34.6 13.5 | 2.5 | 1 . 3 | 19.2 COLUMN 16 66 429 341 234 1 10 22 15 1233 TOTAL 1 . 3 5.4 34.8 27.7 19.0 8.9 1 .8 1 . 2 100.0 CHI-SQUARE D.F. 164.06009 49 STATISTIC SIGNIFICANCE 0.0000 VALUE MIN E.F. CELLS WITH E.F.< 5 0.535 28 OF 64 ( 43.8«> SIGNIFICANCE CRAMER'S V 0.13787 Appendix A. Data. Analysis Tables 71 Table A.34: Postpartum LOS by Delivery Type DELTYPE DELIVERY TYPE OF MOTHER PPDAYS C R O S S T A B U L A T I O N O F BY PPDAYS DAYS SPENT IN POST PARTUM (ROUNDED UP) COUNT ROW PCT DELTYPE 1 SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION PP ONLY COLUMN TOTAL CHI-SQUARE D.F. 780.37991 28 STATISTIC 1 2| 6| 8 DAYS ROW OR MORE TOTAL 7| 8| 14 I 5 1 1 341 I 253 I 49 I 1 3 1 3 1 2 I 726 1.9 1 7.0 1 47.0 | 34.8 | 6.7 I 1-8 1 4 I . 3 I 58.9 2 1 9 1 85 I 64 | 17 1 * 2 I 183 1 . 1 1 4.9 1 46.4 | 35.0 9.3 | 2.2 1 . 1 I 14.8 1 1 11 | 66 1 3 3 1 7 1 2 I 119 1 1 9.2 | 55.5 | 27.7 1 5.9 | 1 . 7 I 9-7 1 1 I 2 I 9 I 98 1 58 1 1 1 1 9 | 188 I -5 I 1.1 I 4.6 I 52. 1 | 30.9 1 5.9 1 4.8 [ 15.2 I 5 I 1 I 4 | 4 1 2 1 1 1 I 1 7 I 29.4 | 5.9 I 23. 5 23.5 | 11.8 1 5.9 1 I 1 -4 16 66 429 341 234 1 10 22 15 1233 1 . 3 5.4 34.8 27.7 19.0 8.9 1.8 1 . 2 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F. < 5 0.0000 0.207 16 OF 40 ( 40 .OX) CRAMER'S V VALUE 0.39778 SIGNIFICANCE Table A.35: Postpartum LOS by Geographical Residence GEOG C R O S S T A B U L A T I O N O F GEOGRAPHICAL REGION OF MOTHER BY PPDAYS DAYS SPENT IN POST PARTUM (ROUNDED UP) PPDAYS COUNT ROW PCT VANCOUVER GVRHD REST OF B.C. COLUMN TOTAL CHI-SQUARE D.F. 14.81379 14 STATISTIC 2| 4| 5| 8 DAYS ROW OR MORE TOTAL 7| 8| 9 I 4 3 I 252 1 191 127 I 8 1 I 12 | 5 I 700 1 . 3 I 6.1 | 36.0 | 27 . 3 18. 1 I S 7 I 1.7 | . 7 I 56.8 4 I 1 8 I 147 I 125 87 I 3 9 I 6 I 7 I 433 .9 I 4.2 | 33.9 | 28.9 20. 1 | 9.0 I 1.4 | 1.6 I 35. 1 3 I 5 I 30 I 25 20 I 1 0 1 4 I 3 I 100 3.0 I 5.0 | 30.0 | 25.0 20.0 I 10.0 I 4.0 | 3.0 I 8. 1 16 66 429 341 234 110 22 15 1233 1. 3 5.4 34.8 27.7 19.0 8.9 1.8 1.2 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F. < 5 0.3910 .217 3 OF 24 ( 12 .5X> SIGNIFICANCE CRAMER'S V 0.07751 Appendix A. Data Analysis Tables 72 Table A.36: Postpartum LOS by PP Complication POST PARTUM COMPLICATION C R O S S T A B U L A T I O N O F BY PPDAYS DAYS SPENT IN POST PARTUM (ROUNDED UP) PP2 NONE SOME COUNT ROW PCT COLUMN TOTAL 2| <l 5| 6| 8 DAYS OR MORE 16 1.5 16 1 . 3 62 5.7 393 36.0 296 27. 1 201 18.4 99 9. 1 16 1.5 4 2.8 36 25.4 45 31.7 33 23.2 11 7.7 6 4.2 66 5.4 429 34.8 341 27.7 234 19.0 110 8.9 22 1.8 7 4.9 15 1.2 ROW TOTAL 1091 88.5 142 11.5 1233 100.0 CHI-SQUARE O.F. 34.39632 7 STATISTIC CRAMER'S V SIGNIFICANCE 0.0000 VALUE 0. 16702 MIN E.F. CELLS WITH E.F.< 5 1.727 3 OF 16 ( 18.8*) SIGNIFICANCE Table A.37: Postpartum LOS by Sterilization STER STERILIZATION (YES/NO) PPDAYS C R O S S T A B U L A T I O N O F BY PPDAYS DAYS SPENT IN POST PARTUM (ROUNDED UP) COUNT ROW PCT STER 1 NO STERILIZATION 2 STERILIZATION COLUMN TOTAL 'I 2| 4| 5| 6| 7| 8 DAYS OR MORE 16 1.4 16 1 . 3 65 1 419 I 325 I 203 I 100 I 18 5.6 1 36. 1 1 28.0 | 17.5 | 8.6 | 1.6 + - * + . + . ....+. 1 I 10 I 16 I 3 1 I 10 1 4 1.4 | 13.9 | 22.2 | 43. 1 | 13.9 | 5.6 66 429 341 234 110 22 5.4 34.8 27.7 19.0 8.9 1 .8 15 1 . 3 ROW TOTAL 1161 94.2 72 5.8 15 1233 1.2 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 46.15509 7 STATISTIC 0.0000 VALUE 0.876 4 OF 16 ( 25.OX) SIGNIFICANCE CRAMER'S V 0.19348 Appendix A. Data Analysis Tables Table A.38: Discharge Day of Week for Adult Patients DEL DELIVERY TYPE C R O S S T A B U L A T I O N BY DISDAY O F DISCHARGE DAY OF WEEK COUNT ROW PCT DISDAY SUNDAY DEL TUESDAY WEDNES-DAY 2| 3| 4| THURSDAY FRIDAY SATURDAY ROW TOTAL 5| 6| 7| 1 I 111 108 111 92 87 116 116 I 741 SPONTANEOUS | 15.0 14.6 15.0 12.4 11.7 15.7 15.7 1 51.1 2 I 25 26 24 28 22 22 38 I 185 INSTRUMENTAL | 13.5 14 . 1 13.0 15. 1 11.9 11.9 20.5 1 12.8 3 I 1 5 2 4 3 2 I 1 7 ELEC C-SECTION | 5.9 29.4 11.8 23.5 17.6 11.8 I 1 2 4 I 18 21 24 44 20 41 20 | 188 EM C-SECTION | 9.6 11.2 12.8 23.4 10.6 21 .8 10.6 | 13.0 5 I 2 2 3 6 1 6 1 I 2 1 PP-ONLY | 9.5 9.5 14.3 28.6 4.8 28.6 4.8 1 1 4 6 I 20 30 28 27 23 44 23 I 195 AP-ONLY | 10.3 15.4 14.4 13.8 11.8 22.6 11.8 I 13.5 9 I 17 26 19 16 5 19 1 102 DOS (ELEC-C) | 16.7 25.5 18.6 15.7 4.9 18.6 I 7.0 COLUMN 194 218 211 217 156 234 219 1449 TOTAL 13.4 15.0 14.6 15.0 10.8 16. 1 15. 1 100.0 CHI-SQUARE D.F. 84.02341 36 STATISTIC SIGNIFICANCE VALUE MIN E.F. CELLS WITH E.F.< 5 1.830 14 OF 49 ( 28.6%) SIGNIFICANCE CRAMER'S V 0.09831 Appendix A. Data Analysis Tables 74 Table A.39: Discharge Time of Day for Adult Patients DELIVERY TYPE DIST C R O S S T A B U L A T I O N O F BY DIST DISCHARGE TIME OF DAY (HRS) COUNT ROW PCT OFF-PEAK 8 - 9 1 8 - 7 11 2| 1 I 4 5 1 3 1 2 8 I 1 0 9 I 1 7 8 I 1 4 8 1 108 6 9 I 36 17 1 741 SPONTANEOUS | 6 . 1 1 4 1 3 . 8 I 1 4 . 7 1 2 4 . 0 I 2 0 . 0 | 1 4 . 6 9 . 3 | 4 . 9 2 . 3 | 5 1 . 1 2 I 10 1 3 1 7 I 2 5 1 3 7 I 4 2 1 , 9 2 2 I 13 7 1 1 8 5 INSTRUMENTAL | 5 . 4 1 1 6 | 3 . 8 | 1 3 . 5 1 2 0 . 0 | 2 2 . 7 1 1 0 . 3 1 1 . 9 I 7 . 0 3 . 8 | 1 2 . 8 3 I 3 | j 1 I 1 1 5 I 5 1 2 1 1 7 ELEC C-SECTION | 1 7 . 8 1 1 5 . 9 | 5 . 9 | 2 9 . 4 I 2 9 . 4 | 1 1 . 8 1 1 2 4 I 13 1 1 I 3 I 34 1 5 5 I 3 7 I , 6 IB 1 7 6 1 1 8 8 EM C-SECTION | 6 . 9 I 5 I 1 . 6 I 1 8 . 1 | 2 9 . 3 | 1 9 . 7 I 8 . 5 8 . 5 1 3 . 7 3 . 2 | 1 3 . 0 5 I 4 1 I 1 1 1 6 1 3 I 2 2 1 3 1 21 PP-ONLY | 1 9 . 0 I I I 4 . 8 | 2 8 . 6 | 1 4 . 3 | 9 . 5 9 . 5 | 1 4 . 3 1 1 4 6 I 39 I 3 I 10 1 19 1 3 0 1 2 6 I 1 8 1 19 | 19 12 | 1 9 6 AP-ONLY | 2 0 . 0 I 1 - 5 | 5 . 1 | 9 . 7 1 1 5 . 4 1 1 3 . 3 [ 9 . 2 9 . 7 | 9 . 7 6 . 2 1 1 3 . 5 9 I 6 1 1 2 I 13 I 2 9 1 2 3 1 1 0 I 12 I 4 3 1 1 0 2 DOS (ELEC-C) | 5 . 9 I I 2 . 0 | 1 2 . 7 | 2 8 4 | 2 2 . 5 I 9 . 8 1 1 . 8 | 3 . 9 2 . 9 I 7 . 0 COLUMN 1 2 0 10 51 2 0 2 3 4 0 2 8 4 1 7 5 1 4 0 79 4 8 1 4 4 9 TOTAL 8 . 3 . 7 3 . 5 1 3 . 9 2 3 . 5 1 9 . 6 1 2 . 1 9 . 7 5 . 5 3 . 3 1 0 0 . 0 CHI-SQUARE D.F. SIGNIFICANCE MIN E .F. CELLS WITH E.F. < 5 1 1 8 . 9 2 5 1 8 5 4 0 . 0 0 0 0 0 . 117 2 6 OF 7 0 ( 37 . 1%) 9 | 1 0 | ROW TOTAL SIGNIFICANCE CRAMER'S V 0 . 1 1 6 9 6 Appendix A. Data Analysis Tables Table A.40: Delivery Type by Geographical Residence DELTYPE DELIVERY TYPE OF MOTHER GEOG C R O S S T A B U L A T I O N O F BY GEOG GEOGRAPHICAL REGION OF MOTHER COUNT ROW PCT VANCOUVE GVRHD R 11 REST OF ROW B.C. TOTAL 3| DELTYPE - * - - + - - + - - + 1 1 422 I 262 1 57 1 741 SPONTANEOUS 1 + -57 .0 I - + -35. 4 1 - + -7.7 1 51 . 1 2 1 104 71 1 10 185 INSTRUMENTAL 1 + -56.2 - + -38.4 1 - + -5.4 | 12.8 3 1 67 I 43 1 9 119 ELEC C-SECTION 1 56.3 I 36. 1 1 7.6 | 8.2 •f - - + - - + - + 4 1 104 I 63 1 21 1 188 EM C-SECTION 1 55. 3 I 33.5 1 11.2 I 13.0 + -5 I 9 I 7 I 5 I 21 PP-ONLY I 42.9 I 33.3 I 23.8 I 1.4 + - - + + - + 6 I 86 I 7 3 I 34 I 195 AP-ONLY | 45. 1 I 37.4 I 17.4 | 13.5 + - - - - - - - -COLUMN 794 519 136 1449 TOTAL 54.8 35.8 9.4 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. 30.03521 10 0.0008 .971 STATISTIC 1 OF SIGNIFICANCE CELLS WITH E.F.< 5 18 ( 5.6%) CRAMER'S V 0.10180 Appendix A. Data Analysis Tables. Table A.41: Delivery Type by AP Category DELTYPE DELIVERY TYPE OF MOTHER AP2 C R O S S T A B U L A T I O N O F BY AP2 ANTE PARTUM COMPLICATION COUNT ROW PCT DELTYPE t SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION 5 PP-ONLY 6 AP-ONLY COLUMN TOTAL CHI-SQUARE D.F. 335.18700 35 STATISTIC NO ANTEP PRETERM RUPTURE HYPERTEN DIABETES IUGR AP HEMOR OTHER ROW ARTUM LABOUR SION RAGE TOTAL °l 1 2| 3| 4 I 5| 6 7| 341 I 36 109 I 42 I 47 I 4 6 I 21 99 I 741 46.0 | 4.9 14.7 | 5.7 | 6.3 I 6.2 | 2.8 13.4 | 51.1 B2 I 8 33 I 12 1 6 I 1 6 I 6 22 I 185 44.3 | 4.3 17.8 | 6.5 | 3.2 I 8 8 I 3.2 11.9 | 12.8 12 1 3 1 10 I 10 1 5 79 I 119 10. 1 | 2.5 1 8.4 1 8.4 1 4.2 66.4 | 8.2 49 I 10 33 I 1 3 I 21 I 7 1 15 40 I 188 26. 1 | 5.3 17.6 | 6.9 | 11.2 1 3-7 1 8.0 21.3 | 13.0 20 I I 1 1 21 95.2 | I 4.8 | 1.4 67 1 23 11 I 8 I 14 1 7 1 24 41 1 195 34.4 | 11.8 5.6 | 4.1 1 7.2 3.6 1 12.3 21.0 | 13.5 571 77 186 78 98 86 71 282 1449 39.4 5.3 12.8 5.4 6.8 5.9 4.9 19.5 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 0 .0000 1 .029 7 OF 48 ( 14. 6X1 SIGNIFICANCE CRAMER'S V 0.21509 Appendix A. Data Analysis Tables Table A.42: Delivery Type by PP Complication DELTYPE DELIVERY TYPE OF MOTHER PP2 C R O S S T A B U L A T I O N O F BY PP2 POST PARTUM COMPLICATION COUNT ROW PCT NONE SOME DELTYPE 1 SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION 5 PP-ONLY 6 AP-ONLY COLUMN TOTAL 2| ROW TOTAL 681 60 91.9 8.1 157 28 84.9 15. 1 106 13 89. 1 10.9 153 81.4 10 47.6 195 100.0 1302 89.9 35 18.6 11 52.4 147 10. 1 741 51 . 1 185 12.8 119 8.2 188 13.0 21 1.4 195 13.5 1449 100.0 CHI-SQUARE D.F. 88.45632 5 STATISTIC SIGNIFICANCE MIN E.F. 2 . 130 1 OF SIGNIFICANCE CELLS WITH E.F.< 5 12 ( 8.3%) CRAMER'S V 0.24427 Appendix A. Data, Analysis Tables Table A.43: Delivery Type by Sterilization C R O S S T A B U L A T I O N O F DELTYPE DELIVERY TYPE OF MOTHER BY STER2 STERILIZATION (YES/NO) COUNT ROW PCT DELTYPE 1 SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION 5 PP-ONLY 6 AP-ONLY STER2 NO 1| YES 2| ROW TOTAL 710 I 95.8 | 31 4.2 1 741 51 . 1 184 I 99.5 | 1 .5 1 165 12.8 90 I 75.6 | 29 24.4 1 119 8.2 177 I 94. 1 | 11 5.9 1 188 13.0 21 I 100.0 | 1 21 1 .4 195 1 100.0 | 1 195 13.5 1377 95.0 72 5.0 1449 100.0 COLUMN TOTAL CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 115.10913 5 0.0000 1.043 1 OF 12 ( 8.3*) STATISTIC VALUE SIGNIFICANCE CRAMER'S V 0.28185 Appendix A. Data Analysis Tables 79 Table A.44: Geographical Residence by AP Category GEOG - • - C R O S S T A B U L A T I O N O F GEOGRAPHICAL REGION OF MOTHER BY AP? ANTE PARTUM COMPLICATION COUNT RbW PCT AP2 NO ANTEP PRETERM RUPTURE HYPERTEN DIABETES IUGR AP HEMOR OTHER ROW ARTUM LABOUR SION RAGE TOTAL 0| 1| 2| 3| 41 5| 6| 7| VANCOUVER 1 | 353 44.5 I £ | 108 1 13.6 | 32 4.0 49 6.2 | 6.5 1 <36s 135 17.0 GVRHD 2 I 192 37 .0 I 6.2 | 59 1 11.4 | 37 7. 1 39 7.5 1 28 | 5.4 | 4.8 107 20.6 REST OF B c 3 I 26 19. 1 I „ ! ! • I 19 I 14.0 | 9 6.6 10 7.4 1 8 1 4.4 1 ^ 40 29.4 COLUMN TOTAL 571 39.4 77 5.3 186 12.8 78 5.4 98 6.8 86 5.9 71 4.9 282 19.5 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F < 5 56.83455 14 0.0000 6 .664 NONE STATISTIC VALUE SIGNIFICANCE 794 54.8 519 35.8 136 9.4 1449 100.0 CRAMER'S V 0.14004 Table A.45: Geographical Residence by Delivery Type GEOG C R O S S T A B U L A T I O N O F GEOGRAPHICAL REGION OF MOTHER BY STER2 STERILIZATION (YES/NO) COUNT ROW PCT STER2 GEOG VANCOUVER GVRHD REST OF B.C. COLUMN TOTAL 756 95.2 YES 2| ROW TOTAL 38 4.8 491 I 28 94.6 I 5.4 130 1 6 95.6 1 4 . 4 1377 72 5.0 794 54.8 519 35.8 136 9.4 1449 100.0 CHI-SQUARE D.F. 0.34526 2 STATISTIC SIGNIFICANCE 0.8415 VALUE MIN E.F. CELLS WITH E.F.< 5 6.75B NONE SIGNIFICANCE CRAMER'S V 0.01544 Appendix A. Data. Analysis Tables Table A.46: Geographical Residence by PP Complication C R O S S T A B U L A T I O N O F GEOG GEOGRAPHICAL REGION OF MOTHER BY PP2 POST PARTUM COMPLICATION PP2 COUNT ROW PCT GEOG 1 VANCOUVER 2 GVRHD 3 REST OF B.C. NONE SOME ROW TOTAL 1| 2| 707 89.0 87 11.0 I 794 54.8 470 90.6 49 9.4 I 519 35.8 125 91.9 11 8. 1 I 136 9.4 1302 147 1449 COLUMN TOTAL 89.9 10.1 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 1.48767 2 0.4753 13.797 NONE STATISTIC VALUE SIGNIFICANCE CRAMER'S V 0.03204 Appendix A. Data, Analysis Tables Table A.47: AP Category by PP Complication AP2 ANTE PARTUM COMPLICATION C R O S S T A B U L A T I O N O F BY PP2 POST PARTUM COMPLICATION COUNT ROW PCT PP2 NONE SOME 1| 2| ROW TOTAL 0 NO ANTEPARTUM 509 89. 1 I 6 2 I I 1 0 9 1 571 39.4 1 PRETERM LABOUR 69 89.6 1 8 1 1 104 | 77 5.3 2 RUPTURE 165 88.7 I 2 1 I I 11-3 | 186 12.8 3 HYPERTENSION 68 87.2 I 1 0 I I 12.8 | 78 5.4 4 DIABETES 89 90.8 1 9 1 1 9.2 | 98 6.8 5 IUGR 75 87 . 2 1 1 1 I I 12- 8 I 86 5.9 B AP HEMORRAGE 68 95.8 I 3 I I 4.2 I 71 4.9 7 OTHER 259 91.8 I 2 3 I I 8.2 | 282 19.5 COLUMN TOTAL 1302 89.9 147 10. 1 1449 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH 5.91667 7 0.5495 7 .203 NONE STATISTIC VALUE SIGNIFICANCE CRAMER'S V 0.06390 Appendix A. Data Analysis Tables % Table A.48: AP Category by Sterilization AP2 ANTE PARTUM COMPLICATION STER2 C R O S S T A B U L A T I O N O F BY STER2 STERILIZATION (YES/NO) COUNT ROW PCT NO YES 1 ROW TOTAL NO ANTEPARTUM 0 I 557 97.5 I 1 4 1 1 2 5 | 571 39.4 1 I PRETERM LABOUR | 74 96. 1 1 3 1 1 3 9 I 77 5.3 RUPTURE 2 I 179 96.2 1 7 1 1 3.8 | 186 12.8 HYPERTENSION 3 I 74 94.9 1 4 | 1 5.1 j 78 5.4 DIABETES 4 I 89 90.8 1 9 1 1 9.2 1 98 6.8 IUGR 5 I 83 96.5 1 3 1 1 3.5 | 88 5.9 AP HEMORRAGE 6 I 67 94.4 1 4 1 1 5.6 1 71 4.9 OTHER 7 I 254 90. 1 1 28 1 1 9.9 | 282 19.5 COLUMN TOTAL 1377 95.0 72 5.0 1449 100.0 CHI-SQUARE D.F. SIGNIFICANCE 27.27096 7 0.0003 STATISTIC CRAMER'S V 3.528 5 OF SIGNIFICANCE CELLS WITH E.F.< 5 16 ( 31.3%) 0.13719 Table A.49: PP Complication by Sterilization PP2 POST PARTUM COMPLICATION STER2 C R O S S T A B U L A T I O N O F BY STER2 STERILIZATION (YES/NO) COUNT ROW PCT NO YES 1| 2| ROW TOTAL NONE 1 I 1235 1 94.9 | 67 5. 1 I 1302 | 89.9 SOME 2 I 142 I 96.6 | 5 3.4 1 147 | 10. 1 COLUMN TOTAL 1377 95.0 72 5.0 1449 100.0 CHI-SQUARE D.F. 0.52198 1 0.85135 1 SIGNIFICANCE 0.4700 0.3562 CELLS WITH E.F.< 5 7.304 NONE ( BEFORE YATES CORRECTION ) STATISTIC SIGNIFICANCE PHI 0 02424 Appendix A. Data Analysis Tables 83 Table A.50: Total LOS Newborns Versus Pediatric Babies BABY NEWBORN VS. PEDIATRIC C R O S S T A B U L A T I O N O F BY TOTDAYS DAYS SPENT IN THE HOSPITAL (ROUNDED UP) BABY COUNT ROW PCT < 2.4 HOURS NEWBORN PEDIATRIC CHI-SQUARE D.F. 134.95702 STATISTIC 0| 2| 3| 5| 8 DAYS ROW OR MORE TOTAL 7| B| 43 I 11 I 45 I 359 345 I 188 I 134 I 32 29 1 1186 3.6 | .9 | 3.8 | 30.3 29. 1 I 15.9 | 11.3 | 2.7 2.4 I 98. 1 I 1 1 2 I 2 2 I " I I 10 1 2 3 1 4.3 1 8.7 | 8.7 8.7 I I ? - 4 1 I 8.7 43.5 1 1-9 - + 43 12 47 361 347 192 134 34 39 1209 3.6 1.0 3.9 29.9 28.7 15.9 11.1 2.8 3.2 100.0 SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 0.0000 0 .228 7 OF 18 ( 38.9%) VALUE SIGNIFICANCE CRAMER'S V Table A.51: Total LOS by Birthweight C R O S S T A B U L A T I O N O F BWEIGHT2 BIRTH WEIGHT (NOT INCLUDING "SHORT STAY") BY TOTDAYS DAYS SPENT IN THE HOSPITAL (ROUNDED UP) COUNT ROW PCT BWEIGHT2 LESS THAN 2500 G MORE THAN 2500 G COLUMN TOTAL CHI-SQUARE O.F. 49.27039 8 STATISTIC TOTDAYS < 2.4 8 DAYS ROW HOURS OR MORE TOTAL o| 1| 2| 3| 4| 5| B| 7| 8| 1 I 2 I 2 I 8 I 13 I 8 I 8 1 4 I 7 I 53 1.9 | 3.8 I 3.8 | 15.1 | 24.5 I 15.1 I 15.1 | 7.5 I '3.2 I 4.6 1 1 9 I 43 I 351 I 332 I 1 8 0 I 126 I 28 I 2 2 I 1092 1 I 8 | 3.9 I 32. 1 | 30.4 I IB.5 | 11.5 | 2.6 I 2 0 I 95.4 2 1 1 45 359 345 188 134 32 29 1145 .2 1.0 3.9 31.4 30. 1 16.4 11.7 2.8 2.5 100.0 SIGNIFICANCE MIN E . F. CELLS WITH E.F.< 5 0 0000 0. 093 6 OF 18 ( 33. 3%) VALUE SIGNIFICANCE CRAMER'S V 0.20744 Appendix A. Data Analysis Tables 84 Table A.52: Total LOS by Gestational Age C R O S S T A B U L A T I O N O F GESTAGE2 GESTATIONAL AGE (NOT INCLUDING SHORTSTAY BY TOTDAYS OAYS SPENT IN THE HOSPITAL (ROUNDED UP) TOTDAYS COUNT ROW PCT < 2.4 HOURS GESTAGE2 Ol 2| 4| 5| B DAYS ROW OR MORE TOTAL 7| 8| 1 I 1 I 2 1 6 36 38 30 24 1 1 3 I 18 I 168 <= 37 WEEKS I 6 | 1.2 | 3.6 21.4 22.6 17.9 14.3 I 7.7 10.7 | 14.7 2 I 1 I 9 I 39 323 307 158 110 I 19 11 I 977 > 37 WEEKS I •1 1 9 I 4.0 33.1 31.4 16.2 11.3 I 1.9 1 . 1 | 85.3 COLUMN 2 11 45 359 345 188 134 32 29 1145 TOTAL . 2 1.0 3.9 31.4 30. 1 16 . 4 11.7 2.8 2.5 100.0 CHI-SQUARE D.F. 82.66027 8 STATISTIC SIGNIFICANCE VALUE MIN E.F. CELLS WITH E.F.< 5 0.293 5 OF 18 ( 27.8X) SIGNIFICANCE CRAMER'S V 0.26869 Table A.53: Total LOS by APGAR score - C R O S S T A B U L A T I O N O F 1 MINUTE APGAR SCORE (NOT INCLUDING SHOR BY TOTDAYS DAYS SPENT IN THE HOSPITAL (ROUNDED UP) TOTDAYS COUNT APGAR 12 0-3 ROW PCT < 2.4 HOURS o| 1| 2| 31 4| 5| 6| 8 DAYS OR MORE 7| 8| ROW TOTAL 1 1 1 3.2 1 12 I 38.7 | 9 29.0 I 22-6 I I I 3 . 1 | 31 2.7 4-6 M e l 4 1 1 6 1 5.0 1 25.6 | 37 30.6 I 16 Z5 | ' 3 I 10. 7 1 3 2.5 1 4.1 | 121 10.6 7« 3 1 . 1 1 .5 1 38 1 3.8 | 316 I 31.8 | 299 30. 1 I ^ I 121 1 12.2 | 29 2.9 1 £ 1 993 86 . 7 COLUMN TOTAL 2 .2 11 1 .0 45 3.9 359 31 .4 345 30. 1 188 16.4 134 11.7 32 2.8 29 2.5 1145 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 29.17268 16 0 022B 0.054 12 OF 27 ( 44. 4X) STATISTIC VALUE SIGNIFICANCE CRAMER'S V 0.11287 Appendix A. Data Analysis Tables 85 Table A.54: Total LOS by New Baby Classification NEWCAT NEW BABY CATEGORIES TOTDAYS C R O S S T A B U L A T I O N O F BY TOTDAYS DAYS SPENT IN THE HOSPITAL (ROUNDED UP) COUNT ROW PCT < 2.4 HOURS NEWCAT D| zl 3| 4| 5| 1 1 1 I 2 I 2 8 13 8 8 1 4 7 1 5 3 < 2500 GRAMS 1 1.9 | 3.8 | 3.8 15. 1 24.5 15. 1 15. 1 I 7.5 13.2 | 4.4 2 1 1 I 5 36 30 22 18 I 9 12 1 133 >2500 G 4 <37 W 1 8 | 3.8 27. 1 22.6 16.5 13.5 I 6.8 9.0 1 11.0 3 1 1 I 8 I 38 315 302 158 108 I 19 10 1 959 >2500 G 4 >37 W 1 1 I 8 | 4.0 32.8 31.5 16.5 11.3 | 2.0 1 .0 | 79.3 4 1 41 I 1 4 1 SHORT STAY 1 100.0 | I 3.4 5 1 1 I 2 2 2 4 2 10 I 2 3 PEDIATRIC 1 4.3 I 8.7 8.7 8.7 17.4 8.7 43.5 I ' 9 COLUMN 43 12 47 361 347 192 134 34 39 1209 TOTAL 3.6 1 .0 3.9 29.9 28.7 15.9 11.1 2.8 3.2 100.0 8 DAYS ROW OR MORE TOTAL 7| 8| CHI-SQUARE D.F. 1357.82319 32 STATISTIC SIGNIFICANCE VALUE CELLS WITH E.F.< 5 0.228 22 OF 45 ( 48.9*) SIGNIFICANCE CRAMER'S V 0.52988 Appendix A. Data Analysis Tables Table A.55: New Baby Category by Mother's Antepartum Category C R O S S T A B U L A T I O N O F AP2 ANTE PARTUM COMPLICATION OF MOTHER BY NEWCAT NEW BABY CATEGORIES NEWCAT < 2500 >2500 G >2500 G SHORT ROW GRAMS & <37 W & >37 W STAY TOTAL 1| 2| 3| 4| AP2 • • • * • 0 I 7 17 449 2 1 475 NO ANTEPARTUM I 1.5 3.6 94.5 .4 | 40.4 1 I 7 20 1 15 I 4 3 PRETERM LABOUR I 16.3 46.5 2.3 34.9 I 3 7 2 I 5 31 121 '4 I 161 RUPTURE I 3.1 19.3 75.2 2.5 | 13.7 3 | 2 11 53 1 I 6 7 HYPERTENSION I 3.0 16.4 79. 1 1.5 I 5- 7 4 I 2 14 66 I 82 DIABETES I 2.4 17.1 80.5 I 7 0 5 I 17 5 50 4 I 7 6 IUGR I 22.4 6.6 65.8 5.3 I 6.5 6 I 7 11 11 7 I 3 6 AP HEMORRAGE I 19.4 30.6 30.6 19.4 I 3.1 7 I 5 19 208 5 I 237 OTHER I 2.1 8.0 87.8 2. 1 | 20. 1 COLUMN 52 128 959 38 1177 TOTAL 4.4 10.9 81 .5 3.2 100.0 CHI-SQUARE D.F. SIGNIFICANCE MIN E.F. CELLS WITH E.F.< 5 444.46432 21 0.0000 1.162 12 OF 32 ( 37.5X) STATISTIC VALUE SIGNIFICANCE COUNT ROW PCT CRAMER'S V 0.35479 Appendix A. Data Analysis Tables Table A.56: New Baby Category by Delivery Type DEL DELIVERY TYPE OF MOTHER NEWCAT C R O S S T A B U L A T I O N O F BY NEWCAT NEW BABY CATEGORIES COUNT ROW PCT DEL 1 SPONTANEOUS 2 INSTRUMENTAL 3 ELEC C-SECTION 4 EM C-SECTION COLUMN TOTAL CHI-SQUARE D.F. < 2500 >2500 G >2500 G SHORT ROW GRAMS S <37 W S >37 W STAY TOTAL 1 2 3 4| 29 1 68 572 21 I 690 4.2 | 9.9 82.9 3 - 0 | 58.6 7 1 1 9 152 4 I 182 3.8 | 10.4 83.5 2.2 | 15.5 6 I 1 8 91 3 I 118 5.1 | 15.3 77. 1 2.5 | 10.0 10 I 2 3 144 10 I 187 5.3 | 12.3 77.0 5.3 | 15.9 52 128 959 38 1177 4.4 10.9 81 .5 3.2 100.0 8.25611 9 STATISTIC SIGNIFICANCE 0.5086 VALUE 3.810 1 OF SIGNIFICANCE CELLS WITH E.F.< 5 16 ( 6.3%) CRAMER'S V 0.04835 Appendix B Model Output Description The following is a detailed description of all the output generated by the Grace Hospital Simulation Model. It is organized in the same order as the model's output (for a sample see the next appendix). 1. STORAGE STATISTICS - gives statistics on the various locations in the hospital. HOLLY Holly antepartum module LOW low risk delivery suite (not including assessment room) ASESS assessment rooms (in low risk) HIGH high risk delivery suite OR operating rooms PAR post anaesthetic recovery rooms ARB Arbutus postpartum module BAL Balsam postpartum module CED Cedar postpartum module DOG Dogwood postpartum/antepartum module EVE Evergreen postpartum module FIR Fir postpartum module TREAT treatment rooms (overflow for PP modules) 88 Appendix B. Model Output Description 89 LRN low risk nursery HRN high risk nursery OBN observation nursery ARBN Arbutus nursery BALN Balsam nursery CEDN Cedar nursery DOGN Dogwood nursery EVEN Evergreen nursery FIRN Fir nursery 2. QUEUE STATISTICS - these are the only queues of interest (the rest were used of verify the model): ORQ total entries minus zero entries shows the number of patients who went to the OR only to find them all occupied APDGN number of mothers in AP who stayed in either DOG or EVE because HOLLY was full. APEVE number of mothers in AP who stayed in EVE because both DOG and HOLLY where full of AP patients when they arrived. DOSNU number of day of surgery patients in PP module. PPNUM number of adults in PP modules not including DOS patients. PPMOD number of adults in PP modules total. 3. USER CHAIN STATISTICS should be ignored, they are used to keep track of the departure order of patients. Appendix B. Model Output Description 90 4. TABLES APZ number of entries and LOS distribution in AP modules (HOLLY, DOG, and EVE) for all AP patients. STILZ number of entries and LOS distribution in AP modules for patients who had a stillbirth and stayed in AP for their postpartum stay. LOWZ number of entries and LOS distribution in LOW and APLOW for all patients. ASESZ number of entries and LOS distribution in ASESS, low risk temporary overflow from LOW or APLOW. LPAR number of entries and LOS distribution in PAR as overflow from LOW and ASESS. LOWTB number of entries and LOS lost when a patient was preempted from LOW risk by another patient who arrives when all of LOW, ASESS, PAR are full. HIGHZ number of entries and LOS distribution in HIGH or APHIG for all pa-- tients. HIGTB number of entries and LOS lost when a patient was preempted from HIGH risk by another patient who arrives when both HIGH and LOW are full. ORZ number of entries and LOS distribution in the OR. ORHR time of day (in minutes) of entry into the OR. ORDAY day of week (Sunday equals 1) of entry into the OR. PARZ number of entries and LOS distribution in the PAR. DOSZ number of entries and LOS distribution in PP for of patients in a PP module as day of surgery patients. endix B. Model Output Description 91 PPZ number of entries and LOS distribution in a PP module for all patients except DOS patients. PPZ2 number of entries and LOS distribution in the PP subsection for delivered mothers. TREAZ number of entries and LOS distribution in TREAT, the temporary over-flow area of the PP modules. PPTB number of entries and LOS lost when a patient was preempted from a PP module due to another patient who arrives to find the PP modules all occupied. FLAG number of entries and LOS lost when a patient was preempted from a PP module due to the red flag condition. DISZ discharge time of day (in minutes) of all adults. LRNZ number of entries and LOS distribution in LRN, the low risk nursery. HRNZ number of entries and LOS distribution in HRN, the high risk nursery. OBNZ number of entries and LOS distribution in OBN, the observation nursery. OBNTB number of entries and LOS lost when a baby is preempted (kicked out early) because another baby arrived and found the OBN full. PPNZ number of entries and LOS distribution in PPN, the postpartum nursery. ATIM2 arrival time of day (in minutes) for all mothers arriving to deliver except the DOS patients. ATIME arrival time of day (in minutes) for all DOS patients. ARATE interarrival time of all mothers arriving to deliver except the DOS pa-tients. Appendix B. Model Output Description 92 DOSDL the delivery time of day of DOS patients. DL the delivery time of day for all mothers except DOS patients. DELAP number and LOS before delivery of all mothers. DELPP number and LOS after delivery of all mothers. SPOPP number and LOS after delivery for all mothers with a spontaneous deliv-ery. INSPP number and LOS after delivery for all mothers who had a instrumental delivery (forceps,assisted,vacuum). ELCPP number and LOS after delivery for all mothers who had a elective C-section. EMCPP number and LOS after delivery for all mothers who had a emergency C-section. UNTOT number and LOS distribution in hospital for AP only patients. PPTOT number and LOS distribution in hospital for PP only patients. NBTOT number and LOS distribution in hospital for all newborn babies except the short stay babies. SHTOT number and LOS distribution in hospital for short stay babies (short stay babies are imeediately discharged to Sick Children's Hospital). PDTOT number and LOS distribution in hospital of pediatric babies. ORWAI number and time waited by elective surgical procedures because fewer than 2 ORs were free. The patients wait in the place they are just before wanting to go to the OR (i.e. they are not transfered until the OR is free). 5. FULLWORD, HALFWORD, BYTE SAVEVALUES can be ignored. endix B. Model Output Description 93 MATRIX SAVEVALUES DISCH record of arrivals and discharges. row # 1 arrival numbers of mothers to deliver, undelivered adults, and ba-bies in that order. row # 2 discharge numbers for the same. CLASS total number of patients in the various categories used to classify patients (columns are identified in brackets following category name). row # 1 geographical residence (Vancouver, GVRHD, B.C.) row # 2 AP complication (no complication, preterm labour, premature rup-ture of membranes, hypertension, diabetes, IUGR, AP hemmorhage, other AP complication) row # 3 delivery type (spontaneous, instrumental, elective C-section (ran-dom arrival), emergency C-section, PP only, undelivered (AP only), DOS elective C-section (in column # 9)) row # 4 PP category (spontaneous no complication, spontaneous with com-plication, instrumental no complication, instrumental with complication, elective C-section no complication, elective C-section with complication, emergency C-section no complication, emergency C-section with compli-cation, PP only, undelivered (AP only)) row # 6 health of baby to deliver (-^ 2500 grams, >- 2500 grams and -< 37 weeks gestation, >- 2500 grams and >- 37 weeks gestation, short stay, pediatric, no baby) row # 7 health of twin (see categories in previous row description) row # 8 health of triplet (see categories of health in row number 6) Appendix B. Model Output Description 94 TRANS transfer table for all adult patients in the model. Row number gives the location from which the transfer initiated, and the column number gives the location to which the transfer was bound. The following translates the numbers to locations in the model: 1 = ADMIT - admitted from home 2 = DOS - day of surgery patient in PP modules 3 = AP - antepartum modules 4 = APLOW - low risk returning to AP 5 = APHIG - high risk returning to AP 6 = APOR - operating room returning to AP 7 = APPAR - post anaesthetic room returning to AP 8 = LOW - low risk to deliver 9 = HIGH - high risk to deliver 10 = OR - operating room to deliver 11 = PAR - post anaesthetic room after delivery 12 = PP - postpartum modules 13 = PPOR - operating room from PP 14 = PPPAR - post anaesthetic room from PPOR 15 = DISCHARGE - return to home BTRANS transfer table for all the baby patients in model. Setup similar to TRANS with the following translations: 1 = ADMIT - from home 2 = LRN - low risk nursery 3 = HRN - high risk nursery Appendix B. Model Output Description 95 4 = OBN - observation nursery 5 = PPN - postpartum nursery 6 = DISCHARGE - return to home APNUM breakdown of the patients in AP modules by AP category (columns, see CLASS above for order of AP categories) and delivery type. The first row is of patients who go on to delivery this session in hospital. The second row is of patients only at Grace for AP complication. BDEL breakdown of the locations in which delivery took place. column # 1 LOW risk column # 2 ASESS (assessment room) or PAR overflow from LOW column # 3 HIGH risk column # 4 OR ORCAT breakdown of delivery type (rows) in the OR, further broken down by reason for OR visit. column # 1 APOR - OR used for antepartum complication column # 2 OR - OR used for delivery column # 3 PPOR - OR used for postpartum complication or sterilization CSTEN the sum of all 10:30 census for the duration of run for the following places: row # 1 number of patients in HOLLY row # 2 number of AP patients in DOG or EVE row # 3 not used row # 4 number' of patients in LOW risk row # 5 number of patients in ASESS endix B. Model Output Description 96 row # 6 number of patients in HIGH risk row # 7 number of PP patients in PP row # 8 number of patients in PP modules (includes DOS) row # 9 number of patients in TREAT row # 10 number of babies in OBN CSMID the sum of all 12 midnight census (see CSTEN for details). CNUM the number of 10:30 and midnight census included in the total CSTEN and CSMID. ARRIV shows daily arrival pattern of mothers to delivery. Rows number the days of most recent month. Column one is all mothers to deliver except DOS patients, and column two is DOS mothers. APPBL record of logic used to overcome crowding in AP subsection. row col 1 1 number of AP patient to DOG (HOLLY full) 1 2 number of AP patient to EVE (DOG, HOLLY full) 1 3 number of no space anywhere for AP patient 2 1 number of APLOW patient sent to ASESS 2 2 number of APLOW patients sent to PAR 2 3 number of APLOW patients preempted (overflow) 3 1 number of APHIG patients sent to LOW 3 2 number of APHIG patients sent to ASESS 3 3 number of APHIG patients preempted (overflow) 4 1 number of times APOR patient finds all ORs full 5 1 number of APPAR patients sent to APHIG endix B. Model Output Description 5 2 number of APPAR patients preempted (overflow) LDPBL record of logic used to overcome crowding in the delivery suite, row col 1 1 number of LOW patients who enter ASESS 1 2 number of LOW patients who enter PAR (LOW) 1 3 number of LOW patients who cause another patient to move prematurely moved from LOW 2 1 number of HIGH patients sent to LOW 2 2 number of HIGH pateints sent to ASESS 2 3 number of HIGH patients who cause another patient to be prematurely moved from HIGH 3 1 number of OR patients who find the OR totally occupied 4 1 number of PAR patients sent to HIGH 4 2 number of PAR patients who cause another patient to be prematurely moved from the PAR 5 1 number of DOS patients sent to TREAT 5 2 number of DOS patients causing another patient to be preempted from PP modules PPPBL record of logic used to overcome crowding in PP. row col 1 1 number of PP patients sent to TREAT 1 2 number of PP patients who cause another patient to be prematurely moved from PP Appendix B. Model Output Description 98 2 1 number of PPOR patients who find the OR totally occupied 3 1 number of PPPAR patients sent to HIGH 3 2 number of PPAR patients who cause another patient to be prematurely moved from the PAR BABPB record of the logic used to overcome crowding of babies. row col 1 1 number of babies who find no room in LRN 2 1 ' number of babies who find no room in HRN 3 1 number of babies who cause another baby to be prematurely moved from the OBN 4 1 number of babies who find no room in the PP RFLAG record of number of adult patients sent home early be the red flag system (see also the table FLAG). CENSU the 10:30 census for the last month of the model's run. See matrix CSTEN for description of column translation. Appendix C Output From Standard Run • - A V G - U T I L - D U R I N G - • STORAGE TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT CAPACITY AVERAGE CURRENT MAXIMUM TIME TIME TIME TIME/UNIT STATUS AVAIL CONTENTS CONTENTS CONTENTS HOLLY .881 3675 5567 975 AVAIL 100.0 26 22 .919 26 26 LOW .629 12479 495 485 AVAIL 100.0 1 1 6 .925 10 1 1 ASSES .024 1243 7 1 .270 AVAIL 100.0 4 0 .099 0 4 HIGH .458 4906 667 .544 AVAIL 100.0 6 3 .668 5 8 OR . 145 4026 96 923 AVAIL 100.0 3 0 437 0 3 PAR . 1 18 3897 108 750 AVAIL 100.0 4 0 .474 0 4 ARB .792 3074 3680 .534 AVAIL 100.0 16 12 .672 1 1 16 BAL . 788 2277 4636 617 AVAIL 100.0 15 1 1 .825 14 15 CED . 754 231 1 4665 .807 AVAIL 100.0 16 12 .077 10 16 DOG .886 2520 5022 .578 AVAIL 100.0 16 14 . 176 13 16 EVE .829 2326 4775 36 3 AVAIL 100.0 15 12 . 44 1 1 1 15 FIR . 780 2357 4732 833 AVAIL 100.0 16 12 . 494 1 1 16 TREAT .008 267 161 .988 AVAIL 100.0 6 0 .048 0 6 LRN .077 6690 113 .430 AVAIL 100.0 1 1 0 . 849 1 7 HRN .083 5070 117 .285 AVAIL 100.0 8 0 .666 0 6 99 Appendix C. Output From Standard Run 100 OBN .665 1932 3077 246 AVAIL 100.0 10 6. 659 4 10 ARBN .694 2003 4954 227 AVAIL 100.0 16 1 1 . 114 9 16 BAIN . 726 1997 4871 669 AVAIL 100.0 15 10. B96 13 15 CEDN .690 2003 4921 849 AVAIL 100.0 16 1 1 . 042 1 1 16 DOGN .684 1998 4890 452 AVAIL 100.0 16 10. 944 10 16 EVEN .732 1989 4931 419 AVAIL 100.0 15 10. 986 a 15 FIRN .694 2006 4946 463 AVAIL 100.0 16 1 1 . 1 14 13 16 QUEUE MAXIMUM AVERAGE TOTAL ZERO PERCENT AVERAGE JAVERAGE OTABLE CURRENT CONTENTS CONTENTS ENTRIES ENTRIES ZEROS TIME/UNIT TIME/UNIT NUMBER CONTENTS APO 1 0 000 4452 4452 100.0 0 000 0 .000 0 APLO 1 0 000 2606 2606 100.0 0 000 0 .000 0 APHQ 1 0 000 1572 1572 100.0 0 000 0 .000 0 APORO 1 0 000 93 93 100.0 0 000 0 .000 0 APPAO 1 0 000 93 93 100.0 0 000 0 .000 0 LOHO 1 0 000 1 1 149 1 1149 100.0 0 000 0 .000 0 HIGO 1 0 000 3425 3425 100.0 0 000 0 .000 0 ORO 0 001 3589 3576 9 9 . 6 0 349 96 .615 0 PARO 1 0 000 3409 3409 100.0 0 000 0 .000 0 DOSO 1 0 000 956 956 100.0 0 000 0 .000 0 PPO 0 000 13294 13294 100.0 0 000 0 .000 0 PPORO 1 0 000 356 356 100.0 0 000 0 .000 0 PPPAO t 0 000 356 356 100.0 0 000 0 .000 0 LRNO t 0 000 6690 6690 100.0 0 000 0 .000 0 HRNO t 0 000 50 70 5070 100.0 0 000 0 000 0 OBNO 1 0 000 1926 1926 100.0 0 000 0 .000 0 PPNQ 4 0 024 11944 1 1939 9 9 . 9 1 821 4350 400 0 APDGN 18 5 260 8 10 0 0 . 0 5797 880 5797 880 4 APEVN 2 0 008 2 0 0 . 0 3993 500 3993 500 0 DOSNU 7 0 639 932 0 0 . 0 613 O i l 613 O i l 0 PPNUM 97 69 8 36 12765 0 0 . 0 4884 449 4884 449 66 PPMOO 102 75 7 36 14507 0 0 . 0 4661 033 4661 033 70 ORW4I 3 0 008 2059 1881 9 1 . 3 3 678 42 550 500 0 USER CHAIN ENTRIES AVERAGE TIME/XACT OOGUC 1712 4654 .547 EVEUC 2324 4 7 7 5 . 8 8 9 LOWUC 12479 4 9 5 . 3 7 0 ASSUC 1243 7 1 . 2 7 0 LPUC 47 172.851 PARUC 3897 114.965 HIGUC 4906 6 6 7 . 3 7 9 PPUC 21923 2867 .917 TREUC 267 161.988 OBNUC 1932 3077.246 AVERAGE CURRENT MAXIMUM CONTENTS CONTENTS CONTENTS 8 . 9 2 5 9 16 12.431 1 1 15 6 . 9 2 3 10 1 1 0 . 0 9 9 0 4 0 . 0 0 9 0 4 0 .501 0 6 3.667 5 8 70 422 66 93 0 .048 0 6 6 .659 4 10 Appendix C. Output From Standard Run T A B L E APZ E N T R I E S IN T A B L E MEAN ARGUMENT STANDARD D E V I A T I O N SUM OF ARGUMENTS 4 3 1 1 5 7 1 3 . 5 4 0 0 8 9 8 1 . 5 7 0 0 2 . 4 6 3 1 E * 0 7 NON-WEIGHTED UPPER O B S E R V E D PERCENT 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 D E V I A T I O N L I M I T F R E Q U E N C Y OF TOTAL P E R C E N T A G E REMAINDER OF MEAN FROM MEAN 1440 1594 3 6 . 97 3 6 . 97 6 3 . 03 2 5 2 0 - . 4 7 5 8 2 8 8 0 9 2 3 21 4 1 5 8 . 38 41 . 62 . 5 0 4 0 - . 3 1 5 4 4 3 2 0 376 8 . 72 67 . 10 3 2 . . 9 0 . 7 5 6 0 - . 1 5 5 1 5 7 6 0 329 7 . 6 3 74 . 73 25 . 27 1 . 0 0 8 1 5 . 1 7 3 3 E - 0 3 7 2 0 0 185 4 . 29 7 9 . 0 3 2 0 . 97 1 . 2601 . 1655 8 6 4 0 118 2 73 81 . 76 18 24 1 . 5 1 2 2 . 3258 1 0 0 8 0 109 Z. 52 8 4 . 29 15 .71 1 . 7642 . 4 8 6 1 1 1 5 2 0 90 2. 0 8 86 38 13. 62 2 . 0 1 6 2 . 6 4 6 4 1 2 9 6 0 65 1 . 5 0 87 . 89 12 . 11 2 . 2 6 8 3 . 8 0 6 8 14400 52 1 . 20 8 9 . 0 9 10. .91 2 . 5 2 0 3 . 9 6 7 1 1 5 8 4 0 52 1 . 2 0 9 0 . 30 9 70 2 . 7723 1 . 1 2 7 4 1 7 2 8 0 37 0 . 8 5 91 . 16 8 . 8 4 3 . 0 2 4 4 1 . 2 8 7 8 1 8 7 2 0 32 0 . . 74 91 . 90 8 . 10 3 2764 1 . 4 4 8 1 2 0 1 6 0 30 0 . 6 9 92 . 6 0 7 . 4 0 3 . 5 2 8 4 1 . 6 0 8 4 2 1 6 0 0 42 0 . .97 9 3 57 6. . 43 3 . 7805 1 . 7 6 8 7 2 3 0 4 0 35 0 .81 94 . 38 5. . 6 2 4 . 0 3 2 5 1 . 9 2 9 1 2 4 4 8 0 2B 0 . 6 4 9 5 . 0 3 4 .97 4 . 2 8 4 5 2 . 0 8 9 4 2 5 9 2 0 19 0 . 44 95 .47 4 . 5 3 4 . 5 3 6 6 2 . 2 4 9 7 2 7 3 6 0 22 0 .51 95 . 9 8 4 . 0 2 4 . 7886 2 . 4 1 0 1 2 8 8 0 0 17 0 39 96 . 38 3 . 6 2 5 . 0 4 0 6 2 . 5 7 0 4 3 0 2 4 0 13 0 . 30 96 . 6 8 3 . 32 5 . 2 9 2 7 2 . 7 3 0 7 3 1 6 8 0 8 0 . 18 96 . 8 6 3 . 14 5 . 5447 2 . 8 9 1 0 3 3 1 2 0 9 0 . 20 97 . 0 7 2 . 9 3 5 . 7967 3 . 0 5 1 4 3 4 5 6 0 6 0 . 1 3 97 .21 2 . 79 6 . 0 4 8 7 3 . 2 1 1 7 3 6 0 0 0 1 1 0 . 25 97 . 47 2 . 5 3 6 . 3008 3 . 3 7 2 0 3 7 4 4 0 11 0 . 25 97 . 72 2 . 2 8 6 . 5 5 2 8 3 . 5 3 2 4 3 8 8 8 0 7 0 . 16 97 . 8 8 2 . 12 6 . 8 0 4 8 3 . 6 9 2 7 4 0 3 2 0 12 0 . 2 7 98 . 16 1 . 8 4 7 . 0 5 6 9 3 . 8 5 3 0 4 1 7 6 0 8 0 . 18 98 . 35 1 . 6 5 7 . 3089 4 . 0 1 3 3 OVERFLOW 71 1 . 6 4 100 . 0 0 0 . 0 0 A V E R A G E V A L U E OF OVERFLOW I S 4 8 9 3 2 . 4 0 0 0 T A B L E S T I L Z E N T R I E S IN T A B L E MEAN ARGUMENT STANDARD D E V I A T I O N SUM OF ARGUMENTS 144 4 1 9 6 . 8 3 0 0 1 1 7 9 . 8 6 0 0 6 . 0 4 3 4 E * 0 5 NON-WEIGHTED UPPER O B S E R V E D P E R C E N T 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 D E V I A T I O N L I M I T F R E Q U E N C Y OF TOTAL P E R C E N T A G E REMAINDER OF MEAN FROM MEAN 1440 3 2 . 0 8 2 . 0 8 97 . 9 2 . 343 1 - 2 . 3 3 6 5 2 8 8 0 15 1 0 . 4 1 12 . 50 87 . 50 . 6 8 6 2 - 1 . 1 1 6 0 4 3 2 0 6 0 41 . 6 6 54 . 16 4 5 . 8 4 1 . 0 2 9 3 . 1043 5 7 6 0 55 38 . 19 92 . 36 7 . 6 4 1 . 3 7 2 4 1 . 3 2 4 8 7 2 0 0 9 6 . 2 5 9 8 . 6 1 1 . 39 1 . 7 1 5 5 2 . 5 4 5 3 8 6 4 0 2 1 . 38 1 0 0 . 0 0 0 . 0 0 2 . 0 5 8 6 3 . 7 6 5 8 ALL R E M A I N I N G FREQUENCY C L A S S E S ARE ZERO Appendix C. Output From Standard Run T A B L E LOWZ E N T R I E S IN T A B L E MEAN ARGUMENT STANDARD D E V I A T I O N SUM OF ARGUMENTS 12469 4 9 9 . 1 7 8 0 9 2 2 . 8 8 1 0 6 . 2 2 4 2 E + 0 6 NON-WEIGHTED UPPER O B S E R V E D PERCENT 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 D E V I A T I O N L I M I T F R E Q U E N C Y OF TOTAL P E R C E N T A G E REMAINDER OF MEAN FROM MEAN 120 1982 15. 89 15. .89 84 . 11 2 4 0 3 - . 4 1 0 8 240 2 6 9 4 21 . 60 3 7 . . 50 6 2 . 50 4807 - . 2 8 0 8 360 1831 14 . 6 8 52 . 18 47 . 82 . 7 2 1 1 - . 1 5 0 8 4 8 0 1300 10 . 4 2 62 .61 37 . 39 9 6 1 5 - 2 . 0 7 8 0 E - 0 2 6 0 0 1068 8 56 71 17 28 8 3 1. 2 0 1 9 . 1092 720 788 6 . 31 77 . .49 22 51 1 . 4 4 2 3 . 2 3 9 2 8 4 0 6 8 8 5. 51 8 3 .01 16. 99 1 . 6827 . 3693 9 6 0 5 8 9 4 . 72 87 . 7 3 12. 27 1 9231 . 4 9 9 3 1080 4 1 9 3 . 36 91 . 0 9 8 91 2 . 1635' . 6 2 9 3 1200 333 2 .67 93 . 76 6 .24 2 . 4039 . 7 5 9 3 1320 240 1 . 92 95 .69 4 , 31 2. 6 4 4 3 . 8894 1440 147 1 . 17 96 .87 3 13 2 8847 1 . 0 1 9 4 1560 138 1 . 10 97 .97 2 . 0 3 3 . 1251 1 . 1 4 9 4 1680 98 0 . 78 98 . 7 6 1 .24 3 . 3655 1 . 2 7 9 5 1800 26 0 . 2 0 98 .97 1 0 3 3 . 6 0 5 9 1 . 4 0 9 5 1920 23 0 . 18 9 9 . . 15 0 85 3. 8 4 6 3 1 . 5 3 9 5 2 0 4 0 26 0 . 20 99 . 36 0 . ,64 4 . 0 8 6 7 1 . 6 6 9 5 2 1 6 0 24 0 . 19 99 . 5 5 0 . 4 5 4 . 3 2 7 1 1 . 7 9 9 6 2 2 8 0 20 0 . . 16 99 .71 0 ,29 4 . 5 6 7 5 1 . 9 2 9 6 2 4 0 0 4 0 . 0 3 99 . 75 0 . 2 5 4 . 8 0 7 9 2 . 0 5 9 6 2 5 2 0 0 0 0 0 99 . 75 0 . 25 5 . 0 4 8 3 2 . 1 8 9 6 2 6 4 0 0 0 . . 0 0 99 . 75 0 . 2 5 5 . 2 8 8 7 2 . 3 1 9 7 2 7 6 0 1 0 . 0 0 99 . 75 0 . 25 5 . 5 2 9 0 2 . 4 4 9 7 2 8 8 0 0 0 . 0 0 99 . 7 5 0 . 2 5 5 . 7694 2 . 5 7 9 7 3 0 0 0 0 0 . 0 0 99 . 75 0 . 25 6 . 0 0 9 8 2 . 7 0 9 8 3 1 2 0 0 0 . 0 0 99 . 75 0 . 25 6 . 2 5 0 2 2 . 8 3 9 8 3 2 4 0 0 0 . 0 0 99 . 75 0 . 25 6 . 4 9 0 6 2 . 9 6 9 8 3 3 6 0 0 0 . 0 0 99 . 7 5 0 . 2 5 6 . 7 3 1 0 3 . 0 9 9 8 3 4 8 0 0 0 . 0 0 99 . 75 0 . 25 6 . 9 7 1 4 3 . 2 2 9 9 OVERFLOW 30 0 . 24 100 . 0 0 0 . 0 0 A V E R A G E V A L U E OF OVERFLOW I S 1 4 6 0 0 . 1 0 0 0 T A B L E A S S E Z E N T R I E S IN T A B L E MEAN ARGUMENT STANDARD D E V I A T I O N SUM OF ARGUMENTS 1243 7 1 . 4 5 9 4 6 0 . 8 4 2 4 8 8 8 2 4 . 0 0 0 0 NON-WEIGHTED UPPER O B S E R V E D P E R C E N T 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 D E V I A T I O N L I M I T F R E Q U E N C Y OF TOTAL P E R C E N T A G E REMAINDER OF MEAN FROM MEAN 30 374 3 0 . 0 8 30 . 0 8 6 9 . 92 . 4 1 9 8 - . 6 8 1 4 6 0 291 2 3 . 4 1 53 .49 46 51 . 8 3 9 6 - . 1 8 8 3 9 0 207 16. . 6 5 70 . 15 2 9 . . 8 5 1 . 2 5 9 4 . 3047 120 147 11 . 8 2 81 .97 18 0 3 1 . 6 7 9 2 . 7978 150 89 7 . 16 89 . 13 10 .87 2 . 0 9 9 0 1 . 2 9 0 8 180 7 1 5. 7 1 94 . 8 5 5 15 2 . 5 1 8 9 1 . 7 8 3 9 2 10 34 2 . 7 3 97 . 58 2 . 4 2 2 . 9 3 8 7 2 . 2 7 7 0 240 9 0 . 72 98 . 3 t 1 .69 3 . 3 5 8 5 2 . 7 701 270 7 0 . 56 98 . 8 7 1 . 1 3 3 . 7 7 8 3 3 . 2 6 3 2 300 5 0 . 40 99 . 2 7 0 . 73 4 . 1 9 8 1 3 . 7 5 6 2 330 2 0 . 16 99 . 4 3 0 . 57 4 . 6 1 8 0 4 . 2 4 9 3 endixC. Output From Standard Run 360 4 0.32 99.75 0.25 5.0378 4.7424 390 0 0.00 99.75 0.25 5.4576 5.2355 420 3 0.24 100.00 0.00 5.8774 5.7285 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE LPAR ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 47 175.6380 92.8843 8255.0000 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 30 2 4 .25 4 .25 95. 75 . 1708 - 1.5679 60 3 6. . 38 10 .63 89. 37 .3416 - 1.2449 90 1 2 . 12 12. . 76 87 . 24 .5124 -.9219 120 7 14 .89 27 .65 72. .35 .6832 -.5990 150 8 17 .02 44 .68 55 32 .8540 -.2760 180 6 12. . 76 57 .44 42. 56 1.0248 4.6958E-02 210 6 12 . 76 70. .21 29. 79 1.1956 . 3699 240 3 6 . 38 76. .59 23. 41 1.3664 .6929 270 3 6 . 38 82. .97 17 . 03 1 .5372 1.0159 300 5 10 .63 93 .61 6 . 39 1.7080 1.3388 330 1 2 . 12 95 . 74 4. 26 1.8788 1.6618 360 0 0 .00 95 . 74 4 26 2.0496 1.9848 390 1 2. . 12 97 .87 2. 13 2.2204 2.3078 420 0 0 .00 97 . 87 2. 13 2.3912 2.6308 450 0 0 .00 97, 87 2. 13 2.5620 2.9538 480 0 0. 00 97. 87 2. 13 2.7328 3.2767 510 1 2. . 12 100. 00 0. 00 2.9036 3.5997 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE LOWTB ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 4 31.0000 38.7556 124 0000 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 30 3 75.00 75.00 25.00 .9677 -2.5802E-02 60 0 0.00 75.00 25.00 1.9354 .7482 90 1 25.00 100.00 0.00 2.9032 1.5223 ALL REMAINING FREQUENCY CLASSES ARE ZERO Appendix C. Output From Standard Run TABLE HIGHZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 4901 668.3870 572.4900 3.2757E*06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 120 578 1 1 . 79 1 1 . 79 88 .21 . 1795 -.9578 240 564 11 .50 23 . 30 76 . 70 . 3590 -.7482 360 428 8 . 73 32 .03 67 .97 .5386 -.5386 480 478 9 . 75 41 .78 58 .22 .7181 -.3290 600 592 12 .07 53 .86 46 . 14 .8976 -.1194 720 442 9 .01 62 .88 37 . 12 1 .0772 9.0155E-02 840 465 9 .48 72 .37 27 .63 1 .2567 .2997 960 311 6 . 34 78 .71 21 . 29 1 .4362 . 5093 1080 203 4 . 14 82 .86 17 . 14 1 .6158 .7189 1200 198 4 .03 86 .90 13 . 10 1 . 7953 .9285 1320 128 2 .61 89 .51 10 .49 1 .9749 1 . 1382 1440 93 1 . 89 91 .40 8 .60 2 . 1544 1 .3478 1560 150 3 .06 94 .47 5 .53 2 . 3339 1 .5574 1680 57 1 . 16 95 .63 4 . 37 2 .5135 1.7670 1800 33 0 .67 96 . 30 3 . 70 2 .6930 1.9766 1920 29 0 . 59 96. 89 3 . 11 2 .8725 2.1862 2040 22 0 . 44 97 , 34 2 .66 3 .0521 2.3958 2160 22 0 44 97, 79 2. .21 3 .2316 2.6054 2280 14 0 .28 98, .08 1 .92 3 .4112 2.8150 2400 9 0 . 18 98, 26 1 . 74 3 .5907 3.0247 2520 17 0. . 34 98, 61 1 . . 39 3 .7702 3.2343 2640 7 0. . 14 98. 75 1 . .25 3. .9498 3.4439 2760 1 1 0. 22 98. 97 1 . 03 4 . 1293 3.6535 2880 5 0 10 99. 08 0 92 4 . 3088 3.8631 3000 9 0. 18 99. 26 0. . 74 4 . 4884 4.0727 3120 4 0. 08 99 . 34 0. 66 4 , .6679 4.2823 3240 0 0. 00 99. 34 0. 66 4 , 8474 4.4919 3360 2 0 . 04 99. 38 0. 62 5, 0270 4.7015 3480 2 0. 04 99. 42 0. 58 5, 2065 4.9112 OVERFLOW 28 0. 57 100. 00 0. 00 AVERAGE VALUE OF OVERFLOW IS 4159.1400 TABLE ORZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 4039 96.9396 40.7714 3.9153E+05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 15 0 0 .00 0 .00 100 .00 . 1547 -2.0097 30 30 0 . 74 0 . 74 99 . 26 . 3094 - 1.6418 45 193 4 . 77 5 . 52 94 . 48 . 4642 - 1.2739 60 336 8 .31 13. .84 86, . 16 .6189 -.9060 75 685 16 .95 30 . 79 69 .21 . 7736 -.5381 90 736 18 . 22 49. 02 50 .98 .9284 -.1702 105 673 16 .66 65. 68 34 . 32 1 .0831 . 1976 120 518 12 . 82 78. .50 21 .50 1.2378 .5656 135 358 8 86 87 . 37 12, 63 1.3926 .9335 150 204 5. 05 92 . 42 7 , 58 1 .5473 1.3014 165 151 3 .73 96. , 16 3 .84 1.7020 1.6693 Appendix C. Output From Standard Run 180 44 1 08 97 25 2 75 1 8568 2 0372 195 18 0 44 97 69 2 31 2 0115 2 4051 2 10 20 0 49 98 19 1 81 2 1663 2 7730 225 17 0 42 98 61 1 39 2 3210 3 1409 240 13 0 32 98 93 1 07 2 4757 3 5088 255 18 0 44 99 38 0 62 2 6305 3 8767 270 6 0 14 99 52 0 48 2 7852 4 2446 285 1 0 02 99 55 0 45 2 9399 4 6125 300 0 0 00 99 55 0 45 3 0947 4 9804 315 2 0 04 99 60 0 40 3 2494 5 3483 330 6 0 14 99 75 0 25 3 4041 5 7162 345 2 0 04 99 80 0 20 3 5589 6 0841 360 0 0 00 99 80 0 20 3 7136 6 4520 375 1 0 02 99 82 0 18 3 8683 6 8199 390 2 0 04 99 87 0 13 4 0231 7 1878 405 0 0 00 99 87 0 13 4 1778 7 5557 420 2 0 04 99 92 0 08 4 3326 7 9237 435 1 0 02 99 95 0 05 4 4873 8 2916 OVERFLOW 2 0 04 100 00 0 00 AVERAGE VALUE OF OVERFLOW IS 484 5000 TABLE ORHR ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 3589 703.8390 395.2990 2.5260E*06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 159 4 43 4 43 95 57 8.5246E-02 - 1.6287 120 126 3 51 7 94 92 06 1704 - 1.4769 180 142 3 95 1 1 89 88 1 1 2557 - 1.3251 240 127 3 53 15 43 84 57 3409 - 1.1733 300 145 4 04 19 47 80 53 4262 - 1.0216 360 141 3 92 23 40 76 60 5114 -.8698 420 159 4 43 27 83 72 17 5967 -.7180 480 158 4 40 32 23 67 77 6819 -.5662 540 170 4 73 36 97 63 03 7672 -.4144 600 169 4 70 4 1 68 58 32 8524 -.2626 660 173 4 82 46 50 53 50 9377 -.1109 7 20 180 5 01 51 51 48 49 1 0229 4.0882E-02 780 196 5 46 56 97 43 03 1 1082 . 1926 840 157 4 37 61 35 38 65 1 1934 . 3444 900 179 4 98 66 34 33 66 1 2787 . 4962 960 166 4 62 70 96 29 04 1 3639 .6480 1020 166 4 62 75 59 24 41 1 4491 .7998 1080 121 3 37 78 96 21 04 1 5344 .9515 1 140 137 3 81 82 78 17 22 1 6196 1 . 1033 1200 121 3 37 86 15 13 85 1 7049 1.2551 1260 126 3 51 89 66 10 34 1 7901 1.4069 1320 124 3 45 93 11 6 89 1 8754 1.5587 1380 128 3 56 96 68 3 32 1 9606 1.7105 1440 119 3 31 100 00 0 00 2 0459 1.8622 ALL REMAINING FREQUENCY CLASSES ARE ZERO Appendix C. Output From Standard Run TABLE ORDAY ENTRIES IN TABLE 3589 MEAN ARGUMENT 3.9685 STANDARD DEVIATION 1.8307 SUM OF ARGUMENTS 14243.0000 NON-WEIGHTED UPPER LIMIT 1 2 3 4 5 6 7 OBSERVED FREOUENCY 388 498 637 612 606 466 382 PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION OF TOTAL 10.81 13.87 17.74 17.05 16.88 12.98 10.64 PERCENTAGE 10.81 24 42 59 76 89 100 68 43 48 37 35 00 REMAINDER 89 . 19 75. 57. 40. 23. 10. 0. . 32 .57 .52 .63 .65 .00 OF MEAN .2519 . 5039 . 7559 1.0079 1.2599 1.5119 1 . 7638 FROM MEAN -1.6214 - 1.0752 -.5290 1.7198E-02 .5634 1.1096 1.6558 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE PARZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 3850 107.9680 46.7157 4.1567E*05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 15 0 0.00 0 .00 100 .00 . 1389 - 1.9900 30 20 0.51 0 .51 99 . 49 . 2778 - 1.6689 45 72 1 .87 2 . 38 97 .62 .4167 - 1.3479 60 237 6.15 8 . 54 91 . 46 . 5557 - 1.0268 . 75 489 12. 70 21 .24 78. 76 .6946 -.7057 90 677 17 .58 38 .83 61 . 17 .8335 -.3846 105 701 18 . 20 57 .03 42 .97 .9725 -6.3539E-02 120 515 13. 37 70 .41 29 .59 1 .1114 . 2575 135 401 10.41 80 .83 19 . 17 1 . 2503 .5786 150 270 7.01 87 .84 12 . 16 1 . 3893 .8997 165 153 3.97 91 .81 8 . 19 1 .5282 1.2208 180 74 . 1 .92 93 . 74 6 . 26 1 .667 1 1.5419 195 54 1 . 40 95 . 14 4. 86 1 .8060 1.8630 210 48 1 . 24 96 . 38 3. .62 1 .9450 2.1841 225 42 1 .09 97 .48 2. 52 2 0839 2.5051 240 16 0.41 97 .89 2. 1 1 2. . 2228 2.8262 255 10 0.25 98 . 15 1 . 85 2. .3618 3.1473 270 21 0 . 54 98 . 70 1 . 30 2. 5007 3.4684 285 14 0 . 36 99 .06 0. 94 2. .6396 3.7895 300 8 0.20 99 .27 0. 73 2. 7785 4.1106 315 9 0.23 99 . 50 0. 50 2 9175 4.4317 330 2 0.05 99. .55 0. 45 3. 0564 4.7528 345 3 0.07 99 .63 0. . 37 3 . 1953 5.0739 360 7 0. 18 99. .81 0. . 19 3 3343 5.3950 375 1 0.02 99 .84 0. 16 3 .4732 5.7160 390 1 0.02 99 .87 0. 13 3. .6121 6.0371 405 0 0.00 99 .87 0. 13 3. .7511 6.3582 420 0 0 .00 99. 87 0. 13 3 8900 6.6793 435 1 0.02 99. 89 0. 1 1 4 . 0289 7.0004 OVERFLOW 4 0. 10 100. 00 0. 00 AVERAGE VALUE OF OVERFLOW IS 501.5000 Appendix C. Output From Standard Run TABLE DOSZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 932 608.3950 508.0070 5.6702E*05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 30 3. 21 3. 21 96 . 79 9.8620E-02 - 1.0795 120 125 13. 41 16. 63 83. 37 1972 - .9613 180 195 20. 92 37. 55 62 . 45 2958 -.8432 240 121 12. 98 50. 53 49 . 47 3944 -.7251 300 13 1 . 39 51. 93 48 . 07 4931 -.6070 360 4 0 .42 52. 36 47 . 64 5917 -.4889 420 1 0 . 10 52. 46 47. 54 6903 -.3708 480 0 0. 00 52. 46 47 . 54 7889 -.2527 540 13 1 . 39 53. 86 46. 14 8875 -.1346 600 5 0 53 54. 39 45. 61 9862 • • 1.6524E-02 660 0 0 .00 54. 39 45. 61 1 . 0848 . 1015 7 20 9 0 .96 55. 36 44 . 64 1 . 1834 .2196 780 7 0 . 75 56. 1 1 43. 89 1 .2820 .3378 840 14 1 .50 57 . 61 42. 39 1 . 3806 . 4559 900 9 0 .96 58. 58 4 1 42 1. 4793 .5740 960 21 2 .25 60 .83 39 . 17 1 .5779 .6921 1020 23 2 .46 63. 30 36 . 70 1 .6765 .8102 1080 49 5 .25 68 . 56 31 44 1 . 7751 .9283 1140 84 9 .01 77 .57 22 .43 1 .8737 1.0464 1200 74 7 .93 85 .51 14 . 49 1 .9724 1.1645 1260 25 2 .68 88 . 19 1 1 .81 2 .0710 1.2826 1320 29 3 . 11 91 . 30 8 . 70 2 . 1696 1.4007 1380 39 4 . 18 95 .49 4 .51 2 .2682 1.5188 1440 26 2 . 78 98 .28 1 .72 2 . 3668 1 .6369 1500 16 1 . 7 1 100 .00 0 .00 2 .4655 1.7551 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE PPZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 12699 4908.6900 2109.7500 6.2335E*07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 480 3. 77 3. 77 96. 23 .2933 - 1 .6441 2880 1353 10. 65 14. 43 85. 57 .5867 -.9615 4320 3422 26 .94 41 . 38 58. .62 .8800 -.2790 5760 3638 28 .64 70. 02 29. .98 1 . 1734 .4035 7200 2066 16 . 26 86 . 29 13 . 7 1 1 . 4667 1.0860 8640 1347 10 .60 96. .90 3 . 10 1 .7601 1.7686 10080 204 1 .60 98. 51 1 . .49 2 .0535 2.4511 1 1520 99 0 . 77 99 .29 0 . 7 1 2. . 3468 3.1337 12960 42 0 . 33 99. .62 0 . 38 2 .6402 3.8162 14400 7 0 .05 99 .67 0 .33 2 .9335 4.4987 15840 9 0 .07 99 . 74 0 . 26 3 . 2269 5.1813 1 7280 0 0 .00 99 . 74 0 .26 3 . 5202 5.8638 18720 6 0 .04 99 . 79 0 .21 3 .8136 6.5464 20160 16 0 . 12 99 .92 0 .08 4 . 1070 7.2289 21600 10 0 .07 100 .00 0 .00 4 . 4003 7.9115 Appendix C. Output From Standard Run ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE PPZ2 ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 12)58 5074.8000 2016.4300 6.1699E+07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 213 1 . 75 1 . 75 98 . 25 .2837 - 1 .8026 2880 1066 8 . 76 10 .51 89 .49 .5675 - 1.0884 4320 3385 27 .84 38 . 36 61 .64 .8512 -.3743 5760 3676 30 .23 68 . 59 31 . 41 1 . 1350 . 3398 7200 206 7 17 .00 85 .59 14 . 4 1 1 .4187 1.0539 8640 1362 11 . 20 96 . 80 3 .20 1 . 7025 1.7680 10080 199 1 .63 98 .43 1 , .57 1 .9862 2.4822 1 1520 98 0 .80 99 .24 0. 76 2 .2700 3.1963 12960 43 0 . 35 99 . 59 0 41 2. 5537 3.9104 14400 8 0 .06 99 . 66 0 . 34 2. .8375 4.6246 15840 9 0 .07 99 . 73 0. 27 3 . 1213 5.3387 1 7280 0 0 .00 99. 73 0. 27 3 .4050 6.0528 18720 4 0 .03 99. . 76 0. 24 3. 6888 6.7670 20160 17 0 1 3 99. 90 0 . 10 3. 9725 7.4811 21600 1 1 0. 09 100. 00 0. 00 4 . 2563 8.1952 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE TREAZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 267 161.9890 126.8780 43251.0000 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 73 27 . 34 27 . 34 72 . 66 . 3703 -.8038 120 50 18 . 72 46.06 53.94 . 7407 -.3309 180 39 14 .60 60.67 39. 33 1.1111 . 1419 240 38 14 . 23 74 . 90 25. 10 1 .4815 .6148 300 22 8 .23 83. 14 16.86 1.8519 1.0877 360 20 7 . 49 90.63 9 . 37 2.2223 1.5606 420 15 5 6 1 96 . 25 3. 75 2.5927 2.0335 480 8 2 . 99 99.25 0. 75 2.9631 2.5064 540 1 0 . 37 99.62 0. 38 3.3335 2.9793 600 1 0. . 37 100.00 0.00 3.7039 3.4522 ALL REMAINING FREQUENCY CLASSES ARE ZERO. Appendix C. Output From Standard Run TABLE PPTB ENTRIES IN TABLE 47 MEAN ARGUMENT 211.9570 STANDARD DEVIATION 122.1170 SUM OF ARGUMENTS 9962.0000 NON-WEIGHTED UPPER LIMIT 360 720 OBSERVED FREQUENCY 42 5 PERCENT OF TOTAL 89 . 36 10.63 CUMULATIVE PERCENTAGE 89 . 36 100.00 CUMULATIVE REMAINDER 10 64 0.00 MULTIPLE OF MEAN 1.6984 3.3969 DEVIATION FROM MEAN 1.2123 4.1603 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE FLAG ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 734 1002.7700 545.4640 7.3603E*05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 360 136 18 . 52 18.52 81 . 48 . 3590 - 1.1783 720 198 26.97 45.50 54 . 50 .7 180 -.5184 1080 1 1 1 . 49 47 .00 53.00 1.0770 . 1415 1440 80 10.89 57.90 42 . 10 1.4360 .8015 1800 309 42.09 100.00 0.00 1.7950 1.4615 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE DISZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 14549 768.7740 207.5760 1.1184E+07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 90 0 .61 0 .61 99 . 39 7.8046E-02 -3.4145 120 95 0 .65 1 .27 98 .73 . 1560 -3.1254 180 94 0 .64 1 .91 98 .09 .2341 -2.8364 240 72 0 . 49 2 .41 97 .59 .3121 -2.5473 300 80 0 . 54 2 .96 97 .04 . 3902 -2.2583 360 102 0 . 70 3 .66 96 . 34 .4682 - 1.9692 420 98 0. 67 4 . 33 95. .67 . 5463 - 1.6802 480 107 0 . 73 5 .07 94 .93 .6243 - 1.3911 540 150 1 . .03 6 . 10 93. .90 . 7024 - 1. 1021 600 1531 10. .52 16 .62 83. 38 . 7804 -.8130 660 680 4 . 67 21 . 30 78 . 70 .8585 -.5240 720 2210 15. . 19 36 .49 63. 51 .9365 -.2349 780 3064 21 . 05 57 . 55 42. 45 1.0146 5.4O79E-02 840 2159 14 . 83 72. 38 27 . 62 1.0926 . 3431 900 1555 10. 68 83 .07 16 . 93 1.1706 .6321 960 684 4 . 70 87. 77 12. 23 1.2487 .9212 1020 427 2. 93 90. 71 9. 29 1.iZ67 1 .2102 1080 305 2. 09 92. .81 7 . 19 1.4048 1 . 4993 1 140 196 1 . 34 94 15 5. 85 1.4828 1.7883 1200 221 1 . 51 95 . 67 4 . 33 1.5609 2.0774 1260 248 1 . 70 97 , 38 2. 62 1.6389 2.3664 1320 170 1 . 16 98 . 54 1 . 46 1.7170 2.6555 Appendix C. Output From Standard Run 1380 124 0.85 99.40 0.60 1.7950 2.9445 1440 87 0.59 100.00 0.00 1.8731 3.2336 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE LRNZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 6689 113.4290 65 9182 7.5872E+05 NON-WEIGH UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 30 325 4 85 4 85 95 15 2644 - 1.2656 60 765 11 43 16 29 83 71 5289 -.8105 90 1530 22 87 39 16 60 84 7934 -.3554 120 1494 22 33 61 50 38 50 1 0579 9.9678E-02 150 1 191 17 80 79 30 20 70 1 3224 .5547 180 572 8 55 87 86 12 14 1 5868 1.0099 210 488 7 29 95 15 4 85 1 8513 1.4650 240 122 1 82 96 98 3 02 2 1158 1.9201 270 47 0 70 97 68 2 32 2 3803 2.3752 300 65 0 97 98 65 1 35 2 6448 2.8303 330 23 0 34 98 99 1 01 2 9093 3.2854 360 21 0 31 99 31 0 69 3 1737 3.7405 390 21 0 31 99 62 0 38 3 4382 4.1956 420 7 0 10 99 73 0 27 3 7027 4.6507 450 5 0 07 99 80 0 20 3 9672 5.1058 480 2 0 02 99 83 0 17 4 2317 5.5609 510 2 0 02 99 86 0 14 4 4961 6.0161 540 0 0 00 99 86 0 14 4 7606 6.47 12 570 1 0 01 99 88 0 12 5 0251 6.9263 OVERFLOW 8 0 1 1 100 00 0 00 AVERAGE VALUE OF OVERFLOW IS 863 7500 TABLE HRNZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 5070 117.2850 125.3650 5.9463E+05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 30 862 17 00 17 00 83 00 .2557 -.6962 60 539 10 63 27 63 72 37 .5115 -.4569 90 776 15 30 42 93 57 07 . 7673 -.2176 120 789 15 56 58 50 4 1 50 1 .0231 2. 1655E-02 150 900 17 75 76 25 23 75 1.2789 . 2609 180 538 10 61 86 86 13 14 1.5347 . 5002 210 246 4 85 91 7 1 8 29 1.7905 . 7395 240 137 2 70 94 4 1 5 59 2.0462 .9788 270 68 1 34 95 75 4 25 2.3020 1.2181 300 79 1 55 97 31 2 69 2.5578 1.4574 330 8 0 15 97 47 2 53 2.8136 1.6967 360 9 0 17 97 65 2 35 3.0694 1.9360 390 17 0 33 97 98 2 02 3.3252 2.1753 4 20 6 0 11 98 10 1 90 3.5810 2.4146 Appendix C. Output From Standard Run 450 6 0.11 98.22 1.78 3.8368 2.6539 480 10 0.19 98.42 1.58 4.0925 2.8932 510 10 0.19 98.61 1.39 4.3483 3.1325 540 8 0.15 98.77 1.23 4.6041 3.3718 570 7 0.13 98.91 1.09 4.8599 3.6111 OVERFLOW 55 1.08 100.00 0.00 AVERAGE VALUE OF OVERFLOW IS 1004.3600 TABLE OBNZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 1928 3058.1600 6832.6900 5.8961E+06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 1341 69. 55 69 55 30 .45 .4708 -.2368 2880 188 9 . 75 79 30 20 . 70 .9417 -2.6074E-02 4320 103 5. 34 84 ,64 15 . 36 1.4126 . 1846 5760 65 3. 37 88. .01 1 1 .99 1 .8834 . 3954 7 200 28 1 . 45 89 47 10 .53 2.3543 .6061 8640 25 1 . 29 90 76 9 . 24 2.8252 .8169 10080 19 0. .98 91 . 75 8 . 25 3.2961 1.0276 1 1520 9 0 .46 92 .21 7 . 79 3.7669 1.2384 12960 23 1 . 19 93 41 6 .59 4.2378 1.4491 14400 20 1 . 03 94, .45 5 .55 4.7087 1.6599 15840 13 0 . 67 95 . 12 4 .88 5.1795 1.8706 17280 10 0. 51 95 .64 4 . 36 5.6504 2.0814 18720 14 0. 72 96 . 36 3 .64 6.1213 2.2921 20160 7 0. 36 96 . 73 3 .27 6.5922 2.5029 21600 5 0. 25 96 .99 3 .01 7.0630 2.7136 23040 0 0. 00 96 99 3 .01 7.5339 2.9244 24480 2 0. 10 97 .09 2 .91 8.0048 3.1352 25920 5 0. .25 97 . 35 2 .65 8.4757 3.3459 27360 4 0 .20 97 .56 2 .44 8.9465 3.5567 OVERFLOW 47 2. 43 100 00 0 00 AVERAGE VALUE OF OVERFLOW IS 38015.8000 TABLE OBNTB ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 274 614.7950 825.8020 1.6845E+05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 360 146 53 .28 53 28 46.72 .5855 ' -.3085 720 56 20 .43 73. .72 26.28 1 .1711 . 1273 1080 19 6 .93 80 .65 19 . 35 1 . 7566 . 5633 1 440 24 8 . 75 89 41 10.59 2 . 3422 .9992 1800 15 5 .47 94 . 89 5.11 2 .9278 1 .4352 2 160 3 1 .09 95 .98 4.02 3 .5133 1.8711 2520 5 1 . 82 97 .81 2. 19 4 .0989 2.307D 2880 0 0 .00 97 .81 2. 19 4 . 6844 2.7430 3240 1 0 . 36 98 . 17 1 .83 5 . 2700 3.1789 OVERFLOW 5 1 . 82 100. 00 0.00 Appendix C. Output From Standard Run AVERAGE VALUE OF OVERFLOW IS 4904.6000 TABLE PPNZ ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 11937 4943.6900 2113.5100 5.9012E+07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 335 2 .80 2 .80 97 . 20 .2912 - 1.6577 2860 704 5 .89 8 .70 91 . 30 .5825 -.9764 4320 4077 34 . 15 42 .85 57 . 15 .8738 -.2950 5760 3387 28 . 37 7 1 .23 28 . 77 1 . 1651 . 3862 7 200 1834 15 . 36 86 .59 13 .41 1 . 4564 1.0675 8640 1 172 9 .81 96 .41 3 .59 1 . . 7476 1.7489 10080 207 1 . 73 98. . 14 1 .86 2. 0389 2.4302 11520 121 1 .01 99 . 16 0 . 84 2 3302 3.1115 12960 43 0 . 36 99 .52 0 .48 2. .6215 3.7928 14400 20 0 . 16 99. 69 0 .31 2. 9128 4.4742 15840 6 0 .05 99 . 74 0 26 3. 2040 5.1555 17280 7 0 .05 99 79 0 .21 3. 4953 5.8368 18720 4 0. 03 99 .83 0 . 17 3 . 7866 6.5182 20160 2 0 .01 99 .84 0 16 4 . 0779 7.1995 21600 5 0 .04 99 . 89 .0 . 1 1 4 3692 7.8808 23040 5 0 04 99 .93 0 .07 4 6604 8.5622 24480 1 0 .00 99 94 0 06 4 . 9517 9.2435 25920 3 0 02 99 . 96 0 04 5. 24 30 9.9248 27360 1 0 00 99 97 0 03 5. 5343 10.6062 OVERFLOW 3 0. .02 100. 00 0. 00 AVERAGE VALUE OF OVERFLOW IS 27883.0000 TABLE ATIM2 ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 11373 725.5440 414.8210 8.2516E*06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 456 4 .00 4 .00 96 .00 8.2696E-02 - 1.6044 120 431 3 . 78 7 .79 92 .21 . 1653 - 1 .4597 180 490 4 . 30 12 . 10 87 .90 . 2480 -1.3151 240 488 4 .29 16 .39 83 .81 . 3307 - 1.1704 300 486 4 .27 20 .67 79 . 33 .4134 - 1.0258 360 489 4 .29 24. .97 75 .03 .4961 -.8812 4 20 443 3 .89 28 .86 71 . 14 . 5788 -.7365 480 457 4 .01 32. .88 67 . 12 .6615 -.5919 540 460 4 .04 36. .92 63 .08 . 7442 -.4472 600 449 3 . 94 40 .87 59 . 13 .8269 -.3026 660 482 4 . 23 45. . 11 54 .89 . 9096 -.1580 720 483 4 . 24 49 . 36 50. 64 .9923 - 1 . 3364E-02 780 477 4 . 19 53. 55 46 .45 1.0750 .1312 840 527 4 .63 58. 19 41 . 81 1.1577 . 2759 900 429 3. 77 61 .96 38 04 1.2404 .4205 960 490 4 30 66. 27 33 . 73 1.3231 .5651 1020 457 4 , .01 70. 28 29 . 72 1.4058 . 7098 Appendix C. Output From Standard Run 1080 445 3.91 74.20 25.80 1.4885 .8544 1140 514 4.51 78.72 21.28 1.5712 .9991 1200 532 4.67 83.39 16.61 1.6539 1.1437 1260 479 4.21 87.61 12.39 1.7366 1.2884 1320 479 4.21 91.82 8.18 1.8193 1.4330 1380 457 4.01 95.84 4.16 1.9020 1.5776 1440 473 4.15 100.00 0.00 1.9847 1.7223 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE ATIME ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 930 657.6580 200.9790 6.1162E*05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 0 0 .00 0 .00 100 .00 9.1232E-02 -2.9737 120 0 0 .00 0 .00 100 .00 . 1824 -2.6751 180 0 0 .00 0 .00 100 .00 .2736 -2.3766 240 0 0 .00 0 .00 100 .00 .3649 -2.0781 300 0 0 .00 0 .00 100 .00 .4561 -1.7795 360 0 0 .00 0 .00 100 .00 . 5473 - 1.4810 420 91 9. . 78 9 . 78 90 . 22 .6386 - 1.1825 480 98 10. .53 20 . 32 79 .68 . 7298 -.8839 540 117 12 .58 32 .90 67 . 10 .8210 -.5854 600 121 13. 01 45 .91 54 .09 .9123 -.2868 660 93 10. .00 55 .91 44 .09 1 .0035 1.1653E-02 720 94 10 10 66 .02 33 .98 1.0947 .3101 780 92 9 . 89 75 .91 24 .09 1.1860 .6087 840 97 10. 43 86 . 34 13 .66 1.2772 .9072 900 5 0. 53 86 .88 13 .12 1.3684 1.2058 960 27 2. 90 89. . 78 10 .22 1.4597 1.5043 1020 26 2. 79 92. .58 7 .42 1.5509 1.8028 1080 22 2. 36 94 94 5. 06 1.6421 2.1014 1 140 23 2. 47 97. 41 2. .59 1.7334 2.3999 1200 22 2 . 36 99. 78 0 .22 1.8246 2.6985 1260 2 0. 21 100. 00 0. 00 1.9158 2.9970 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE ARATE ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 11373 78.5058 79.9164 8.9284E+05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 20 2665 23.43 23.43 76.57 . 2547 -.7320 40 1985 17.45 40.88 59 . 12 . 5095 -.4818 60 1510 13.27 54 . 16 45.84 . 7642 -.2315 80 1 136 9 . 98 64 . 15 35.85 1 .0190 1.8697E-02 100 907 7 .97 72.12 27 . 88 1.2737 . 2689 120 7 1 1 6.25 78. 37 21 .63 1.5285 .5192 140 573 5.03 83.41 16 . 59 1.7833 . 7694 160 426 3. 74 87.16 12.B4 2.0380 1 .0197 Appendix C. Output From Standard Run 180 327 2 .87 9 0 . 0 3 9 . 9 7 2 . 2 9 2 8 1 . 2 7 0 0 200 250 2 . 19 92 . 23 7 . 77 2 . 5 4 7 5 1 . 5 2 0 2 2 2 0 201 1 . 76 94 . 0 0 6 . 0 0 2 8 0 2 3 1 . 7 7 0 5 2 4 0 146 1 , . 2 8 95 . 28 4 . 72 3. . 0 5 7 1 2. . 0 2 0 7 2 6 0 1 10 0 . .96 96 . 2 5 3 . 75 3. 3118 2. 2 7 1 0 2 8 0 89 0 . 78 97 . 0 3 2 .97 3. 5 6 6 6 2. 5 2 1 3 300 6 8 0 . 5 9 97 . 6 3 2 . 37 3 . 8 2 1 3 2 . 7 7 1 5 320 73 0 . 6 4 98 . 2 7 1 . 73 4 . 0 7 6 1 3 . 0 2 1 8 340 33 0 . 29 98 . 5 6 1 . 44 4 . 3308 3 . 2 7 2 1 360 47 0 .41 98 . 9 8 1 . 0 2 4 . 5 8 5 6 3 . 5 2 2 3 380 23 0 . 20 99 . 18 0 . 8 2 4. . 8 4 0 4 3 7726 4 0 0 19 0 . 16 99 . 34 0 . 6 6 5. . 0 9 5 1 4 0 2 2 8 4 2 0 12 0 . 10 99 . 4 5 0 . 5 5 5. . 3 4 9 9 4 . 2731 4 4 0 9 0 . 07 99 . 53 0 .47 5. 6 0 4 6 4 . 5234 460 12 0 . 10 99 . 6 3 0 . 37 5. 8 5 9 4 4 . 7736 4 8 0 1 1 0 . 0 9 99 . 7 3 0 . 27 6 1142 5 . 0 2 3 9 500 5 0 . 04 99 78 0 . 2 2 6 . 3689 5. . 2 7 4 1 5 2 0 2 0 . 01 99 . 79 0 .21 6 . 6 2 3 7 5. . 5244 5 4 0 5 0 . 04 99 .84 0 . 16 6 . 8 7 8 4 5. . 7 7 4 7 5 6 0 2 0 . 01 9 9 . . 8 5 0 . 15 7 . 1332 6. . 0 2 4 9 5 8 0 4 0 . 0 3 99 . .89 0 . 11 7 , 3879 6 . 2752 OVERFLOW 12 0 . 10 100 . 0 0 0 0 0 A V E R A G E V A L U E OF OVERFLOW I S 6 7 5 . 0 0 0 0 T A B L E DOSDL E N T R I E S IN T A B L E MEAN ARGUMENT STANDARD D E V I A T I O N SUM OF ARGUMENTS 9 3 2 6 8 3 . 0 4 1 0 3 3 2 . 1 8 3 0 6 . 3 6 5 9 E * 0 5 NON-WEIGHTED UPPER O B S E R V E D P E R C E N T 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 D E V I A T I O N L I M I T F R E Q U E N C Y OF TOTAL P E R C E N T A G E REMAINDER OF MEAN FROM MEAN 60 28 3 . 0 0 3 . 0 0 97 . 0 0 8 . 7 8 4 2 E - 0 2 - 1 . 8 7 5 6 120 18 1 . 9 3 4 . 9 3 95 . 0 7 . 1756 - 1 . 6 9 4 9 180 23 2 . 4 6 7 . 40 92 . 60 . 2 6 3 5 - 1 . 5 1 4 3 2 4 0 39 4 . 18 1 1 . 58 88 . 4 2 . 3513 - 1 . 3 3 3 7 300 27 2 . 89 14 . 48 85 . 52 . 4 3 9 2 - 1 . 1 5 3 1 360 38 4 .07 18 . 56 81 . 44 . 5 2 7 0 - . 9 7 2 4 4 2 0 43 4 .61 23 . 17 76 . 8 3 . 6 1 4 8 - . 7 9 1 8 4 8 0 40 4 . 29 27 . 4 6 72 . 54 . 7027 - . 6 1 1 2 5 4 0 55 5 . 9 0 33 . 3 6 66 . 6 4 . 7905 - . 4 3 0 6 6 0 0 54 5 . 79 39 . 16 60 . 8 4 . 8784 - . 2 4 9 9 6 6 0 71 7 .61 46 . 78 53 . 22 . 9 6 6 2 - 6 . 9 3 6 1 E - 0 2 720 76 8 15 5 4 . . 9 3 45 .07 1 . 0 5 4 1 . 1 1 1 2 780 67 7 . 18 6 2 . . 12 37 . 8 8 1 . 1419 . 2918 8 4 0 50 5. 36 6 7 . 48 3 2 . . 5 2 1 . 2 2 9 7 . 4 7 2 5 9 0 0 66 7 . 0 8 74 , 57 2 5 . .43 1 . 3 1 7 6 . 6 5 3 1 9 6 0 51 5 .47 80 04 19 .96 1 . 4054 . 8 3 3 7 1020 43 4 .61 84 . 6 5 15 . 35 1 . 4 9 3 3 1 . 0 1 4 3 1080 25 2 . 6 8 8 7 . 33 12 .67 1 .581 1 1 . 1 9 5 0 1140 23 2. 46 89 . . 8 0 10. 20 1 . 6 6 9 0 1 . 3 7 5 6 1200 29 3. 1 1 9 2 . 91 7 .09 1 . 7568 1 . 5 5 6 2 1260 18 1 , 93 9 4 . 84 5 . 16 1 . 8 4 4 6 1 . 7 3 6 8 1320 18 1 . 93 . 9 6 . 78 3 22 1 . . 9 3 2 5 1 . 9 1 7 5 1380 17 1 . 82 98 . 60 1 , 40 2 . 0 2 0 3 2 . 0 9 8 1 1440 13 1 . 39 100 . 0 0 0 . 0 0 . 2 . 1082 2 . 2 7 8 7 ALL R E M A I N I N G F R E Q U E N C Y C L A S S E S ARE ZERO Appendix C. Output From Standard Run TABLE DL ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 11490 716.1510 412.5640 8.2285E*06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 60 489 4 25 4 .25 95. . 75 8.3781E-02 - 1 .5904 120 455 3. 95 8 .21 91 . 79 . 1675 - 1.4449 180 498 4 . 33 12. .55 87. .45 .2513 -1.2995 240 456 3. 96 16. .51 83 .49 . 3351 -1.1541 300 516 4. 49 21 . 00 79 00 .4189 - 1.0086 360 478 4. 16 25 . 16 74. .84 .5026 -.8632 420 492 4 . 28 29 .45 70 .55 .5864 -.7178 480 482 4 . 19 33 .64 66 . 36 .6702 -.5723 540 463 4 . 02 37. .67 62. . 33 . 7540 -.4269 600 463 4 . 02 41 . 70 58 . 30 .8378 -.2815 660 491 4 27 45 .97 54 .03 .9215 -.1361 720 472 4 . 10 50 08 49 . 92 1 .0053 9.3297E-03 780 517 4 . 49 54 . 58 45 .42 1 .0891 . 1547 840 503 4 . 37 58 .96 41 .04 1 . 1729 . 3001 900 444 3. 86 62 .82 37 . 18 1 .2567 . 4456 960 509 4 42 67 .25 32 . 75 1 . 3405 . 5910 1020 500 4 . 35 71 .61 28 . 39 1 .4242 .7364 1080 439 3 .82 75 .43 24 . 57 1 . 5080 .8819 1140 517 4 . 49 79 .93 20 .07 1 . 59 18 1 .0273 1200 497 4 . 32 84 . 25 15 .75 1 .6756 1.1727 1260 465 4 . 04 88 . 30 11 . 70 1 . 7594 1.3182 1320 445 3. 87 92 . 17 7 .83 1 .8431 1.4636 1380 434 3 . 77 95 . 95 4 .05 1 .9269 1.6090 1440 465 4 .04 100 .00 0 .00 2 .0107 1.7545 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE DELAP ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 12304 1459.2600 4311.0000 1.7954E+07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 10369 84. 27 84 .27 15. 73 .9868 -4.4680E-03 2880 998 8. 1 1 92 . 38 7 . 62 1 . .9736 .3295 4320 256 2 08 94 . 46 5. 54 2 .9604 .6635 5760 1 17 0. 95 95 .41 4 . 59 3 .9472 .9976 7200 96 0. 78 96 . 19 3. 81 4 . 9340 1.3316 8640 65 0. 52 96 . 72 3. 28 5. .9208 1.6656 10080 60 0 48 97 .21 2. 79 6. .9076 1.9997 1 1520 39 0. 31 97 .52 2. 48 7 . 8944 2.3337 12960 35 0 .28 97 .81 2. . 19 8 .8812 2.6677 14400 26 0. 21 98 .02 1 . 98 9 . 8680 3.0018 15840 15 0. . 12 98 . 14 1 . .86 10. 8548 3.3358 17280 12 0. 09 98 . 24 1 . 76 1 1 . .8416 3.669B 18720 19 0 . 15 98 . 39 1 . .61 12. 8284 4.0038 20160 14 0 1 1 98 .51 1 . 49 13 .8152 4.3379 21600 24 0. . 19 98 . 70 1 30 14 .8020 4.67 19 23040 16 0 . 1 3 98 . 83 1 . 17 15 . 7888 5.0059 24480 23 0 . 18 99 .02 0 .98 16 . 7756 5.3400 Appendix C. Output From Standard Run 25920 1 1 0 .08 99 . 11 0 . 89 17 . 7624 5 .6740 27300 1 1 0 .08 99 . 20 0. . 80 18 . 7492 6 .0080 28800 15 0 . 12 99 . 32 0 .68 19 .7 360 6 . 3420 30240 7 0 .05 99 . 38 0 .62 20 . 7228 6 .6761 31680 9 0 .07 99 .45 0 .55 21 . 7096 7 .0101 33120 6 0 .04 99 .50 0. 50 22 .6964 7 . 344 1 34560 3 0. 02 99 .52 0 48 23 .6832 7 .6782 36000 6 0 .04 99 . 57 0. 43 24 .6 700 8 .0122 37440 5 0 04 99. .61 0. 39 25. .6568 8 . 3462 38880 4 0. .03 99 .65 0. 35 26 .6436 8 .6803 40320 7 0. 05 99 . 70 0. 30 27. .6304 9 .0143 41760 3 0. 02 99. .73 0. 27 28. 6172 9 3483 OVERFLOW 33 0. 26 100 .00 0. 00 AVERAGE VALUE OF OVERFLOW IS 47882.3000 TABLE OELPP ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 12310 5243.5800 2005.5800 6.4548E*07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 720 6 0 .04 0 .04 99 .96 . 1373 -2.2555 1440 109 0 . 88 0 .93 99 .07 . 2746 - 1 .8965 2160 225 1 .82 2 . 76 97 .24 .4119 - 1 .5375 2880 740 6 .01 8 . 77 91 .23 .5492 -1.1785 3600 930 7 .55 16 . 32 83 .68 .6865 -.8195 4320 2105 17 .09 33 .42 66 .58 .8238 -.4605 5040 2669 21 .68 55 . 10 44 .90 .961 1 - . 1015 5760 1483 12 .04 67 . 15 32 .85 1 .0984 . 2574 6480 937 7 .61 74 .76 25 .24 1 . 2358 .6164 7200 1010 8 .20 82 . 97 17 .03 1 . 373 1 .9754 7920 1178 9 .56 92 .54 7 . 46 1 .5104 1.3344 8640 473 3 .84 96 . 38 3 .62 1 .6477 1.6934 9360 152 1 . 23 97 .61 2 . 39 1 . 7850 2.0524 10080 83 0 .67 98. 29 1 . 7 1 1 .9223 2.41 14 10800 74 0 .60 98 .89 1 . 11 2 .0596 2.7704 1 1520 36 0 . 29 99 . 18 0 .82 2 . 1969 3.1294 12240 36 0 .29 99 . 48 0 .52 2 . 3342 3.4884 12960 13 0 . 10 99 .58 0 .42 2 .47 15 3.8474 13680 6 0 .04 99 . 63 0 . 37 2. .6089 4.2064 14400 2 0 .01 99. 65 0 . 35 2 . 7462 4.5654 15120 9 0 .07 99 .72 0 . 28 2 .8835 4.9244 15840 2 0 01 99. 74 0 .26 3 .0208 5.2834 16560 0 0 00 99 74 0. 26 3. . 1581 5.6424 17280 0 0 . 00 99 . 74 0. 26 3 . 2954 6.0014 18000 0 0. .00 99. 74 0. . 26 3 .4327 6.3604 18720 5 0. 04 99. 78 0. 22 3. 5700 6.7194 19440 4 0 . 03 99 . 81 0. . 19 3 7073 7.0784 20160 7 0. 05 99. 87 0. 13 3 8447 7.4374 20880 16 0 . 12 100. 00 0 . 00 3. 9820 7.7964 ALL REMAINING FREQUENCY CLASSES ARE ZERO Appendix C. Output From Standard Run TABLE SPOPP ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 7308 4428.3200 1384.0300 3.2362E+07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 7 20 3 0. .04 0 .04 99. 96 . 1625 -2. 6793 1440 100 1 . 36 1 40 98. 60 . 3251 -2. . 1591 2160 184 2 .51 3 .92 96. .08 .4877 - 1 6389 2880 611 8 36 12 .28 87. 72 6503 - 1 1 187 3600 797 10. 90 23 . 19 76. 81 .8129 .5984 4320 1646 22 52 45 . 7 1 54. .29 .9755 -7.8261E-02 5040 2069 28 .31 74 .02 25. .98 1 .1381 .4419 5760 976 13. 35 87 . 38 12 .62 1 . 3007 .9621 6480 469 6 . 4 1 93 . 80 6. . 20 1 . 4633 1 . 4824 7200 234 3. . 20 97 .00 3 00 1 .6259 2 .0026 7920 111 1. .51 98 .52 1 48 1 . 7884 2 .5228 8640 55 0 . 75 99 . 27 0 . 73 1 .9510 3 .0430 9360 22 0 . 30 99 . 57 0 .43 2 . 1 136 3 . 5632 10080 6 0 .08 99 .65 0 35 2 . 2762 4 .0835 10800 9 0 . 12 99 . 78 0 . 22 2 .4388 4 .6037 1 1520 1 0 .01 99 .79 0 .21 2 .6014 5 . 1239 12240 0 0 .00 99 .79 0 .21 2 . 7640 5 .6441 12960 1 0 01 99 . 80 0 . 20 2 .9266 6 . 1643 13680 1 0 .01 99 .82 0 . 18 3 .0892 6 .6846 14400 2 0 .02 99 .84 0 . 16 3 .2518 7 . 2048 15120 9 0 . 12 99 . 97 0 .03 3 .4143 7 . 7250 15840 2 0 .02 100 .00 0 .00 3 . 5769 8 . 2452 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE INSPP ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 1877 4737.2100 1652.0600 8.8917E+06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 720 3 0. 15 0 . 15 99 . 85 . 1519 -2.4316 1440 7 0. 37 0 . 53 99. 47 . 3039 - 1.9958 2160 33 1 . 75 2 . 29 97 . 71 . 4559 - 1.5600 2880 1 19 6 . 33 8 .63 91 . 37 .6079 - 1.1241 3600 127 6 . 76 15 . 39 84 , .61 . 7599 -.6883 4320 416 22. 16 37 .55 62. 45 .9119 -.2525 5040 558 29. 72 67 .28 32. 72 1 .0639 . 1832 5760 311 16. 56 83 .85 16. 15 1 , .2159 .6191 6480 172 9 . 16 93 .02 6. .98 1 . 3678 1.0549 7200 67 3. 56 96 .59 3 .41 1 .5198 1.4907 7920 29 1 . 54 98 . 13 1 , 87 1 .67 18 1.9265 8640 1 1 0. 58 98 . 72 1 , 28 1 .8238 2.3623 9360 1 0 05 98 . 77 1 . 23 1 .9758 2.7982 10080 0 0. 00 98 .77 1 . .23 2 . 1278 3.2340 10800 0 0. 00 98 . 77 1 . .23 2 . 2798 3.6698 1 1520 3 0. 15 98 .93 1 07 2 .4318 4.1056 12240 8 0. 42 99 . 36 0. .64 2 . 5838 4.5414 12960 3 0 . 15 99 .52 0 48 2 . 7357 4.9773 13680 0 0 .00 99 . 52 0 48 2 .8877 5.4131 endix C. Output From Standard Run 14400 0 0 .00 99 . 52 0 .48 3 .0397 5 .8489 15120 0 0 .00 99 .52 0. .48 3 1917 6 .2847 15840 0 0 .00 99 .52 0 .48 3 . 3437 6 . 7205 16560 0 0 .00 99 .52 0. .48 3 4957 7 . 1564 17280 0 0 oo 99 .52 0. 48 3. .6477 7 . 5922 18000 0 0 .00 99 .52 0. .48 3. . 7997 8. .0280 18720 4 0 .21 99 . 73 0. .27 3. .9517 8 .4638 19440 3 0 . 15 99 .89 0. . 11 4 1036 8. .8996 20160 2 0 . 10 100 .00 0. 00 4 2556 9. .3355 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE ELCPP ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 1241 7369.1200 1647.0000 9.1450E+06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 7 20 0 0 .00 0 .00 100 .00 9.7704E-02 -4.0371 1440 0 0 .00 0 .00 100. 00 . 1954 -3.5999 2160 0 0. .00 0 .00 100. 00 .2931 -3.1628 2880 0 0. 00 0 .00 100. 00 . 3908 -2.7256 3600 0 0. 00 0 .00 100. 00 . 4885 -2.2884 4320 26 2. .09 2 .09 97 . 91 .5862 - 1 .8513 5040 19 1 . .53 3 .62 96 . 38 .6839 -1.4 141 5760 87 7 , .01 10 .63 89. 37 . 7816 -.9770 6480 118 9. 50 20 . 14 79. 86 .8793 - .5398 7200 292 23 .52 43 .67 56 . 33 .9770 -.1026 7920 438 35 . 29 78 96 21 .04 1 .0747 . 3344 8640 137 11 .03 90 .00 10 .00 1.1724 .77 16 9360 50 4 .02 94 .03 5. .97 1.2701 1.2087 10080 22 1 . 77 95 .80 4 .20 1.3678 1.6459 10800 26 2 .09 97 .90 2 . 10 1.4655 2.0831 1 1520 9 0 . 72 98 .63 1 . 37 1.5632 2.5202 12240 7 0 .56 99 . 19 0. .81 1.6609 2.9574 12960 1 0. .08 99 .27 0. .73 1.7586 3:3945 13680 0 0 00 99 .27 0. 73 1.8563 3.8317 14400 0 0. .00 99 . 27 0. . 73 1.9541 4.2689 15120 0 0. 00 99 .27 0. 73 2.0518 4.7060 15840 0 0. 00 99 .27 0. 73 2.1495 5.1432 16560 0 0. .00 99 . 27 0. .73 2.2472 5.5803 17280 0 0. 00 99 . 27 0. .73 2.3449 6.0175 18000 0 0 00 99 .27 0 .73 2.4426 6.4547 18720 1 0 .08 99 . 35 0 .65 2.5403 6.8918 19440 0 0 .00 99 . 35 0 .65 2.6380 7.3290 20160 2 0 . 16 99 .51 0 . 49 2.7357 7.7661 20880 6 0 .48 100 .00 0 .00 2.8334 8.2033 ALL REMAINING FREQUENCY CLASSES ARE ZERO lix C. Output From Standard Run TABLE EMCPP ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 1884 7510.3300 1844.2800 1.4149E*07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 7 20 0 0. 00 0 .00 100. 00 9.5867E-02 -3.6818 1440 2 0 10 0 . 10 99. 90 .1917 -3.2914 2160 8 0. 42 0 .53 99. 47 . 2876 -2.9010 2880 10 0 .53 1 ,06 98. 94 . 3834 -2.5106 3600 6 0 .31 1 . 38 98. ,62 . 4793 -2.1202 4320 17 0 .90 2 .28 97 . 72 .5752 - 1.7298 5040 23 1 .22 3 .50 96 ,50 .6710 - 1.3394 5760 109 5 . 78 9 .28 90 . 72 . 7669 -.9490 6480 178 9 . 44 18 . 73 81 ,27 . 862B -.5586 7200 417 22 13 40 .87 59 13 .9586 -.1682 7920 600 31 84 72 .71 27, 29 1 .0545 .2221 8640 270 14 . 33 87 .04 12 ,96 1.1504 .6125 9360 79 4 . . 19 91 .24 8 ,76 1.2462 1.0029 10080 55 2 .91 94 . 16 5 .84 1.3421 1 .3933 10800 39 2 .07 96 .23 3 .77 1.4380 1.7837 11520 23 1 . 22 97 .45 2 .55 1.5338 2.1741 12240 21 1 . 1 1 98 . 56 1 . 44 1.6297 2.5645 12960 8 0 42 98 .99 1 .01 1 .7256 2.9549 13680 5 0 . 26 99 .25 0, . 75 1.8214 3.3452 14400 0 0 .00 99 . 25 0 . 75 1.9173 3.7356 15120 0 0 .00 99 .25 0 . 75 2.0132 4.1260 15840 0 0 .00 99 . 25 0 . 75 2.1090 4.5164 16560 0 0 .00 99 .25 0 . 75 2.2049 4.9068 17280 0 0 .00 99 .25 0 . 75 2.3008 5.2972 18000 0 0 .00 99 . 25 0 . 75 2.3967 5.6876 18720 0 0 .00 99 . 25 0 . 75 2.4925 6.0780 19440 1 0 .05 99 . 30 0 . 70 2.5884 6.4684 20160 3 0 . 15 99 . 46 0 .54 2.6843 6.8588 20880 10 0 . 53 100 .00 0 .00 2.7801 7.2492 ALL REMAINING FREQUENCY CLASSES ARE ZERO. TABLE UNTOT ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 2013 7466.4800 9703.8500 1.5030E*07 NON-WEIGHTEO UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 374 18 .57 18 .57 81 .43 1928 - .6210 2880 327 16 . 24 34 .82 65 . 18 . 3857 -.4726 4320 320 15 .89 50 . 72 49 .28 5785 -.3242 5760 252 12 .51 63 . 23 36 .77 . 7714 -.1758 7200 159 7 .89 7 1 . 13 28 .87 9643 -2.7461E-02 8640 97 4 .81 75 .95 24 .05 1 157 1 . 1209 10080 57 2 . 83 78 . 78 2 1 . 22 1 . 3500 . 2693 1 1520 55 2 .73 81 .52 18 . 48 1 5428 .4177 12960 44 2 . 18 83 . 70 16 .30 1 7357 .5661 14400 48 2 . 38 86 .09 13 .91 1 .9286 .7 145 15840 42 2 .08 88 . 17 11 .83 2 . 1214 .8629 17280 34 1 . 68 89 .86 10 . 14 2 .3143 1.0113 Appendix C. Output From Standard Run 18720 25 1 24 91 10 8 90 2 5072 1 1597 20160 15 0 74 91 85 8 15 2 7000 1 3080 21600 13 0 64 92 49 7 51 2 8929 1 4564 23040 14 0 69 93 19 6 81 3 0857 1 6048 24480 17 0 84 94 03 5 97 3 2786 1 7532 25920 8 0 39 94 43 5 57 3 4715 1 9016 27360 12 0 59 95 03 4 97 3 6643 2 0500 28800 13 0 64 95 67 4 33 3 8572 2 1984 30240 9 0 44 96 12 3 88 4 0501 2 3468 31680 6 0 29 96 42 3 58 4 2429 2 4952 33120 3 0 14 96 57 3 43 4 4358 2 6436 34560 2 0 09 96 67 3 33 4 6286 2 7920 36000 4 0 19 96 87 3 13 4 8215 2 9404 37440 2 0 09 96 96 3 04 5 0144 3 0888 38880 6 0 29 97 26 2 74 5 2072 3 2372 40320 2 0 09 97 36 2 64 5 4001 3 3856 41760 6 0 29 97 66 2 34 5 5929 3 5340 OVERFLOW 47 2 33 100 00 0 00 AVERAGE VALUE OF OVERFLOW IS 50669.8000 TABLE PPTOT ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 226 4247.5200 2947.7700 9.5994E*05 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 720 36 15 92 15 92 84 08 . 1695 - 1. 1966 1440 26 11 50 27 43 72 57 . 3390 -.9524 2160 23 10 17 37 61 62 39 . 5085 -.7081 2880 6 2 65 40 26 59 74 .6780 -.4639 3600 6 2 65 42 92 57 08 .8475 -.2196 4320 14 6 19 49 1 1 50 89 1 .0170 2.4586E-02 5040 1 1 4 86 53 98 46 02 1.1865 . 2688 5760 14 6 19 60 17 39 83 1.3560 .5130 6480 28 12 38 72 56 27 44 1.5255 . 7573 7 200 13 5 75 78 31 21 69 1.6951 1 .0016 7920 34 15 04 93 36 6 64 1.8646 1.2458 8640 6 2 65 96 01 3 99 2.0341 1.4901 9360 0 0 00 96 01 3 99 2.2036 1.7343 10080 4 1 76 97 78 2 22 2.3731 1.9786 10800 5 2 21 100 00 0 00 2.5426 2.2228 ALL REMAINING FREQUENCY CLASSES ARE ZERO. Appendix C. Output From Standard Run TABLE NBTOT ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 11817 5318.3900 2276.9500 6.2847E--07 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREQUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 136 1 . 15 1 . 15 98 .85 .2707 - 1.7033 2880 608 5 . 14 6 .29 93 .71 .5415 - 1.0709 4 320 3483 29 .47 35. . 77 64 23 .8122 -.4384 5760 3677 31 . 1 1 66 88 33 . 12 1 .0830 . 1939 7200 1863 15 . 76 82 65 17 .35 1 . 3537 .8263 8640 1386 11 . 72 94 . 38 5 .62 1 .6245 1.4587 10080 309 2 .61 96 99 3 .01 1 .8953 2.0912 11520 154 1 . 30 98. .29 1 .71 2 . 1660 2.7236 12960 79 0 .66 98. .96 1 .04 2 .4368 3.3560 14400 44 0 . 37 99 . 33 0. .67 2 . 7075 3.9884 15840 17 0 . 14 99 48 0. 52 2 .9783 4.6209 17280 18 0 . 15 99 63 0. 37 3. .2491 5.2533 18720 14 0 . 11 99. 75 0 .25 3 5198 5.8857 20160 7 0 .05 99. 81 0 . 19 3 . 7906 6.5181 21600 6 0 .05 99. 86 0 . 14 4 .0613 7.1506 23040 6 0 .05 99. 91 0. .09 4 . 3321 7.7830 24480 2 0 .01 99. 93 0. 07 4 . 6029 8.4154 25920 3 0 .02 99 95 0 05 4 8736 9.0478 27360 2 0. .01 99. 97 0. 03 5. 1444 9.6803 OVERFLOW 3 0 .02 100. 00 0 00 AVERAGE VALUE OF OVERFLOW IS 28833.7000 TABLE SHTOT ENTRIES IN TABLE 547 MEAN ARGUMENT 17.4333 STANDARD DEVIATION 27.6569 SUM OF ARGUMENTS 9536.0000 NON-WEIGHTED UPPER OBSERVED LIMIT FREQUENCY 20 40 60 80 100 120 436 12 31 35 19 14 PERCENT CUMULATIVE CUMULATIVE OF TOTAL PERCENTAGE REMAINDER MULTIPLE DEVIATION 79 . 2 5. 6. 3 2. 70 19 66 39 47 55 79 . 70 81 .90 87.56 93.96 97 . 44 100.00 20.30 18. 10 12.44 6.04 2.56 0.00 OF MEAN 1.1472 2.2944 3.4417 4.5889 5.7361 6.8833 FROM MEAN 9.28O6E-02 B159 1 .5391 2.2622 2.9853 3.7085 ALL REMAINING FREQUENCY CLASSES ARE ZERO. Appendix C. Output From Standard Run TABLE PDTOT ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 225 15136.0000 13281.2000 3.4056E+06 NON-WEIGHTED UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREOUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 1440 1 0 .44 0 . 44 99 .56 9.5137E-02 - 1.0312 2880 24 10 .66 11 . 1 1 88 .89 . 1902 -.9228 4320 16 7 . 1 1 18 .22 81 . 78 .2854 -.8143 5760 25 ' 11 . 11 29 .33 70 .67 '.3805 -.7059 7200 24 10 .66 40 .00 60 .00 .4756 -.5975 8640 12 5 . 33 45 . 33 54 .67 .5708 -.4891 10080 19 8 .44 53 . 77 46 .23 .6659 -.3806 11520 10 4 44 58 .22 41 . 78 .7610 -.2722 12960 10 4 . 44 62 .66 37 . 34 .8562 -.1638 14400 4 1 . 77 64 . 44 35 .56 .9513 -5.5416E-02 15840 6 2. .66 67 . 1 1 32 .89 1.0465 5.3007E-02 17280 4 1 . 77 68. .88 31 . 12 1.1416 . 1614 18720 5 2 .22 7 1 . 1 1 28 .89 1.2367 . 2698 20160 3 1 . 33 72 . 44 27 . 56 1.3319 . 3782 21600 5 2. 22 74 . 66 25 . 34 1.4270 . 4867 23040 0 0. 00 74 . 66 25 . 34 1.5222 .5951 24480 1 0. 44 75 .11 24 .89 1.6173 .7035 25920 5 2. 22 77 . 33 22 .67 1.7124 .8119 27360 3 1. 33 78. 66 21. . 34 1.8076 .9203 28800 1 0. 44 79 . 11 20. 89 1.9027 1.0288 30240 5 2. 22 81. 33 18. 67 1.9978 1.1372 31680 2 0 . 88 82. 22 1 7 . 78 2.0930 1.2456 33120 3 1 . 33 83. 55 16. 45 2.1881 1.3540 34560 2 0. 88 84. 44 15. 56 2.2833 1.4525 36000 1 0. 44 84. 88 15. 12 2.3784 1.5709 37440 3 1 . 33 86 . 22 13 .78 2.4735 1.6793 38880 5 2. 22 88. 44 1 1 . 56 2.5687 1.7877 40320 8 3 . 55 92. 00 8. 00 2.6638 1.8962 41760 9 4 . 00 96. 00 4. 00 2.7589 2.0046 OVERFLOW 9 4 . 00 100. 00 0 00 AVERAGE VALUE OF OVERFLOW IS 43352.4000 TABLE ORWAI ENTRIES IN TABLE MEAN ARGUMENT STANDARD DEVIATION SUM OF ARGUMENTS 2059 3.67B4 15 .2521 7574.0000 NON-WEIGV UPPER OBSERVED PERCENT CUMULATIVE CUMULATIVE MULTIPLE DEVIATION LIMIT FREOUENCY OF TOTAL PERCENTAGE REMAINDER OF MEAN FROM MEAN 15 1929 93.68 93.68 6. 32 4.0777 . 7422 30 29 1 . 40 95.09 4.91 8.1555 1.7257 45 32 1 .55 96.64 3 . 36 1212333 2.7092 60 22 1 .06 97.71 2 . 29 16.3111 3.6927 75 18 0.87 98 . 59 1.41 20.3888 4.6761 90 12 0.58 99 . 17 0.83 24.4666 5.6596 105 4 0 . 19 99 . 36 0.64 28.5444 6.6431 120 8 0. 38 99 . 75 0.25 32.6221 7 . 6265 1 35 5 0.24 100.00 0.00 36.6999 8.6100 ALL REMAINING FREOUENCY CLASSES ARE ZERO Appendix C. Output From Standard Run 123 NON-ZERO FULLWORD SAVEVALUES: (NAME : VALUE) 2: 1339168. 1 : 6: 6. 18272 21220 NON-ZERO HALFWORO SAVEVALUES: (NAME : VALUE) 1: 204 . 2: 1204. NON-ZERO BYTE SAVEVALUES: (NAME : VALUE) 11: 4. 12: 3 FULLWORD MATRIX SAVEVALUE ROW/COL 1 12303 12310 DISCH 2 2233 2239 12593 12589 FULLWORD MATRIX SAVEVALUE DW/COL 1 2 3 4 5 6 7 8 9 10 1 7908 5260 1368 0 0 0 0 0 0 0 2 5693 863 1913 795 939 805 769 2759 0 0 3 7299 1877 310 1887 227 2006 0 0 930 0 4 6747 552 1578 299 1 109 131 1553 334 227 2006 6 606 1290 9903 504 224 2233 0 0 0 0 7 43 80 34 42 0 14337 0 0 0 0 8 1 7 1 7 0 14520 0 0 0 0 FULLWORD MATRIX SAVEVALUE I0W/C0L 1 2 3 4 5 6 7 8 9 10 1 0 673 775 2204 552 0 0 9220 1017 0 2 0 0 0 0 0 0 0 0 63 869 3 0 0 0 136 572 69 0 545 1113 1B3 4 0 0 1979 0 418 14 0 a 0 0 5 0 0 149 1 36 0 10 0 0 0 0 6 0 0 0 0 0 0 93 0 0 0 7 0 0 63 0 30 0 0 0 0 0 B 0 257 0 0 0 0 0 2 108? 1623 9 0 0 0 0 0 0 0 239 0 914 10 0 0 0 0 0 0 0 120 23 0 1 1 0 0 0 0 0 0 0 0 1 19 0 16 0 930 4 308 2378 1572 93 93 10126 34 17 3589 Appendix C. Output From Standard Run 124 IOW/COL 1 1 12 13 14 15 16 1 0 95 0 0 0 14536 2 0 0 0 0 0 932 3 0 0 0 0 1837 4455 4 0 0 0 0 0 241 1 5 0 0 0 0 0 1539 6 0 0 0 0 0 93 7 0 0 0 0 0 93 8 0 6853 0 0 264 10081 9 0 2078 1 0 101 3333 to 3409 31 0 0 3 3586 1 1 0 3283 0 0 0 3402 12 0 0 355 0 12344 12699 13 0 0 0 356 0 356 14 0 355 0 0 0 355 16 3409 12695 356 356 14549 0 FULLW0R0 MATRIX SAVEVALUE ROW/COL 1 6642 0 46 0 0 6690 5070 0 0 0 0 5070 466 400 849 0 211 1926 417 6181 3669 1677 0 1 1944 6 0 108 504 251 117 26 12589 12595 6689 5070 1928 1 1937 FULLWORD MATRIX SAVEVALUE ROW/COL 1 171 513 APNUM 2 159 385 509 156 262 106 234 100 226 68 3 3 4 267 393 428 2288 2023 FULLWOBO MATRIX SAVEVALUE ROW/COL 1 8674 13 2019 3454 Appendix C. Output From Standard Run 125 FULLWORD MATRIX SAVEVALUE ORCAT ROW/COL 1 2 3 1 15 133 247 2 2 214 67 3 1 1253 23 4 6 1963 19 5 0 26 0 6 69 0 0 FULLWORD MATRIX SAVEVALUE CSTEN ROW/COL 1 1 14240 2 3269 4 4319 5 64 6 2234 7 46340 8 50024 9 27 10 4137 FULLWORD MATRIX SAVEVALUE CSMID ROW/COL 1 1 14212 2 3264 4 4295 5 56 6 2327 7 42865 8 46532 9 1 1 10 4129 HALFWORD MATRIX SAVEVALUE ARRIV ROW/COL 1 2 1 19 0 2 17 0 3 16 0 4 18 0 5 15 2 6 20 3 7 21 4 8 19 0 9 14 2 Appendix C. Output From Standard Run 126 10 19 1 11 20 0 12 18 1 13 18 4 14 21 3 15 17 0 15 1 1 0 17 22 0 18 22 0 19 24 0 20 13 3 21 14 2 22 20 2 23 18 1 24 23 0 25 19 0 26 23 0 27 17 2 28 14 1 29 24 1 30 15 1 31 24 1 HALFWORD MATRIX SAVEVALUE APPBL ROW/COL 1 2 3 1 362 0 0 2 229 7 2 3 29 5 0 HALFWORD MATRIX SAVEVALUE LDPBL ROW/COL 1 2 3 1 1012 39 2 2 54 7 0 3 13 0 0 4 7 0 0 5 23 5 0 HALFWORD MATRIX SAVEVALUE PPPBL ROW/COL 1 2 1 240 42 " 3 1 0 Appendix C. Output From Standard Run 1 2 7 HALFWORD MATRIX SAVEVALUE BABPB ROW/COL 1 3 274 4 5 HALFWORD MATRIX SAVEVALUE RFLAG ROW/COL 1 1 734 HALFWORD MATRIX SAVEVALUE CENSU ROW/COL 1 2 3 1 17 1 0 2 25 2 0 3 25 0 0 4 20 1 0 5 13 1 0 6 15 1 0 7 18 0 0 8 23 0 0 9 20 1 0 10 20 1 0 11 24 1 0 12 24 1 0 13 23 1 0 14 26 4 0 15 26 8 0 16 25 14 0 17 25 12 0 18 25 10 0 19 23 6 0 20 21 6 0 21 25 5 0 22 19 2 0 23 19 2 0 24 26 2 0 25 19 2 0 26 20 2 0 27 19 2 0 28 20 1 0 29 16 1 0 30 16 1 0 4 5 6 7 8 3 0 4 75 77 8 0 2 77 80 7 0 2 72 73 9 0 4 75 78 7 0 3 79 80 7 0 2 77 78 6 0 6 73 73 6 0 5 68 68 10 0 2 66 67 10 0 5 76 78 5 0 0 82 85 7 0 4 72 73 6 0 4 73 75 8 0 1 78 83 8 0 5 73 81 8 0 3 68 82 7 0 1 7 1 84 5 0 2 63 74 1 1 0 6 61 67 8 0 4 66 73 3 0 3 70 75 8 0 5 73 75 7 0 2 70 72 6 0 3 69 71 6 0 2 70 73 6 0 5 65 69 9 0 5 63 67 10 0 3 74 75 5 0 2 82 84 8 0 3 79 80 Appendix D The Grace Hospital Simulation Model Code What follows is a complete listing of the G P S S / H program used to model Grace Hospital. 128 Appendix D. The Grace Hospital Simulation Model Code L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1 *T h i s i s a s i m u l a t i o n model of Grace h o s p i t a l i n Vancouver B.C. 2 * c r e a t e d by STEFAN STEINER 1989 3 *The model s t a r t s on a Sunday a t 0 AM. 4 5 6 7 8 9 10 * 11 INITIAL XH7,1 day of month number SIMULATE REALLOCATE FAC,0 , i REALLOCATE LSV, o , : REALLOCATE FUN,25 REALLOCATE STO,25 REALLOCATE VAR,10 7,1 INITIAL XH5,31 INITIAL XB11,1 INITIAL XB12,1 INITIAL X5,1 INITIAL X6,1 INITIAL X4,1 INITIAL X3,1 INITIAL X2,0 12 # days per month 13 send f i r s t mother t o Arbutus 14 send f i r s t baby t o Arbutus 15 5,l count the number of mothers 16 6,l count the number of babies 17 4,l count the number of mothers through PP 18 3,l count the number of mothers through PAR 19 ,0 a r r i v a l time of prev. mother ( f o r d e l i v ) 20 * 21 * space remaining i n the PP modules 22 PPSPA VARIABLE R$ARB+R$BAL+R$CED+R$DOG+R$EVE+R$FIR 23 * 24 *Mothers are re p r e s e n t e d by e n t i t i e s with a f o l l o w i n g parameter 25 *assignment 26 * Parameter # Value 27 * 1 g e o g r a p h i c a l l o c a t i o n of mother's home (1-3) 28 * 2 Ante Partum c o n d i t i o n of mother (1-10) 29 * 3 D e l i v e r y type of mother "(1-6) 30 * 4 Post Partum c o n d i t i o n of mother (1-10) 31 * 5 PP module # to t r a n s f e r to 32 * 6 baby # 1 h e a l t h (1-6) 33 * 7 baby # 2 h e a l t h (1-6) 34 * 8 baby # 3 h e a l t h (1-6) 35 * 9 next t r a n s f e r to t h i s l o c a t i o n (1-20) 36 * 10 p r e s e n t l o c a t i o n (2-14) 37 * 11 d e l i v e r e d (0=no,l=yes) / f i r s t PP mod t r i e d 38 * 12 t o t a l time i n PP s e c t i o n ( i n c l u d i n g PAR,OR) 39 * 13 de l a y d e l i v e r y (# mins) 40 * 14 unique cha i n ID # 41 * 15 l e n g t h of stay i n pre s e n t l o c a t i o n 42 * 16 d i s c h a r g e time from p r e s e n t l o c a t i o n 43 * 44 *Babies are re p r e s e n t e d by e n t i t i e s with the f o l l o w i n g parameter 45 *assignment. 46 * Parameter # Value 47 * 5 PP module to t r a n s f e r to 48 * 6 h e a l t h (1-5) 49 * 9 t r a n s f e r t o t h i s l o c a t i o n next 50 * 10 p r e s e n t l o c a t i o n (1-4) 51 * 13 f i r s t PP module t r i e d 52 * 14 unique c h a i n ID # 53 * 15 le n g t h of stay i n p r e s e n t l o c a t i o n 54 * 16 d i s c h a r g e time from p r e s e n t l o c a t i o n 55 * 56 GENERATE (XH5*1440),1,,,,16,F 57 ASSIGN 1,1 58 CL TEST LE P1,XH5,NT c l e a r s torage Appendix D. The Grace Hospital Simulation Model Code 130 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 59 MSAVEVALUE ARRIV,P1,1,0 ,H 60 MSAVEVALUE ARRIV,P1,2,0,H 61 ASSIGN 62 TRANSFER ,CL 63 NT ASSIGN 1,FN70 # mothers i n t h i s month 64 ASSIGN 2,PI 65 LOP TRANSFER .073,,SPEC 7.3% are DOS mothers 66 * spont/inst/elC/emC p a t i e n t s 67 REGP ASSIGN 3,FN73 day i n month 68 TEST LE P3,XH5,REGP 69 MSAVEVALUE ARRIV+,P3,1, 1,H 70 TRANSFER ,LOPl 71 * DOS p a t i e n t s 72 SPEC ASSIGN 3,FN73 day i n month 73 TEST LE P3,XH5,SPEC r e t u r n i n v a l i d day #s 74 ASSIGN 16,P3+(AC1/1440) 75 ASSIGN 16,P16-(P16/7)*7 normalize t o day of wee 76 DCT TEST NE P16,0,SPEC no a r r i v a l s on Saturday 77 TEST G P16,1,FS Sunday 78 TEST G P16,5,MT mon/tues/wed/thur 79 TEST G P16,6,FS f r i d a y 80 TRANSFER , SPEC no a r r i v a l s on Saturday 81 FS TRANSFER .85,TIM,SPEC r e t u r n 85% friday&sunday 82 MT TRANSFER .15,,SPEC r e t u r n 15% monday-thurs 83 TIM MSAVEVALUE ARRIV+,P3,2, 1,H s p e c i a l time a r r i v a l s 84 LOP1 LOOP l,LOP 85 * 86 ASSIGN 1,1 1st day i n month 87 LOP2 TEST LE PI,XH5,TER loop through a l l the days 88 ASSIGN 3,MH$ARRIV(P1,1) r e c o r d # mothers t o a r r i 89 LOP3 TEST G P3,0,PDOS 90 SPLIT 1,DELTP 91 ASSIGN 3 - , l 92 TRANSFER ,LOP3 93 * 94 PDOS ASSIGN 3,MH$ARRIV(P1,2) move DOS p a t i e n t s now 95 LOP4 TEST G P3,0,NDAY 96 SPLIT 1,DAYOS 97 ASSIGN 3 - , l 98 TRANSFER ,LOP4 99 NDAY ADVANCE 1440 wait u n t i l next day 100 ASSIGN 1 + ,1 increment day counter 101 TRANSFER ,LOP2 102 TER TERMINATE 0 103 DELTP ADVANCE FN72 wait to en t e r h o s p i t a l 104 MARK 105 PRIORITY 2 106 TRANSFER FN, 71 send to r i g h t d e l i v e r y type 107 * 108 * c r e a t e e n t i t i e s (mothers) t o have a Spontaneous b i r t h s 109 • a s s i g n e n t i t y : g e o g r a p h i c a l l o c a t i o n , antepartum category, 110 *and a d e l i v e r y type 111 SPONT ASSIGN 1,FN81 c a l c geog. l o c a t i o n 112 ASSIGN 2,FN*P1 c a l c AP category 113 ASSIGN 3,1 s t o r e d e l i v e r y type 114 TRANSFER ,CRMOM 115 *c r e a t e e n t i t i e s (mothers) t o have an i n s t r u m e n t a l b i r t h 116 INST ASSIGN 1,FN82 geog. l o c a t i o n Appendix D. The Grace Hospital Simulation Model Code 131 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 117 SAVEVALUE 10,3,XH use XH10 as a temp v a r i a b l e 118 SAVEVALUE 10+,P1,XH 119 ASSIGN 2,FN*XH10 AP category 120 ASSIGN 3,2 d e l i v e r y type 121 TRANSFER ,CRMOM 122 * 123 " c r e a t e e n t i t i e s (mothers) t o have an E l e c t i v e C - s e c t i o n 124 " r e g u l a r a r r i v a l 125 ELC ASSIGN 1,FN83 geog. l o c a t i o n 126 SAVEVALUE 10,10,XH use XH10 as a temp v a r i a b l e 127 SAVEVALUE 10+,P1,XH 128 ASSIGN 2,FN*XH10 AP category 129 ASSIGN 3,3 d e l i v e r y type 130 TRANSFER ,CRMOM 131 * 132 DAY VARIABLE AC1-(AC1/1440)"1440 time of day i n minutes 133 WEEK VARIABLE AC1/1440-AC1/10080*7+1 day of week (l=sunday) 134 * 135 " c r e a t e e n t i t i e s (mothers) t o have an E l e c t i v e C - s e c t i o n 136 "day of surgery a r r i v a l 137 138 DAYOS TRANSFER .873,,SIX14 87% between 6 and 14 o'clock 139 ASSIGN 15,FN76 between 15-20 140 TRANSFER ,DTEST 141 SIX14 ASSIGN 15,FN77 between 6-14 142 DTEST ADVANCE P15 wait to enter h o s p i t a l 143 MARK enter the h o s p i t a l 144 PRIORITY 2 145 ASSIGN 16,V$DAY 146 TABULATE ATIME 147 ASSIGN 1,FN83 geog. l o c a t i o n 148 SAVEVALUE 10,10,XH use XH10 as a temp v a r i a b l e 149 SAVEVALUE 10+,P1,XH 150 ASSIGN 2,FN*XH10 AP category 151 ASSIGN 3,9 d e l i v e r y type 152 TRANSFER ,CRMOM 153 " c r e a t e e n t i t i e s (mothers) t o have an Emergency C - s e c t i o n 154 EMC ASSIGN 1,FN84 geog. l o c a t i o n 155 SAVEVALUE 10,13,XH use XH10 as a temp v a r i a b l e 156 SAVEVALUE 10+,P1,XH 157 ASSIGN 2,FN*XH10 AP category 158 ASSIGN 3,4 d e l i v e r y type 159 TRANSFER ,CRMOM 160 161 " a r r i v a l of p a t i e n t s f o r the v a r i o u s d e l i v e r y types 162 "EXPONENTIAL DISTRIBUTION! 163 EXPO FUNCTION RN252,C24 164 0,0/0.1,0.104/0.2,0.222/0.3,0.355/0.4,0.509/0.5,0.690/0.6,0.915/ 165 0.7,1.20/0.75,1.38/0.80,1.60/0.84,1.83/0.88,2.12/0.90,2.30/ 166 0.92,2.52/0.94,2.81/0.95,2.99/0.96,3.2/0.97,3.5/0.98,3.9/ 167 0.99,4.6/0.995,5.3/0.998,6.2/0.999,7.0/0.9997,8 168 * 169 " c r e a t e e n t i t i e s (mothers) a r r i v i n g j u s t f o r a Postpartum c o n d i t i o n 170 GENERATE 4051,FN$EXPO,,,2,16,F 171 ASSIGN 1,FN85 geog. l o c a t i o n 172 ASSIGN 2,1 AP category i s none 173 ASSIGN 3,5 d e l i v e r y type 174 TRANSFER ,CRMOM Appendix D. The Grace Hospital Simulation Model Code 132 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 175 * c r e a t e e n t i t i e s (mothers) a r r i v i n g j u s t f o r an Antepartum c o n d i t i o n 176 GENERATE 446,FN$EXPO,,,2,16,F 177 ASSIGN 1,FN86 geog. l o c a t i o n 178 SAVEVALUE 10,23,XH use XH10 as a temp v a r i a b l e 179 SAVEVALUE 10+,P1,XH 180 ASSIGN 2,FN*XH10 AP category 181 ASSIGN 3,6 d e l i v e r y type 182 TRANSFER ,CRMOM 183 " c r e a t e p e d i a t r i c babies a r r i v i n g 184 GENERATE 3882,FN$EXPO,,,2,16,F 185 ASSIGN 6,5 mark p e d i a t r i c baby 186 ASSIGN 13,0 no delay i n e n t r y to system 187 MSAVEVALUE CLASS+,6,P6,1 s t o r e p e d i a t r i c baby a r r i v a l 188 TRANSFER ,ADMB 189 190 " a s s i g n the r e s t of the parameters f o r mothers 191 192 CRMOM SAVEVALUE 10,P3,XH 193 TEST E P3,9,CRMCT i f mother DOS 194 SAVEVALUE 10,3,XH use ElecC f o r c l a s s i f i c a t i o n 195 CRMCT SAVEVALUE 10+,30,XH 196 ASSIGN 4,FN*XH10 a s s i g n PP category 197 ASSIGN 14,X5 a s s i g n unique Xact # 198 SAVEVALUE 5+,l,X increment mother count 199 ASSIGN 6,6 assume no baby 200 ASSIGN 7,6 and no twin 201 ASSIGN 8,6 or t r i p l e t 202 ASSIGN 11,1 assume mother not to d e l i v e r 203 TEST NE P3,5,C0NT1 204 TEST NE P3,6,C0NT1 i f u n d e l i v e r e d or PPonly 205 * a s s i g n babies t o mothers s k i p the next p a r t 206 ASSIGN 11,0 mother w i l l d e l i v e r 207 SAVEVALUE 10,50,XH 208 SAVEVALUE 10+,P2,XH depends on AP category 209 ASSIGN 6,FN*XH10 babies 210 TEST E P2,8,C0NT1 i f i n other AP category 211 TRANSFER .003,,TRIP chance of a t r i p l e t 212 TRANSFER .081,CONTl,TWIN chance of a twin 213 TRIP ASSIGN 8,FN60 a s s i g n t r i p l e t h e a l t h 214 TWIN ASSIGN 7,FN60 a s s i g n twin h e a l t h 215 *save a l l the c l a s s i f i c a t i o n 216 CONTl MSAVEVALUE CLASS+,1,PI,1 217 MSAVEVALUE CLASS+,2,P2,1 218 MSAVEVALUE CLASS+,3,P3,1 219 MSAVEVALUE CLASS+,4,P4,1 220 MSAVEVALUE CLASS+,6,P6,1 221 MSAVEVALUE CLASS+,7,P7,1 222 MSAVEVALUE CLASS+,8,P8,1 223 TRANSFER ,ADM 224 * 225 "generate a l l the bab i e s born 226 CRBAB TEST NE P6,6,COUT check i f baby should be born 227 SPLIT 1,ADMB 228 TEST NE P7,6,COUT check i f twin should be born 229 SPLIT 1,SBABY 230 TEST NE P8,6,COUT check i f t r i p l e t should be born 231 SPLIT 1,TBABY 232 COUT TERMINATE 0 remove copy used to generate babies Appendix D. The Grace Hospital Simulation Model Code 133 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 233 SBABY ASSIGN 6,P7 second baby (twin) 234 TRANSFER ,ADMB 235 TBABY ASSIGN 6,P8 t h i r d baby ( t r i p l e t ) 236 TRANSFER ,ADMB 237 * 238 239 * ADMISSION TO HOSPITAL 240 * 241 * 242 *use AP cat e g o r y t o c o n t r o l i n i t i a l admission i n t o h o s p i t a l 243 *u n l e s s mother i s a Post Partum only p a t i e n t 244 ADM SAVEVALUE 10,100,XH 245 ASSIGN 10,1 from admit 246 TEST NE P3,5,PPOIN i f PPonly s k i p 247 , TEST NE P3,6,ADM2 admission depends on d e l i v e r y yes/nc 248 MSAVEVALUE DISCH+,1,1,1 249 TEST NE P3,9,DELIV i f DOS s k i p 250 * To d e l i v e r y mothers 251 ASSIGN 16,AC1-X2 f i n d i n t e r a r r i v a l time 252 TABULATE ARATE 253 SAVEVALUE 2,AC1,X s t o r e l a s t a r r i v a l time 254 ASSIGN 16,V$DAY a r r i v a l time of day 255 TABULATE ATIM2 256 SAVEVALUE 10+,70,XH f o r d e l i v e r i e s 257 SAVEVALUE 10+,P2,XH t r a n s f e r depends on AP c a t . 258 ASSIGN 9,FN*XH10 t r a n s f e r t o ... 259 TRANSFER FN,100 260 * U n d e l i v e r e d mothers 261 ADM2 MSAVEVALUE DISCH+,1,2,1 262 - SAVEVALUE 10+,P2,XH depends on AP category (Undel) 263 ASSIGN 9,FN*XH10 t r a n s f e r t o where? 264 TRANSFER FN,100 265 * 266 PPOIN MSAVEVALUE DISCH+,1,2,1 267 SAVEVALUE 10+,9,XH PP only admissions 268 ASSIGN 9,FN*XH10 t r a n s f e r l o c a t i o n i n para #9 269 TRANSFER FN,100 270 * 271 *admission of a l l babies 272 ADMB MSAVEVALUE DISCH+,1,3,1 273 SAVEVALUE 1,500,XH 274 SAVEVALUE 1+,P6,XH t r a n s f e r depends on babies h e a l t h 275 ASSIGN 9,FN*XH1 t r a n s f e r to ... 276 ASSIGN 10,1 from admit 277 ASSIGN 14,X6 a s s i g n unique baby number 278 SAVEVALUE 6+,l,X increment counter 279 ADVANCE P13 de l a y i f necessary 280 MARK en t e r the h o s p i t a l 281 TRANSFER FN,96 282 * 2 3 3 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 284 *============================================================= 285 *======= THE HOSPITAL ======== 286 *============================================================= 287 * 288 * 289 * 290 *ANTE PARTUM s u b s e c t i o n * Appendix D. The Grace Hospital Simulation Model Code 134 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 291 292 * 293 *AP module s e c t i o n ( H o l l y and Dogwood) 294 AP MSAVEVALUE TRANS+,PI0,3,1 t r a n s f e r t a b l e 295 MSAVEVALUE TRANS+,P10,16,1 t o t a l row 296 MSAVEVALUE TRANS+,16,3,1 t o t a l column 297 SAVEVALUE 1,110,XH 298 SAVEVALUE 1+,P2,XH t r a n s f e r depend on AP category 299 TEST LE P3,4,APUND and whether mother w i l l d e l i v e r 300 SAVEVALUE 1+,50,XH w i l l d e l i v e r 301 APUND ASSIGN 9,FN*XH1 t r a n s f e r to ... 302 TEST E P9,19,APMOV i f t r a n s f e r to Labour and D e l i v e r y 303 SAVEVALUE 1,250,XH then 304 SAVEVALUE 1+,P3,XH t r a n s f e r depends on d e l i v e r y type 305 ASSIGN 9,FN*XH1 t r a n s f e r to ... 306 APMOV PRIORITY 2 307 SAVEVALUE 2,1110,XH 308 SAVEVALUE 2+,P2,XH length of stay f u n c t i o n # 309 TEST LE P3,4,APUNE LOS depends on d e l / u n d e l 310 SAVEVALUE 2+,50,XH d e l i v e r y 311 APUNE ASSIGN 15,FN*XH2 a s s i g n l e n g t h of stay 312 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 313 APEX ASSIGN 10,3 mark i n AP 314 QUEUE APQ 315 HOLLY GATE SNF HOLLY,APDOG i f H o l l y f u l l go t o Dogwood 316 ENTER HOLLY e l s e take a bed i n H o l l y 317 DEPART APQ 318 ADVANCE P15 stay p r e s c r i b e d amount of time 319 TEST NE P9,10,HOR check i f t r a n s f e r to OR 320 TEST NE P9,6,HOR2 i f to AP OR check i f OR i s f r e e 321 TRANSFER , HOLL 322 HOR TEST NE P3,4,HOLL i f emergency t r a n s f e r immediately 323 HOR2 QUEUE ORWAI 324 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 325 DEPART ORWAI 326 HOLL LEAVE HOLLY 327 TRANSFER ,APCT 328 APDOG GATE SNF DOG,APDPR i f Dogwood f u l l go to problem 329 QUEUE APDGN c o l l e c t s t a t s f o r AP i n DOG 330 QUEUE PPMOD c o l l e c t s t a t s on PP module use 331 ENTER DOG e l s e take bed i n Dogwood 332 DEPART APQ 333 PRIORITY 2 334 ADVANCE PI 5 sta y p r e s c r i b e d amount of time 335 TEST NE P9,10,DOR 336 TEST NE P9,6,DOR2 i f t r a n s f e r to OR check OR f i r s t 337 TRANSFER , DOGL 338 DOR TEST NE P3,4,DOGL i f emergency t r a n s f e r immediately 339 DOR2 QUEUE ORWAI 340 TEST G R$OR,l i f <= 1 OR l e f t d e l a y t r a n s f e r 341 DEPART ORWAI 342 DOGL LEAVE DOG 343 DEPART APDGN 344 DEPART PPMOD 345 TRANSFER ,APCT 346 APDPR TEST G CH$DOGUC,0,APEVE i f Dogwood f u l l , but PP p a t i e n t s 347 UNLINK DOGUCD20UT, 1 i n Dogwood. Move a PP p a t i e n t to 348 BUFFER Appendix D. The Grace Hospital Simulation Model Code 1 3 5 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 349 MSAVEVALUE APPBL+,1,1,1,H another PP module and r e c o r d 350 PRIORITY 5 make sure i t gets p l a c e i n DOG 351 TRANSFER ,APDOG event 352 APEVE GATE SNF EVE,APEPR i f HOL DOG f u l l of AP t r y EVE 353 QUEUE APDGN c o l l e c t s t a t s f o r AP i n EVE 354 QUEUE APEVN 355 QUEUE PPMOD 356 ENTER EVE e l s e take bed i n Dogwood 357 DEPART APQ' 358 PRIORITY 2 359 ADVANCE P15 stay p r e s c r i b e d amount of time 360 TEST NE P9,10,EOR 361 TEST NE P9,6,EOR i f t r a n s f e r to OR check OR f i r s t 362 TRANSFER ,AEVEL 363 EOR TEST NE P3,4,AEVEL i f emergency t r a n s f e r immediately 364 QUEUE ORWAI 365 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 366 DEPART ORWAI 367 AEVEL LEAVE EVE 368 DEPART APDGN 369 DEPART APEVN 370 DEPART PPMOD 371 TRANSFER ,APCT 372 APEPR TEST G CH$EVEUC,0,APPB i f EVE f u l l , but PP p a t i e n t s 373 UNLINK EVEUC,E20UT,1 i n EVE. Move a PP p a t i e n t to 374 BUFFER 375 MSAVEVALUE APPBL+,1,2,1,H another PP module and r e c o r d 376 PRIORITY 5 make sure i t gets p l a c e i n EVE 377 TRANSFER ,APEVE 378 APPB MSAVEVALUE APPBL+,1,3,1,H i f both H o l l y and Dogwood f u l l 379 ADVANCE P15 of AP p a t i e n t s r e c o r d problem 380 DEPART APQ 381 APCT TEST E P11,2,APCT2 382 TABULATE STILZ s t i l l b i r t h time i n AP 383 TRANSFER ,APOUT 384 APCT2 TABULATE AP2 385 TEST LE P3,4,APUN 386 MSAVEVALUE APNUM+,1,P2,1 387 MSAVEVALUE APNUM+,1,9,1 d e l i v e r y p a t i e n t i n AP 388 TRANSFER ,APOUT 389 A PUN MSAVEVALUE APNUM+,2,P2,1 390 MSAVEVALUE APNUM+,2,9,1 undel p a t i e n t i n AP 391 APOUT TRANSFER FN,100 t r a n s f e r t o next p l a c e 392 * 393 * APLOW s u b s e c t i o n 394 APLOW MSAVEVALUE TRANS+,P10,4,1 t r a n s f e r t a b l e 395 MSAVEVALUE TRANS+,P10,16,1 t o t a l row 396 MSAVEVALUE TRANS+,16,4,1 t o t a l column 397 SAVEVALUE 1,120,XH 398 SAVEVALUE 1+,P2,XH t r a n s f e r depends on AP category 399 ASSIGN 9,FN*XH1 t r a n s f e r to ... i n para 9 400 SAVEVALUE 2,1120,XH 401 SAVEVALUE 2+,P2,XH LOS f u n c t i o n # 402 ASSIGN 15,FN*XH2 a s s i g n l e n g t h of s t a y 403 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 404 PRIORITY 2 405 APLT ASSIGN 10,4 mark i n APLOW 406 QUEUE APLQ Appendix D. The Grace Hospital Simulation Model Code 1 3 6 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 407 GATE SNF LOW,APASS i f LOW f u l l stay temp, i n ASESS 408 APL ENTER LOW 409 DEPART APLQ 410 ASSIGN 14,CC$LOWUC s t o r e user c h a i n unique number 411 SPLIT 1,APLTI c r e a t e copy to time LOS 412 PRIORITY 5 413 LINK LOWUC,16 sta y on l i n k u n t i l t i mer up 414 APLF TEST E P9,6,APLL i f t r a n s f e r t o OR check OR f i r s t 415 TEST LE P16,AC1,APLL i f k i c k e d out t r a n s f e r now 416 QUEUE ORWAI 417 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 418 DEPART ORWAI 419 APLL LEAVE LOW 420 TRANSFER ,APLCT 421 APLTI ADVANCE P15 run timer 422 UNLINK LOWUC,LUOUT,1 ,14PF,P14 u n l i n k i f Xact # match 423 TERMINATE 0 stop copy 424 APASS GATE SNF ASESS,APLPA i f assessment rooms f u l l goto PAR 425 ENTER ASESS e l s e take an assessment room 426 DEPART APLQ 427 MSAVEVALUE APPBL+,2,1,1, H r e c o r d event 428 ASSIGN 14,CC$ASSUC s t o r e user c h a i n unique number 429 SPLIT 1,APSTI c r e a t e copy to time LOS 430 PRIORITY 5 431 LINK ASSUC,16 st a y on c h a i n u n t i l time up 432 APASU LEAVE ASESS or a bed i n LOW becomes f r e e 433 PRIORITY 2 434 TEST G P16,AC1,APSCT i f s t i l l have time i n LOW 435 ASSIGN 15,P16-AC1 time l e f t i n LOW 436 QUEUE APLQ 437 GATE SNF LOW,APLPB t r y to take a bed i n LOW 438 TRANSFER ,APL 439 APSCT TRANSFER FN,100 t r a n s f e r t o next l o c a t i o n 440 APSTI PRIORITY 10 timer 441 SPLIT 1,APST2 c r e a t e second timer t o watch LOW 442 ADVANCE P15 e i t h e r spend a l l time 443 UNLINK ASSUC,AUOUT,1 ,14PF,P14 i n assessment or 444 TERMINATE 0 445 APST2 PRIORITY 0 446 GATE SNF LOW t r a n s f e r t o low r i s k 447 PRIORITY 10 448 UNLINK ASSUC,AUOUT,1 ,14PF,P14 when f r e e 449 TERMINATE 0 450 APLPA GATE SNF PAR,APLPB i f PAR a l s o f u l l go t o problem 451 ENTER PAR 452 DEPART APLQ 453 MSAVEVALUE APPBL+,2,2,1, H 454 ASSIGN 14,X3 455 SAVEVALUE 3+,l,X 456 SPLIT 1,APLTM 457 PRIORITY 5 458 LINK LPUC,16 459 APLOT LEAVE PAR 460 TEST G P16,AC1,APLPT 461 PRIORITY 1 462 ASSIGN 15,P16-AC1 time l e f t f o r LOW 463 QUEUE APLQ 464 GATE SNF LOW,APLPB Appendix D. The Grace Hospital Simulation Model Code 1 3 7 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 TRANSFER APLTM PRIORITY SPLIT SPLIT LINK APLP1 UNLINK TERMINATE APLT2 PRIORITY GATE SNF UNLINK TERMINATE APLPT TRANSFER APLPB MSAVEVALUE UNLINK BUFFER TRANSFER APLCT PRIORITY TABULATE TRANSFER ,APL 10 1,PARTI 1,APLT2 PARUC,16 LPUC, LROUT, 1,14PF, PI 4 0 0 LOW LPUC,LROUT,1,14PF,PI 4 0 FN,100 APPBL+,2,3,1,H LOWUC,LUOUT,1 ,APL 2 LOWZ FN,100 r e c o r d t h i s problem remove next t o leave from storage k APHIGH SUBSECTI APHIG MSAVEVALUE MSAVEVALUE MSAVEVALUE SAVEVALUE SAVEVALUE ASSIGN SAVEVALUE SAVEVALUE ASSIGN ASSIGN PRIORITY APHT ASSIGN QUEUE GATE SNF APH ENTER DEPART ASSIGN SPLIT PRIORITY LINK APHF TEST E TEST LE QUEUE TEST G DEPART APHL LEAVE PRIORITY TABULATE TRANSFER APHTI PRIORITY ADVANCE UNLINK TERMINATE APHPB GATE SNF DEPART MSAVEVALUE ON TRANS+,PI0,5,1 t r a n s f e r t a b l e TRANS+,PI0,16,1 t o t a l row TRANS+,16,5,1 t o t a l column 1,130,XH 1+,P2,XH 9,FN*XH1 2,1130,XH 2+,P2,XH 15, FN*XH2 16, P15+AC1 2 10,5 APHQ HIGH,APHPB HIGH APHQ 14,CC$HIGUC 1,APHTI 5 HIGUC,16 P9,6,APHL P16,AC1,APHL ORWAI R$OR,1 ORWAI HIGH 2 HIGHZ FN,100 10 P15 HIGUC,HUOUT,l,14PF,P14 0 LOW,APHP2 i f HIGH f u l l t r y LOW APHQ APPBL+,3,1,1,H r e c o r d i f s u c c e s s f u l i n t o LOW t r a n s f e r depends on AP category t r a n s f e r to ... len g t h of stay d i s c h a r g e time mark i n APHIGH i f HIGH f u l l goto problem e l s e take room i n HIGH r i s k s t o r e user c h a i n unique number c r e a t e timer l i n k by d i s c h a r g e time i f t r a n s f e r to OR check OR f i r s t i f <= 1 OR l e f t d e l a y t r a n s f e r t imer wait p r e s c r i b e d l e n g t h of time then move Xact to next p i ; Appendix D. The Grace Hospital Simulation Model Code 1 3 8 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 523 TRANSFER , APLT 524 APHP2 GATE SNF ASESS,APHP3 i f LOW f u l l check ASESS 525 DEPART APHQ 526 MSAVEVALUE APPBL+,3,2,1,H r e c o r d i f s u c c e s s f u l i n t o LOW 527 TRANSFER , APLT 528 APHP3 MSAVEVALUE APPBL+,3,3,1,H i f HIGH and LOW f u l l 529 UNLINK HIGUCHUOUT, 1 remove someone f o r high r i s k 530 BUFFER 531 TRANSFER ,APH and r e c o r d event 532 * 533 * ANTE PARTUM OPERATING ROOM & 534 * ANTE PARTUM POST ANAESTHETIC RECOVERY s u b s e c t i o n 535 APOR MSAVEVALUE TRANS+,PI 0,6,1 t r a n s f e r t a b l e 536 MSAVEVALUE TRANS+,P10,16, 1 t o t a l row 537 MSAVEVALUE TRANS+,16,6,1 t o t a l column 538 QUEUE APORQ 539 ASSIGN 15,FN1140 a s s i g n l e n g t h of stay 540 ASSIGN 16,P15+AC1 c a l c u l a t e d i s c h a r g e time 541 ASSIGN 10,6 now i n AP OR 542 PRIORITY 2 543 MSAVEVALUE ORCAT+,P3,1,1 544 GATE SNF OR,APOPB i s the OR f r e e ? 545 ENTER OR i f yes, move to OR 546 DEPART APORQ 547 ADVANCE P15 s t a y i n OR p r e s c r i b e d time 548 LEAVE OR 549 TRANSFER ,APOCT t r a n s f e r t o next l o c a t i o n 550 APOPB MSAVEVALUE APPBL+,4,1,1,H i f no, r e c o r d problem 551 ADVANCE P15 552 DEPART APORQ 553 APOCT TABULATE ORZ 554 *move t o the PAR immediately 555 556 APPAR MSAVEVALUE TRANS+,P10,7,1 t r a n s f e r t a b l e 557 MSAVEVALUE TRANS+,P10,16, 1 t o t a l row 558 MSAVEVALUE TRANS+,16,7,1 t o t a l column 559 ASSIGN 9,FN150 t r a n s f e r t o ... (independent of < 560 ASSIGN 15,FN1150 a s s i g n l e n g t h of stay 561 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 562 ASSIGN 10,7 mark i n AP PAR 563 QUEUE APPAQ 564 GATE SNF PAR,APPPB i f PAR f u l l goto problem 565 APPIN ENTER PAR e l s e take bed i n PAR 566 DEPART APPAQ 567 ASSIGN 14,X3 s t o r e user c h a i n unique numbe: 568 SAVEVALUE 3+,l,X 569 SPLIT 1,APPTI c r e a t e copy t o time LOS 570 PRIORITY 5 571 LINK PARUC,16 wait i n c h a i n u n t i l removed 572 APPF LEAVE PAR by timer or another mother 573 PRIORITY 2 who needs PAR 574 ASSIGN 15-,P16-AC1 575 TABULATE PARZ 576 TRANSFER FN,100 577 APPTI PRIORITY 10 timer 578 ADVANCE P15 wait p r e s c r i b e d length of time 579 UNLINK PARUC,RUOUT,1, 14PF,P14 remove mother from wait 580 TERMINATE 0 stop copy Appendix D. The Grace Hospital Simulation Model Code 1 3 9 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 581 APPPB GATE SNF HIGH,APPP2 i f PAR f u l l t r y HIGH r i s k 582 DEPART APPAQ 583 MSAVEVALUE APPBL+,5,1,1, H 584 TRANSFER , APHT 585 APPP2 MSAVEVALUE APPBL+,5,2,1, H i f PAR and HIGH r i s k f u l l 586 UNLINK PARUCRUOUT, 1 remove someone from the PAR 587 BUFFER 588 TRANSFER ,APPIN 589 * 590 591 "DELIVERY SUITE * 592 593 " e n t r y p o i n t f o r a l l t r a n s a c t i o n s go t o D e l i v e r y s u i t e . 594 " C o n t r o l f o r where t r a n s a c t i o n i s sent i s taken over by 595 "the t r a n s a c t i o n ' s a s s i g n e d d e l i v e r y type 596 * 597 "mothers coming d i r e c t l y from a d m i t t i n g 598 DELIV SAVEVALUE 1,260,XH 599 SAVEVALUE 1+,P3,XH 600 ASSIGN 9,FN*XH1 t r a n s f e r t o ... 601 TRANSFER FN,100 602 * 603 "LOW Sub s e c t i o n 604 LOW MSAVEVALUE TRANS+,P10,8, 1 t r a n s f e r t a b l e 605 MSAVEVALUE TRANS+,P10,16,1 t o t a l row 606 MSAVEVALUE TRANS+,16,8,1 t o t a l column 607 TEST E P10,8,LOWA 608 ASSIGN 10,8 609 LOWA SAVEVALUE 1,200,XH 610 SAVEVALUE 1+,P3,XH 611 ASSIGN 9,FN*XH1 s t o r e next t r a n s f e r 612 TEST NE P3,3,LOWG i f p a t i e n t i n f o r C - s e c t i o n 613 TEST NE P3,4,LOWG 614 TEST NE P3,9,LOWG 615 TRANSFER ,LOWH 616 LOWG TEST E P9,12,LOWH then do not t r a n s f e r to PP 617 TEST E PI1,1,LOWA i f not d e l i v e r e d 618 LOWH SAVEVALUE 2,1200,XH len g t h of stay 619 SAVEVALUE 2+,P3,XH depends on d e l i v e r y type 620 ASSIGN 15,FN*XH2 s t o r e l e n g t h of st a y 621 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 622 PRIORITY 2 623 LOWT ASSIGN 10,8 mark i n LOW 624 QUEUE LOWQ 625 GATE SNF LOW,ASESS i f LOW f u l l go temp, to ASESS 626 LOW IN ENTER LOW e l s e take a room i n LOW r i s k 627 DEPART LOWQ p a t i e n t i n low r i s k now 628 TEST E P9,12,LOWC i f next t r a n s f e r to PP generati 629 TEST E P11,0,LOWC and b a b i e s not y e t d e l i v e r e d 630 ASSIGN 11,1 d e l i v e r b a b i e s 631 ASSIGN 13,0 assume no delay t i l l babies 632 TEST G P15,180,LOWB 633 ASSIGN 13,P15-180 d e l a y baby's d e l i v e r y 634 LOWB TEST E P3,l,LOWD of the spont d e l i v e r i e s 635 TRANSFER .018,,LSTIL 1.8% d e l i v e r i e s are s t i l l b i r t h 636 LOWD SPLIT 1,CRBAB send copy t o generate babies 637 MSAVEVALUE BDEL+,1,1,1 638 LOWMA SAVEVALUE 10,V$DAY,XH s t o r e d e l i v e r y time of day Appendix D. The Grace Hospital Simulation Model Code 1 4 0 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 639 TABULATE DL 640 TABULATE DELAP s t o r e time i n h o s p i t a l b efore 641 MARK get time a f t e r d e l i v e r y 642 LOWC ASSIGN 14,CC$LOWUC s t o r e user c h a i n unique number 643 SPLIT 1,LOWTI send copy t o time LOS i n LOW 644 PRIORITY 5 645 LINK LOWUC,16 j o i n c h a i n of mothers i n LOW 646 LOWF TEST E P9,10,LOWL i f t r a n s f e r t o OR check OR f i r s t 647 TEST NE P3,4,LOWL t r a n s f e r i f emergency 648 TEST LE PI 6,ACl,LOWL t r a n s f e r i f bumped out e a r l y 649 QUEUE ORWAI 650 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 651 DEPART ORWAI 652 LOWL LEAVE LOW 653 PRIORITY 2 654 TABULATE LOW2 655 LOWLL TRANSFER FN,100 t r a n s f e r t o next l o c a t i o n 656 LSTIL ASSIGN 9,18 send to AP i n s t e a d of PP 657 ASSIGN 11,2 mark s t i l l b i r t h 658 TRANSFER ,LOWMA 659 LOWTI PRIORITY 10 timer 660 ADVANCE P15 wait p r e s c r i b e d time 661 UNLINK LOWUC,LUOUT,1,14PF,P14 then remove mother from cha 662 TERMINATE 0 stop copy 663 ASESS GATE SNF ASESS,LOWPA i f ASESS f u l l go t o PAR 664 ENTER ASESS e l s e take room i n ASESS 665 DEPART LOWQ 666 MSAVEVALUE LDPBL+,1,1,1,H r e c o r d event 667 ASSIGN 14,CC$ASSUC s t o r e user c h a i n unique number 668 SPLIT 1,ASSTI c r e a t e copy t o time LOS 669 PRIORITY 5 670 LINK ASSUC,16 j o i n c h a i n of mothers i n ASESS 671 ASSU LEAVE ASESS 672 PRIORITY 2 673 TEST G P16,AC1,BABCH check i f removed be f o r e time up 674 ASSIGN 15,P16-AC1 time l e f t f o r LOW, i f yes 675 QUEUE LOWQ 676 GATE SNF LOW,LOWPA t r y t o enter LOW now 677 TRANSFER ,LOWIN 678 * i f no, assessment room check t o see i f mother needs to d e l i v e r 679 BABCH ASSIGN 13,0 assume no delay i n b i r t h 680 TEST E P9,12,BABOT i s t r a n s f e r t o PP 681 TEST E PI1,0,BABOT and mother i s u n d e l i v e r e d 682 ASSIGN 11,0 then mother w i l l now d e l i v e r y 683 TEST E P3,1,BABD of the spont d e l i v e r i e s 684 TRANSFER .018,,ASTIL 1.8% d e l i v e r i e s are s t i l l b i r t h s 685 BABD SPLIT 1,CRBAB send copy to generate babies 686 MSAVEVALUE BDEL+,2,1,1 687 BABTB TABULATE DELAP s t o r e time b e f o r e 688 MARK get time a f t e r d e l i v e r y 689 BABOT TRANSFER FN,100 r e t u r n t o normal flow 690 ASTIL ASSIGN 9,18 send t o AP i n s t e a d of PP 691 ASSIGN 11,2 mark s t i l l b i r t h 692. TRANSFER ,BABTB 693 ASSTI PRIORITY 10 timer 694 SPLIT 1,ASST2 c r e a t e second timer t o watch LOW 695 ADVANCE P15 wait p r e s c r i b e d time 696 UNLINK ASSUC,AUOUT,1,14PF,P14 r e l e a s e mother from c h a i n Appendix D. The Grace Hospital Simulation Model Code 141 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 697 TERMINATE 0 stop copy 698 ASST2 PRIORITY 0 t h i s t imer waits u n t i l there i s 699 GATE SNF LOW space i n LOW risk. 700 PRIORITY 10 701 UNLINK ASSUC,AUOUT,l,14PF,P14 and then r e l e a s e s mother 702 TERMINATE 0 stop copy 703 LOWPA GATE SNF PAR,LOWPB i f PAR a l s o f u l l go to problem 704 ENTER PAR 705 DEPART LOWQ 706 MSAVEVALUE LDPBL+,1,2,1,H 707 ASSIGN 14,X3 708 SAVEVALUE 3+,l,X 709 SPLIT 1,LPTIM 710 PRIORITY 5 711 LINK LPUC,16 712 LPOUT LEAVE PAR 713 PRIORITY 1 714 TEST G P16,AC1,BABCH 715 ASSIGN 15,P16-AC1 time l e f t f o r LOW 716 QUEUE LOWQ 717 GATE SNF LOW,LOWPB 718 TRANSFER ,LOWIN 719 LPTIM PRIORITY 10 720 SPLIT 1,PARTI 721 SPLIT 1,LPTI2 722 LINK PARUC,16 723 LP1 UNLINK LPUCLROUT, 1, 14PF,P14 724 TERMINATE 0 725 LPTI2 PRIORITY 0 726 GATE SNF LOW 727 UNLINK LPUCLROUT, 1,14PF,P14 728 TERMINATE 0 729 LOWPB MSAVEVALUE LDPBL+,1,3,1,H both LOW and ASESS are f u l l 730 UNLINK LOWUC,LUOUT,1 r e c o r d problem, and k i c k 731 BUFFER 732 TRANSFER ,LOWIN someone out of LOW 733 * 734 *HIGH s u b s e c t i o n 735 HIGH MSAVEVALUE TRANS+,P10,9,1 t r a n s f e r t a b l e 736 MSAVEVALUE TRANS+,P10,16,1 t o t a l row 737 MSAVEVALUE TRANS+,16,9,1 t o t a l column 738 TEST E P10,9,HIGA 739 ASSIGN 10,9 740 HIGA SAVEVALUE 1,210,XH t r a n s f e r depends on 741 SAVEVALUE 1+,P3,XH d e l i v e r y type 742 ASSIGN 9,FN*XH1 s t o r e next t r a n s f e r 743 TEST NE P3,3,HIGG i f p a t i e n t i n f o r C - s e c t i o n 744 TEST NE P3,4,HIGG 745 TEST NE P3,9,HIGG 746 TRANSFER ,HIGJ 747 HIGG TEST E P9,12,HIGJ then do not t r a n s f e r t o PP 748 TEST E P11,1,HIGA i f not d e l i v e r e d 749 HIGJ SAVEVALUE 2,1210,XH le n g t h of stay 750 SAVEVALUE 2+,P3,XH depends on d e l i v e r y type 751 ASSIGN 15,FN*XH2 s t o r e l e n g t h of st a y 752 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 753 PRIORITY 2 754 HIGT ASSIGN 10,9 mark i n HIGH Appendix D. The Grace Hospital Simulation Model Code 1 4 2 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 755 QUEUE HIGQ 756 GATE SNF HIGH,HIGPB i f HIGH f u l l go t o problem 757 HIGIN ENTER HIGH e l s e take a room i n HIGH 758 DEPART HIGQ 759 TEST E P9,12,HIGC i f next t r a n s f e r to PP generate 760 TEST E PI1,0,HIGC a l l b abies not yet d e l i v e r e d 761 ASSIGN 11,1 d e l i v e r b a b i e s 762 ASSIGN 13,0 assume no de l a y t i l l babies 763 TEST G P15, 180,HIGB 764 ASSIGN 13,P15-180 de l a y baby's d e l i v e r y 765 HIGB TEST E P3,1,HIGD of the spont d e l i v e r i e s 766 TRANSFER .018,,HSTIL 1.8% d e l i v e r i e s are s t i l l b i r t h s 767 HIGD SPLIT 1,CRBAB send copy t o generate babies 768 MSAVEVALUE BDEL+,3,1,1 769 SAVEVALUE 10,V$DAY,XH s t o r e d e l i v e r y time of day 770 HIGMA TABULATE DL 771 TABULATE DELAP s t o r e time before 772 MARK get time a f t e r d e l i v e r y 773 HIGC ASSIGN 14,CC$HIGUC s t o r e user c h a i n unique number 774 SPLIT 1,HIGTI c r e a t e copy t o time LOS 775 PRIORITY 5 776 LINK HIGUC,16 wait on c h a i n of HIGH p a t i e n t s 777 HIGF TEST E P9,10,HIGL i f t r a n s f e r t o OR check OR f i r s t 778 TEST NE P3,4,HIGL t r a n s f e r i f emergency 779 TEST LE P16,AC1,HIGL t r a n s f e r i f bumped e a r l y 780 QUEUE ORWAI 781 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 782 DEPART ORWAI 7 83 HIGL LEAVE HIGH 784 PRIORITY 2 785 ASSIGN 15-,P16-AC1 time spent i n HIGH 786 TABULATE HIGH2 787 TRANSFER FN,100 t r a n s f e r t o next l o c a t i o n 788 HSTIL ASSIGN 9,18 send to AP i n s t e a d of PP 789 ASSIGN 11,2 mark s t i l l b i r t h 790 TRANSFER ,HIGMA 791 HIGTI PRIORITY 10 timer 792 ADVANCE P15 wait p r e s c r i b e d amount of time 793 UNLINK HIGUC,HUOUT,1 14PF,P14 then r e l e a s e mother from H 794 TERMINATE 0 stop copy 795 HIGPB GATE SNF LOW,HIGP2 i f HIGH f u l l go to LOW 796 DEPART HIGQ 797 MSAVEVALUE LDPBL+,2,1,1, H r e c o r d event 798 TRANSFER ,LOWT 799 HIGP2 GATE SNF ASESS,HIGP3 800 DEPART HIGQ 801 MSAVEVALUE LDPBL+,2,2,1, H r e c o r d event 802 TRANSFER ,LOWT 803 HIGP3 MSAVEVALUE LDPBL+,2,3,1, H i f HIGH and LOW f u l l r e c o r d , and 804 UNLINK HIGUC,HUOUT,1 k i c k out someone from HIGH 805 BUFFER 806 TRANSFER ,HIGIN 807 * 808 * OPERATING ROOM , subse c t i o n 809 OR MSAVEVALUE TRANS+,P10,10, 1 t r a n s f e r t a b l e 810 MSAVEVALUE TRANS+,P10,16 1 t o t a l row 811 MSAVEVALUE TRANS+,16,10, 1 t o t a l column 812 QUEUE ORQ Appendix D. The Grace Hospital Simulation Model Code 1 4 3 ;ting of HOSPITAL at 14:30: 47 on JUL 18, 1989 f o r CCid=SNAH on G 813 SAVEVALUE 10,V$DAY,XH 814 TEST E P3,9,ORD i f DOS 815 ASSIGN 3,3 change now to Ele c - C 816 TABULATE DOSDL s t o r e DOS d e l i v e r y time 817 TRANSFER ,ORE 818 ORD TABULATE DL s t o r e d e l i v e r y time 819 ORE ASSIGN 15,V$DAY 820 TABULATE ORHR st o r e time of day 821 ASSIGN 15,V$WEEK 822 TABULATE ORDAY s t o r e day of week 823 SAVEVALUE 1,220,XH 824 SAVEVALUE 1+,P3,XH 825 ASSIGN 9,FN*XH1 t r a n s f e r to ... 826 SAVEVALUE 2,1220,XH length of stay 827 SAVEVALUE 2+,P3,XH depends on d e l i v e r y type 828 ASSIGN 15,FN*XH2 s t o r e LOS 829 ASSIGN 10,10 mark i n OR 830 PRIORITY 2 831 MSAVEVALUE ORCAT+,P3,2,l s t o r e d e l i v e r y type i n OR 832 TEST E PI1,0,ORC c r e a t e baby i f necessary 833 ASSIGN 11,1 d e l i v e r y now 834 ASSIGN 13,0 no delay of b i r t h 835 836 TEST E P3,l,ORF of the spont d e l i v e r i e s 837 TRANSFER .018,,OSTIL 1.8% d e l i v e r i e s are s t i l l b i r t h s 838 ORF SPLIT 1,CRBAB send copy t o generate babies 839 MSAVEVALUE BDEL+,4,1,1 840 ORMAR TABULATE DELAP s t o r e time b e f o r e 841 MARK get time a f t e r d e l i v e r y 842 ORC GATE SNF OR,ORPB check i f OR f r e e 843 ENTER OR i f yes, enter the OR 844 DEPART ORQ 845 ADVANCE P15 stay a l l o t t e d time i n the OR 846 LEAVE OR 847 TRANSFER ,ORCT 848 ORPB MSAVEVALUE LDPBL+,3,1,1, H OR f u l l , r e c o r d problem 849 ADVANCE P15 wait i n queue 850 DEPART ORQ 851 ORCT TABULATE ORZ r e c o r d amount of time spent i n OR 852 TRANSFER FN,100 t r a n s f e r to next l o c a t i o n 853 OSTIL ASSIGN 9,18 send t o AP i n s t e a d of PP 854 ASSIGN 11,2 mark s t i l l b i r t h 855 TRANSFER ,ORMAR 856 * 857 858 * POST ANAESTHETIC RECOVERY s u b s e c t i o n 859 PAR MSAVEVALUE TRANS+,P10,11 ,1 t r a n s f e r t a b l e 860 MSAVEVALUE TRANS+,P10,16 ,1 t o t a l row 861 MSAVEVALUE TRANS+,16,11, 1 t o t a l column 862 SAVEVALUE 1,230,XH 863 SAVEVALUE 1+,P3,XH 864 ASSIGN 9,FN*XH1 t r a n s f e r to ... 865 SAVEVALUE 2,1230,XH length of st a y 866 SAVEVALUE 2+,P3,XH depends on d e l i v e r y type 867 ASSIGN 15,FN*XH2 s t o r e LOS 868 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 869 ASSIGN 10,11 mark i n PAR 870 QUEUE PARQ Appendix D. The Grace Hospital Simulation Model Code 144 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 871 GATE SNF PAR,PARPB i f PAR f u l l go t o problem 872 PAR IN ENTER PAR e l s e take bed i n PAR 873 DEPART PARQ 874 ASSIGN 14,X3 s t o r e user c h a i n unique number 875 SAVEVALUE 3+,l,X 876 SPLIT 1,PARTI c r e a t e copy to time LOS 877 PRIORITY 5 878 LINK PARUC,16 wait on c h a i n u n t i l time up 879 PARF LEAVE PAR or other mother preempts you 880 PRIORITY 2 881 ASSIGN 15-,P16-AC1 time spent i n PAR 882 TABULATE PAR2 883 TRANSFER FN,100 t r a n s f e r t o next l o c a t i o n 884 PARTI PRIORITY 10 ti m e r 885 ADVANCE P15 wait p r e s c r i b e d time 886 UNLINK PARUC,RUOUT ,1, 14PF,P14 r e l e a s e mother from PAR 887 TERMINATE 0 stop copy 888 PARPB GATE SNF HIGH,PARP2 i f PAR f u l l t r y HIGH 889 DEPART PARQ i f HIGH has space 890 MSAVEVALUE LDPBL+,4,1, 1,H r e c o r d event 891 TRANSFER , HIGT and t r a n s f e r t o HIGH 892 PARP2 MSAVEVALUE LDPBL+,4,2, 1,H i f PAR and HIGH f u l l 893 UNLINK PARUC,RUOUT ,1 k i c k out next mother from PAR 894 BUFFER 895 TRANSFER ,PARIN and r e c o r d event 896 * 897 *DAY OF SURGERY SUBSECTION 898 DOS MSAVEVALUE TRANS+,P10, 2,1 t r a n s f e r t a b l e 899 MSAVEVALUE TRANS+,P10, 16, 1 t o t a l row 900 MSAVEVALUE TRANS+,16,2 ,1 t o t a l column 901 ASSIGN 9,FN24 9 t r a n s f e r t o ... 902 ASSIGN 15,FN1249 s t o r e length of stay 903 ASSIGN 16,P15+AC1 c a l c d i s c h a r g e time 904 PRIORITY 2 905 QUEUE DOSNU 906 QUEUE PPMOD 907 DOST QUEUE DOSQ 908 ASSIGN 10,2 mark i n DOS 909 ASSIGN 5,1 send DOS p a t i e n t t o ARB i f p o s s i b L 910 TRANSFER FN, 98 t r a n s f e r t o PP module of c h o i c e 911 DARB GATE SNF ARB,DINC i f Arbutus i s f u l l t r y another 912 ENTER ARB module 913 DEPART DOSQ 914 ASSIGN 5,7 mark i n Arbutus from DOS 915 ASSIGN 14,X4 s t o r e user c h a i n unique number 916 SAVEVALUE 4+,l,X 917 SPLIT l,DOSTI c r e a t e LOS timer 918 PRIORITY 5 919 LINK PPUC,16 wait on PP c h a i n 920 DARB1 TEST E P9,10,DARBL i f t r a n s f e r t o OR check OR f i r s t 921 TEST LE P16,AC1,DARBL t r a n s f e r i f bumped e a r l y 922 QUEUE ORWAI 923 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 924 DEPART ORWAI 925 DARBL LEAVE ARB 926 TRANSFER ,DOSCT 927 DBAL GATE SNF BAL,DINC i f BAL f u l l t r y another module 928 ENTER BAL Appendix D. The Grace Hospital Simulation Model Code 1 4 5 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 929 DEPART DOSQ 930 ASSIGN 5,8 mark in BAL from DOS 931 ASSIGN 14,X4 store user chain unique number 932 SAVEVALUE 4+,l,X 933 SPLIT l,DOSTI create LOS timer 934 PRIORITY 5 935 LINK PPUC,16 wait on chain 936 DBAL1 TEST E P9,10,DBALL i f transfer to OR check OR f i r s t 937 TEST LE P16,AC1,DBALL 938 QUEUE ORWAI 939 TEST G R$OR,1 i f <= 1 OR l e f t delay transfer 940 DEPART ORWAI 941 DBALL LEAVE BAL 942 TRANSFER ,DOSCT 943 DCED GATE SNF CED,DINC i f CED f u l l t ry another module 944 ENTER CED 945 DEPART DOSQ 946 ASSIGN 5,9 mark in CED from DOS 947 ASSIGN 14,X4 store user chain unique number 948 SAVEVALUE 4+,l,X 949 SPLIT l,DOSTI create LOS timer 950 PRIORITY 5 951 LINK PPUC,16 wait on chain t i l l time up 952 DCED1 TEST E P9,10,DCEDL i f transfer to OR check OR f i r s t 953 TEST LE P16,AC1 transfer i f bumped early 954 QUEUE ORWAI 955 TEST G R$OR,1 i f <= 1 OR l e f t delay transfer 956 DEPART ORWAI 957 DCEDL LEAVE CED 958 TRANSFER ,DOSCT 959 DDOG GATE SNF DOG,DINC i f DOG f u l l t ry another module 960 ENTER DOG 961 DEPART DOSQ 962 ASSIGN 5,10 mark in DOG from DOS 963 ASSIGN 14,X4 store user chain unique number 964 SAVEVALUE 4+,l,X 965 SPLIT 1,DDGTI create LOS timer 966 PRIORITY 5 967 LINK DOGUC,16 wait on DOG chain in case AP patien 968 * needs place in DOG 969 DDG11 TEST E P9,10,DDOGL i f transfer to OR check OR f i r s t 970 TEST LE P16,ACl,DDOGL 971 QUEUE ORWAI 972 TEST G R$OR,1 i f <= 1 OR l e f t delay transfer 973 DEPART ORWAI 974 DDOGL LEAVE DOG 975 TRANSFER ,DOSCT 976 DDGTI PRIORITY 10 977 SPLIT l,DOSTI create LOS timer 978 LINK PPUC,16 join PP wait chain 979 DDOG1 TEST E P15,-100,DDLP 980 UNLINK DOGUC,FIN22,1, 14PF,P14 981 TERMINATE 0 982 DDLP UNLINK DOGUC,DUOUT,1, 14PF,P14 leaving PP also leave DOG 983 TERMINATE 0 wait chain 984 DEVE GATE SNF EVE,DINC i f EVE f u l l try other module 985 ENTER EVE 986 DEPART DOSQ Appendix D. The Grace Hospital Simulation Model Code 1 4 6 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 987 ASSIGN 5,11 mark i n EVE from DOS 988 ASSIGN 14,X4 s t o r e user c h a i n unique number 989 SAVEVALUE 4+,l,X 990 SPLIT 1,DEVTI c r e a t e LOS timer 991 PRIORITY 5 992 LINK EVEUC,16 wait on EVE p a t i e n t c h a i n 993 DEV11 TEST E P9,10,DEVEL i f t r a n s f e r t o OR check OR f i r s t 994 TEST LE P16,AC1,DEVEL 995 QUEUE ORWAI 996 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 997 DEPART ORWAI 998 DEVEL LEAVE EVE 999 TRANSFER ,DOSCT 1000 DEVTI PRIORITY 10 EVE LOS timer 1001 SPLIT 1,DOSTI j o i n DOS timer 1002 LINK PPUC,16 wait on PP p a t i e n t c h a i n 1003 DEVE1 TEST E P15,-100,DELP 1004 UNLINK EVEUC,FIN22,1 ,14PF,P14 1005 TERMINATE 0 1006 DELP UNLINK EVEUC,EUOUT,1 ,14PF,P14 1007 TERMINATE 0 1008 DFIR GATE SNF FIR,DINC i f FIR f u l l t r y other module 1009 ENTER FIR 1010 DEPART DOSQ 1011 ASSIGN 5,12 mark i n FIR from DOS 1012 ASSIGN 14,X4 s t o r e user c h a i n unique number 1013 SAVEVALUE 4+,l,X 1014 SPLIT 1,DOSTI c r e a t e LOS timer 1015 PRIORITY 5 1016 LINK PPUC,16 wait i n PP p a t i e n t c h a i n 1017 DFIR1 TEST E P9,10,DFIRL i f t r a n s f e r t o OR check OR f i r s t 1018 TEST LE P16,AC1,DFIRL t r a n s f e r i f bumped e a r l y 1019 QUEUE ORWAI 1020 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 1021 DEPART ORWAI 1022 DFIRL LEAVE FIR 1023 TRANSFER ,DOSCT 1024 DOSTI PRIORITY 10 1025 ADVANCE P15 1026 UNLINK PPUC,PUOUT,l, 14PF,P14 1027 TERMINATE 0 1028 DINC ASSIGN 5+,l ARB f u l l t r y another module 1029 TEST L P5,7,DTREA i f a l l PP f u l l t r y TREAT 1030 TRANSFER FN, 98 t r y next module 1031 * A l l : PP modules f u l l , go temp. to TREAT room 1032 DTREA GATE SNF TREAT,DOSPB i f TREAT f u l l go to problem 1033 ENTER TREAT e l s e take a TREAT room 1034 DEPART DOSQ 1035 ASSIGN 14,CC$TREUC s t o r e user c h a i n unique number 1036 SPLIT 1,DTRTI c r e a t e timer 1037 PRIORITY 5 1038 LINK TREUC,16 wait i n TREAT p a t i e n t chain 1039 DTRIN LEAVE TREAT 1040 PRIORITY 2 1041 TEST G P16,ACl,DOSCT i f time l e f t i n PP 1042 ASSIGN 15,P16-AC1 1043 TEST G V$PPSPA,0,DOSPB and the r e i s now p l a c e i n PP 1044 MSAVEVALUE LDPBL+,5,1,1, H r e c o r d event Appendix D. The Grace Hospital Simulation Model Code 147 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1045 TRANSFER ,DOST and goto PP module 1046 DTRTI PRIORITY 10 1047 SPLIT 1,DTRT2 c r e a t e second t i m e r t o watch PP 1048 ADVANCE P15 w a i t a l l o t t e d time 1049 UNLINK TREUCTUOUT, 1, 14PF,P14 remove mother from TREAT w 1050 TERMINATE 0 d e s t r o y t i m e r 1051 DTRT2 PRIORITY 1 1052 TEST G V$PPSPA,0 i f PP has p l a c e 1053 PRIORITY 10 move any mothers i n TREAT t o those 1054 UNLINK TREUCTUOUT, 1, 14PF,P14 f r e e beds 1055 TERMINATE 0 d e s t r o y t i m e r 1056 DOSPB MSAVEVALUE LDPBL+,5,2,1,H i f b o th PP & TREAT f u l l 1057 UNLINK PPUCPUOUT, 1 k i c k someone out of PP e a r l y 1058 ASSIGN 5,1 t r y t o get t o ARB ag a i n 1059 PRIORITY 0 l e t mothers i n TREAT go f i r s t 1060 BUFFER 1061 PRIORITY 2 1062 TRANSFER FN, 98 1063 DOSCT PRIORITY 2 f i n i s h e d w i t h DOS 1064 DEPART DOSNU count # i n DOS 1065 DEPART PPMOD 1066 ASSIGN 15-,P16-AC1 time spent i n PP 1067 TEST NE P15,500,NOTE 1068 ASSIGN 15+,0 1069 NOTE TABULATE DOSZ r e c o r d time i n DOS 1070 TRANSFER FN,100 t r a n s f e r t o next l o c a t i o n 1071 * 1072 * STILLBIRTHS 1073 STILL ASSIGN 9,15 t r a n s f e r t o d i s c h a r g e a f t e r AP 1074 SAVEVALUE 2,1300,XH use LOS from PP module 1075 SAVEVALUE 2+,P4,XH LOS depends on PP c a t e g o r y 1076 SAVEVALUE 1,FN*XH2,XH get # days i n PP 1077 ASSIGN 15,1440*XH1 s t o r e # minutes 1078 ASSIGN 15+,FN1300 add random time a f t e r 10AM 1079 ASSIGN 15+,1440-V$DAY add p o r t i o n of f i r s t day 1080 TEST G P15,0,STILL 1081 ASSIGN 16,P15+AC1 1082 TRANSFER ,APEX t r a n s f e r t o AP module 1083 * s t i l l b i r t h mothers not sent t o PP 1084 * 1085 1086 * POST PARTUM 1087 1088 1089 *POST PARTUM modules s u b s e c t i o n 1090 * 1091 PP MSAVEVALUE TRANS+,P10,12, 1 t r a n s f e r t a b l e 1092 MSAVEVALUE TRANS+,P10,16, 1 t o t a l row 1093 MSAVEVALUE TRANS+,16,12,1 t o t a l column 1094 QUEUE PPNUM 1095 QUEUE PPMOD 1096 PRIORITY 2 1097 TEST E P10,14,PPONE coming from PP PAR ? 1098 ASSIGN 15,P12 s t a y r e m a i n i n g time i n PP 1099 ASSIGN 16,P15+AC1 s t o r e d i s c h a r g e time 1100 ASSIGN 9,15 c o n t i n u e t o d i s c h a r g e 1101 TRANSFER ,PPT2 1102 * f i r s t v i s i t t o Post Partum Appendix D. The Grace Hospital Simulation Model Code 1 4 8 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1103 PPONE SAVEVALUE 1,300,XH 1104 SAVEVALUE 1+,P4,XH 1105 ASSIGN 9,FN*XH1 t r a n s f e r t o where? 1106 PPLOS SAVEVALUE 2,1300,XH 1107 SAVEVALUE 2+,P4,XH LOS depends on PP category 1108 SAVEVALUE 1,FN*XH2,XH get # days i n PP 1109 ASSIGN 15,1440*XH1 s t o r e # minutes 1110 ASSIGN 15+,FN1300 add random time a f t e r 10AM 1111 ASSIGN 15+,1440-V$DAY add p o r t i o n of f i r s t day 1112 TEST G P15,0,PPLOS 1113 ASSIGN 16,P15+AC1 1114 TEST E P9,13,PPT t r a n s f e r to PP OR? 1115 TEST G P15,1440,PPONE l e s s than 1 day i n PP, no OR 1116 ASSIGN 12,P15 1117 PPNEW ASSIGN 15.FN1299 amount of time i n PP b e f o r e OR 1118 TEST G P12-500, P15, PPNEW make sure enough time f o r returr. 1119 ASSIGN 12-,P15 to PP 1120 ASSIGN 16,P15+AC1 1121 PPT TEST NE P9,13,PPT3 i f not t r a n s f e r t o PP OR next 1122 ASSIGN 12,P15 use P12 to s t o r e t o t a l time i n PP 1123 PPT3 TEST NE P4,9,PPT2 1124 TABULATE PPZ2 1125 PPT2 QUEUE PPQ 1126 ASSIGN 5,XB11 PP module # 1127 ASSIGN 10,12 mark i n PP 1128 TEST G P5,6,PPSK check i f module number l e g a l 1129 ASSIGN 5,1 1130 SAVEVALUE 11,1,XB 1131 PPSK ASSIGN 11,P5 s t o r e f i r s t module t r i e d 1132 TRANSFER FN, 99 t r a n s f e r t o PP module of cho i c e 1133 ARB GATE SNF ARB,PPINC i f ARB f u l l t r y another module 1134 ENTER ARB e l s e take room i n ARB 1135 DEPART PPQ 1136 SAVEVALUE 11+,1,XB increment module r o t a t i o n counter-1137 ASSIGN 14,X4 s t o r e user c h a i n unique number 1138 SAVEVALUE 4+,l,X 1139 SPLIT 1,PPTI c r e a t e LOS timer 1140 PRIORITY 5 1141 LINK PPUC,16 wait on PP c h a i n 1142 ARB1 TEST E P9,13,ARBL i f t r a n s f e r t o OR check OR f i r s t 1143 TEST GE P16,AC1,ARBL t r a n s f e r i f bumped e a r l y 1144 QUEUE ORWAI c o l l e c t s t a t s 1145 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 1146 DEPART ORWAI 1147 ARBL LEAVE ARB 1148 TRANSFER ,PPCT f i n i s h e d with PP modules 1149 BAL GATE SNF BAL,PPINC i f BAL f u l l t r y another module 1150 ENTER BAL 1151 DEPART PPQ 1152 SAVEVALUE 11+,1,XB 1153 ASSIGN 14,X4 s t o r e user c h a i n unique number 1154 SAVEVALUE 4+,l,X 1155 SPLIT 1,PPTI c r e a t e LOS timer 1156 PRIORITY 5 1157 LINK PPUC,16 wait on PP wait c h a i n 1158 BALI TEST E P9,13,BALL i f t r a n s f e r to OR check OR f i r s t 1159 TEST GE P16,AC1,BALL 1160 QUEUE ORWAI Appendix D. The Grace Hospital Simulation Model Code 149 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid= SNAH on G 1161 TEST G R$OR,l i f <= 1 OR l e f t delay t r a n s f e r 1162 DEPART ORWAI 1163 BALL LEAVE BAL 1164 TRANSFER ,PPCT f i n i s h e d with PP modules 1165 CED GATE SNF CED,PPINC i f CED f u l l t r y next module i n r o t 1166 ENTER CED e l s e take room i n CED 1167 DEPART PPQ 1168 SAVEVALUE 11+,1,XB 1169 ASSIGN 14,X4 s t o r e user c h a i n unique number 1170 SAVEVALUE 4+,l,X 1171 SPLIT 1,PPTI c r e a t e LOS timer 1172 PRIORITY 5 1173 LINK PPUC,16 wait on PP c h a i n 1174 CED1 TEST E P9,13,CEDL i f t r a n s f e r to OR check OR f i r s t 1175 TEST GE P16,AC1,CEDL 1176 QUEUE ORWAI 1177 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 1178 DEPART ORWAI 1179 CEDL LEAVE CED 1180 TRANSFER ,PPCT f i n i s h e d with PP modules 1181 DOG GATE SNF DOG,PPINC i f DOG f u l l t r y another module 1182 ENTER DOG e l s e take bed i n DOG 1183 DEPART PPQ 1184 SAVEVALUE 11+,1,XB 1185 ASSIGN 14,X4 s t o r e user c h a i n unique number 1186 SAVEVALUE 4+,l,X 1187 SPLIT 1,DOGTI c r e a t e DOG LOS timer 1188 PRIORITY 5 1189 LINK DOGUC,16 wait on DOG wait c h a i n 1190 DOG 11 TEST E P9,13,DOGPL i f t r a n s f e r t o OR check OR f i r s t 1191 TEST GE P16,ACl,DOGPL i f preempted move to OR immed. 1192 QUEUE ORWAI 1193 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 1194 DEPART ORWAI 1195 DOGPL LEAVE DOG 1196 TRANSFER ,PPCT f i n i s h e d with DOG room 1197 DOGTI PRIORITY 10 1198 SPLIT 1,PPTI a l s o c r e a t e a PP LOS timer 1199 LINK PPUC,16 and wait i n PP wait c h a i n 1200 DOG1 TEST E PI 5,-100,DOLP i f d i s c h a r g e d by f l a g 1201 UNLINK DOGUC,FIN22,1, 14PF,P14 1202 TERMINATE 0 1203 DOLP UNLINK DOGUC,DUOUT,1, 14PF,P14 1204 TERMINATE 0 de s t r o y timer 1205 EVE GATE SNF EVE,PPINC i f EVE f u l l t r y next module 1206 ENTER EVE e l s e take room i n EVE 1207 DEPART PPQ 1208 SAVEVALUE 11+,1,XB 1209 ASSIGN 14,X4 s t o r e user c h a i n unique number 1210 SAVEVALUE 4+,l,X 1211 SPLIT 1,EVETI c r e a t e EVE LOS timer 1212 PRIORITY 5 1213 LINK EVEUC,16 wait on EVE wait c h a i n 1214 EVE11 TEST E P9,13,EVEL i f t r a n s f e r t o OR check OR f i r s t 1215 TEST GE P16,AC1,EVEL 1216 QUEUE ORWAI 1217 TEST G R$OR,1 i f <= 1 OR l e f t d e l a y t r a n s f e r 1218 DEPART ORWAI Appendix D. The Gia.ce Hospital Simulation Model Code 150 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1219 EVEL LEAVE EVE 1220 TRANSFER ,PPCT f i n i s h e d with EVE room 1221 EVETI PRIORITY 10 1222 SPLIT 1,PPTI a l s o c r e a t e PP timer 1223 LINK PPUC,16 and wait on PP wait c h a i n 1224 EVE1 TEST E P15,-100,EVLP 1225 UNLINK EVEUC,FIN22,1,14PF,P14 1226 TERMINATE 0 1227 EVLP UNLINK EVEUC,EUOUT,1,14PF,PI 4 1228 TERMINATE 0 d e s t r o y timer 1229 FIR GATE SNF FIR,PPINC i f FIR f u l l t r y next module 1230 ENTER FIR e l s e take bed i n FIR 1231 DEPART PPQ 1232 SAVEVALUE 11+,1,XB 1233 ASSIGN 14,X4 s t o r e user c h a i n unique number 1234 SAVEVALUE 4+,l,X 1235 SPLIT 1,PPTI c r e a t e PP LOS ti m e r 1236 PRIORITY 5 1237 LINK PPUC, 16 wait i n chain 1238 FIR1 TEST E P9,13,FIRL i f t r a n s f e r t o OR check OR f i r s t 1239 TEST LE P16,AC1,FIRL t r a n s f e r i f bumped e a r l y 1240 QUEUE ORWAI 1241 TEST G R$OR,l i f <= 1 OR l e f t d e l a y t r a n s f e r 1242 DEPART ORWAI 1243 FIRL LEAVE FIR 1244 TRANSFER ,PPCT f i n i s h e d with PP modules 1245 PPTI PRIORITY 10 PP LOS timer 1246 ADVANCE P15 wait p r e s c r i b e d amount of time 1247 UNLINK PPUC,PUOUT,1,14PF,PI4 remove mother from wait cha 1248 TERMINATE 0 d e s t r o y timer 1249 PPINC ASSIGN 5+,l t r y next module i n r o t a t i o n 1250 TEST L P5,7,PPRES r e s t a r t module counter? 1251 TEST NE P5,P11,TREAT check i f a l l PP modules are f u l l 1252 TRANSFER FN,99 1253 PPRES ASSIGN 5,1 r e s e t PP module counter 1254 TEST NE P5,P11,TREAT check i f a l l PP modules are f u l l 1255 TRANSFER FN,99 1256 TREAT GATE SNF TREAT,PPPB i f a l l PP modules f u l l 1257 ENTER TREAT . go to TREAT t e m p o r a r i l y 1258 DEPART PPQ 1259 ASSIGN 14,CC$TREUC s t o r e user c h a i n unique number 1260 SPLIT 1,TRETI c r e a t e TREAT LOS timer 1261 PRIORITY 5 1262 LINK TREUC16 wait i n TREAT 1263 TREIN LEAVE TREAT f i n i s h e d with TREAT 1264 TEST G P16,AC1,PPCT i f time l e f t i n PP st a y 1265 ASSIGN 15,P16-AC1 1266 TEST G V$PPSPA,0,PPPB t r y t o t r a n s f e r t o PP modules 1267 MSAVEVALUE PPPBL+,1,1,1,H r e c o r d event 1268 ASSIGN 15,P16-AC1 time l e f t f o r PP 1269 TRANSFER ,PPT2 go to PP module 127 0 TRETI PRIORITY 10 TREAT LOS timer 1271 SPLIT 1,TRET2 c r e a t e PP wait timer 1272 ADVANCE P15 wait p r e s c r i b e d amount of time 1273 UNLINK TREUC,TUOUT,1,14PF,PI4 then remove mother from TR 1274 TERMINATE 0 d e s t r o y timer 1275 TRET2 PRIORITY 1 second timer 1276 TEST G V$PPSPA,0 wait u n t i l PP modules become f r e e Appendix D. The Grace Hospital Simulation Model Code 151 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH'on G 1277 PRIORITY 10 when PP room f r e e 1278 UNLINK TREUCTUOUT ,1,14PF,P14 remove mothers from TREAT 1279 TERMINATE 0 d e s t r o y timer 1280 PPPB MSAVEVALUE PPPBL+,1,2, 1,H a l l PP modules and TREAT f u l l 1281 UNLINK PPUCPUOUT, 1 k i c k someone out of PP e a r l y 1282 ASSIGN 5,P11 t r y f i r s t module again 1283 PRIORITY 0 l e t mothers i n TREAT go f i r s t 1284 BUFFER 1285 PRIORITY 2 1286 TRANSFER FN, 99 1287 PPCT PRIORITY 2 f i n i s h e d with PP go to next l o c a t i o n 1288 TEST E P9,13,PPCT2 i f t r a n s f e r to PP OR 1289 ASSIGN 15-,P16-AC1 time i n PP i n P15 1290 TRANSFER ,PPCT3 1291 PPCT2 ASSIGN 15,P12-(P16 -AC1) time spent i n PP 1292 PPCT3 TABULATE PPZ 1293 DEPART PPNUM 1294 DEPART PPMOD 1295 TRANSFER FN,100 t r a n s f e r to next l o c a t i o n (P9) 1296 * 1297 * 1298 * POST PARTUM OPERATING ROOM / POST ANAESTHETIC RECOVERY s u b s e c t i o n 1299 PPOR MSAVEVALUE TRANS+,P10, 13,1 t r a n s f e r t a b l e 1300 MSAVEVALUE TRANS+,P10, 16,1 t o t a l row 1301 MSAVEVALUE TRANS+,16,13,1 t o t a l column 1302 QUEUE PPORQ 1303 PRIORITY 2 1304 ASSIGN 15,FN1310 1305 ASSIGN 16,P15+AC1 1306 ASSIGN 12-,P15 1307 ASSIGN 10, 13 1308 MSAVEVALUE ORCAT+,P3,3 ,1 1309 GATE SNF OR,PPOPB 1310 ENTER OR 1311 DEPART PPORQ 1312 ADVANCE P15 1313 LEAVE OR 1314 TRANSFER ,PPOCT 1315 PPOPB MSAVEVALUE PPPBL+,2,1, 1,H r e c o r d problem 1316 ADVANCE P15 1317 DEPART PPORQ 1318 PPOCT TABULATE ORZ 1319 * 1320 PPPAR MSAVEVALUE TRANS+,P10, 14,1 t r a n s f e r t a b l e 1321 MSAVEVALUE TRANS+,PI 0, 16,1 t o t a l row 1322 MSAVEVALUE TRANS+,16,14,1 t o t a l column 1323 ASSIGN 15,FN1320 generate length of st a y 1324 ASSIGN 16,P15+AC1 s t o r e d i s c h a r g e time 1325 ASSIGN 12-,P15 remove PAR time from t o t a l time i n PP 1326 ASSIGN 10,14 i n PAR now 1327 QUEUE PPPAQ 1328 GATE SNF PAR,PPPPB i f PAR f u l l , r e c o r d and preempt 1329 PPPIN ENTER PAR 1330 DEPART PPPAQ 1331 ASSIGN 14,X3 s t o r e user c h a i n unique number 1332 SAVEVALUE 3+,l,X 1333 SPLIT 1,PPPTI s p l i t to timer 1334 PRIORITY 5 Appendix D. The Grace Hospital Simulation Model Code 152 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on g ' 1335 LINK PARUC,16 j o i n chain of mothers i n PAR 1336 PPPF LEAVE PAR 1337 PRIORITY 2 1338 ASSIGN 15-,P16-AC1 time spent i n PAR 1339 TABULATE PAR2 1340 TRANSFER ,PP always go back to Post Partum 1341 PPPTI PRIORITY 10 PAR timer 1342 ADVANCE P15 wait l e n g t h of s t a y 1343 UNLINK PARUC,RUOUT,1,14PF,P14 remove mother from PAR cha 1344 TERMINATE 0 terminate t i m e r > 1345 * PAR f u l l ! 1346 PPPPB GATE SNF HIGH,PPPP2 t r y to go to HIGH r i s k 1347 MSAVEVALUE PPPBL+,3,1,1,H 1348 DEPART PPPAQ 1349 TRANSFER ,HIGT 1350 PPPP2 MSAVEVALUE PPPBL+,3,2,1,H r e c o r d problem 1351 UNLINK PARUC,RUOUT,1 e l s e preempt a mother i n PAR 1352 TRANSFER ,PPPIN 1353 * 1354 * 1355 *Babies path i n h o s p i t a l 1356 * 1357 * LOW RISK NURSERY s u b s e c t i o n 1358 LRN MSAVEVALUE BTRAN+,PI0,2,1 t r a n s f e r t a b l e 1359 MSAVEVALUE BTRAN+,P10,7,1 t o t a l row 1360 MSAVEVALUE BTRAN+,7,2,1 t o t a l column 1361 SAVEVALUE 1,400,XH 1362 SAVEVALUE 1+,P6,XH 1363 ASSIGN 9,FN*XH1 t r a n s f e r to ... 1364 SAVEVALUE 2,1400,XH 1365 SAVEVALUE 2+,P6,XH 1366 ASSIGN 15,FN*XH2 s t o r e length of stay 1367 ASSIGN 16,P15+AC1 s t o r e d i s c h a r g e time 1368 ASSIGN 10,2 i n LRN 1369 QUEUE LRNQ 1370 GATE SNF LRN,LRNPB i f LRN f u l l go to problem 1371 ENTER LRN e l s e take c o t i n LRN 1372 DEPART LRNQ 1373 ADVANCE P15 wait p r e s c r i b e d time 1374 LEAVE LRN 1375 TRANSFER ,LRNCT t r a n s f e r t o next l o c a t i o n 1376 LRNPB MSAVEVALUE BABPB+,1,1,1,H i f LRN f u l l r e c o r d problem 1377 ADVANCE P15 and wait a l l o t t e d time i n queue 1378 DEPART" LRNQ 1379 LRNCT TABULATE LRN2 1380 TRANSFER FN,96 t r a n s f e r t o next l o c a t i o n 1381 * 1382 * HIGH RISK NURSERY s u b s e c t i o n 1383 HRN MSAVEVALUE BTRAN+,P10,3,1 t r a n s f e r t a b l e 1384 MSAVEVALUE BTRAN+,PI0,7,1 t o t a l row 1385 MSAVEVALUE BTRAN+,7,3,1 t o t a l column 1386 SAVEVALUE 1,410,XH 1387 SAVEVALUE 1+,P6,XH 1388 ASSIGN 9,FN*XH1 t r a n s f e r t o ... 1389 SAVEVALUE 2,1410,XH 1390 SAVEVALUE 2+,P6,XH 1391 ASSIGN 15,FN*XH2 s t o r e l e n g t h of stay 1392 ASSIGN 16,P15+AC1 s t o r e d i s c h a r g e time Appendix D. The Grace Hospital Simulation Model Code 153 L i s t i n g o f H O S P I T A L a t 1 4 : 3 0 : :47 o n J U L 1 8 , 1 9 8 9 f o r C C i O S N A H o n G 1 3 9 3 A S S I G N 1 0 , 3 m a r k i n HRN 1 3 9 4 Q U E U E HRNQ 1 3 9 5 G A T E S N F HRN,HRNPB i f HRN f u l l g o t o p r o b l e m 1 3 9 6 E N T E R HRN e l s e t a k e c o t i n HRN 1 3 9 7 D E P A R T HRNQ 1 3 9 8 A D V A N C E P 1 5 w a i t a l l o t t e d t i m e 1 3 9 9 L E A V E HRN 1 4 0 0 T R A N S F E R ,HRNCT t r a n s f e r t o n e x t l o c a t i o n 1 4 0 1 H R N P B M S A V E V A L U E B A B P B + , 2 , 1 , 1 , H i f HRN f u l l r e c o r d p r o b l e m 1 4 0 2 A D V A N C E P 1 5 a n d w a i t i n q u e u e 1 4 0 3 D E P A R T HRNQ 1 4 0 4 H R N C T T A B U L A T E HRNZ 1 4 0 5 T R A N S F E R F N , 9 6 t r a n s f e r t o n e x t l o c a t i o n 1 4 0 6 * 1 4 0 7 * O B S E R V A T I O N N U R S E R Y s u b s e c t i o n 1 4 0 8 O B N M S A V E V A L U E B T R A N + , P 1 0 , 4 , 1 t r a n s f e r t a b l e 1 4 0 9 M S A V E V A L U E B T R A N + , P I 0 , 7 , 1 t o t a l r o w 1 4 1 0 M S A V E V A L U E B T R A N + , 7 , 4 , 1 t o t a l c o l u m n 1 4 1 1 S A V E V A L U E 1 , 4 2 0 , X H t r a n s f e r d e p e n d s o n 1 4 1 2 S A V E V A L U E 1 + , P 6 , X H b a b y ' s h e a l t h 1 4 1 3 A S S I G N 9 , F N * X H 1 t r a n s f e r t o . . . 1 4 1 4 S A V E V A L U E 2 , 1 4 2 0 , X H 1 4 1 5 S A V E V A L U E 2 + , P 6 , X H 1 4 1 6 A S S I G N 1 5 , F N * X H 2 s t o r e l e n g t h o f s t a y 1 4 1 7 A S S I G N 1 6 , P 1 5 + A C 1 c a l c d i s c h a r g e t i m e 1 4 1 8 A S S I G N 1 0 , 4 m a r k i n OBN 1 4 1 9 Q U E U E OBNQ 1 4 2 0 G A T E S N F O B N , O B N P B i f OBN f u l l g o t o p r o b l e m 1 4 2 1 O B N T E N T E R OBN e l s e t a k e c o t i n OBN 1 4 2 2 D E P A R T OBNQ 1 4 2 3 A S S I G N 1 4 , C C $ O B N U C s t o r e u s e r c h a i n u n i q u e numbi 1 4 2 4 S P L I T 1 , O B N T I c r e a t e c o p y t o c o n t r o l L O S 1 4 2 5 P R I O R I T Y 5 1 4 2 6 L I N K O B N U C , 1 6 w a i t i n c h a i n o f b a b i e s i n O BN 1 4 2 7 O B N F L E A V E O B N 1 4 2 8 P R I O R I T Y 2 1 4 2 9 A S S I G N 1 5 - , P 1 6 - A C 1 t i m e s p e n t i n OBN 1 4 3 0 T A B U L A T E O B N Z 1 4 3 1 T E S T G P 1 6 , A C 1 , O B N C i f k i c k e d o u t o f OBN e a r l y 1 4 3 2 A S S I G N 1 5 , P 1 6 - A C 1 1 4 3 3 T A B U L A T E O B N T B s t o r e l o s t t i m e 1 4 3 4 O B N C T R A N S F E R F N , 9 6 t r a n s f e r t o n e x t l o c a t i o n 1 4 3 5 O B N T I P R I O R I T Y 10 t i m e r 1 4 3 6 A D V A N C E P 1 5 w a i t p r e s c r i b e d t i m e 1 4 3 7 U N L I N K O B N U C , O B N F , l , 1 4 P F , P 1 4 r e l e a s e b a b y f r o m OBN 1 4 3 8 T E R M I N A T E 0 d e s t r o y t i m e r 1 4 3 9 O B N P B U N L I N K O B N U C , O B N F , 1 i f OBN f u l l k i c k s o m e o n e o u t 1 4 4 0 B U F F E R 1 4 4 1 M S A V E V A L U E B A B P B + , 3 , 1 , 1 , H o f OBN e a r l y a n d r e c o r d e v e n t v / ^ ' 1 4 4 2 T R A N S F E R , OBNT 1 4 4 3 * 1 4 4 4 * P O S T P A R T U M N U R S E R Y s u b s e c t i o n 1 4 4 5 P P N M S A V E V A L U E B T R A N + , P I 0 , 5 , 1 1 4 4 6 M S A V E V A L U E B T R A N + , P 1 0 , 7 , 1 1 4 4 7 M S A V E V A L U E B T R A N + , 7 , 5 , 1 1 4 4 8 S A V E V A L U E 1 , 4 3 0 , X H 1 4 4 9 S A V E V A L U E 1 + , P 6 , X H 1 4 5 0 A S S I G N 9 , F N * X H 1 t r a n s f e r t a b l e t o t a l r o w t o t a l c o l u m n t r a n s f e r t o .. Appendix D. The Grace Hospital Simulation Model Code 154 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1451 SAVEVALUE 2,1430,XH 1452 SAVEVALUE 2+,P6,XH 1453 ASSIGN 15,FN*XH2 s t o r e l e n g t h of stay 1454 ASSIGN 16,P15+AC1 s t o r e d i s c h a r g e time 1455 ASSIGN 10,5 i n PPN 1456 QUEUE PPNQ 1457 ASSIGN 5,XB12 f i n d which PP module to t r y next 1458 TEST G P5,6,BMOVE check t h a t module # not > 6 1459 ASSIGN 5,1 e l s e r e s t a r t # 1460 SAVEVALUE 12,1,XB 1461 BMOVE ASSIGN 11, P5 s t o r e f i r s t module t r i e d 1462 TRANSFER FN, 97 t r a n s f e r to module of c h o i c e 1463 ARBN GATE SNF ARBN,BINC i f ARB nursery f u l l t r y next nurser 1464 ENTER ARBN e l s e take c o t i n ARB nursery 1465 DEPART PPNQ 1466 SAVEVALUE 12+,1,XB increment module r o t a t i o n counter 1467 ADVANCE P15 stay p r e s c r i b e d length of time 1468 LEAVE ARBN 1469 TRANSFER ,PPNCT 1470 BALN GATE SNF BALN,BINC i f BALN f u l l t r y next n u r s e r y 1471 ENTER BALN e l s e take c o t i n BAL nursery 1472 DEPART PPNQ 1473 SAVEVALUE 12+,1,XB increment module r o t a t i o n counter 1474 ADVANCE P15 s t a y a l l o t t e d l e n gth of time 1475 LEAVE BALN 1476 TRANSFER ,PPNCT 1477 CEDN GATE SNF CEDN,BINC i f CEDN f u l l t r y next n u r s e r y 1478 ENTER CEDN e l s e take c o t i n CED nu r s e r y 1479 DEPART PPNQ 1480 SAVEVALUE 12+,1,XB increment module r o t a t i o n counter 1481 ADVANCE P15 stay a l l o t t e d time 1482 LEAVE CEDN 1483 TRANSFER ,PPNCT 1484 DOGN GATE SNF DOGN,BINC i f DOG nursery f u l l t r y next nurser 1485 ENTER DOGN e l s e take c o t i n DOGN 1486 DEPART PPNQ 1487 SAVEVALUE 12+,1,XB increment module r o t a t i o n counter 1488 ADVANCE P15 stay p r e s c r i b e d l e n g t h of time 1489 LEAVE DOGN 1490 TRANSFER ,PPNCT 1491 EVEN GATE SNF EVEN,BINC i f EVE nu r s e r y f u l l t r y other nurser 1492 ENTER EVEN e l s e take c o t i n EVEN 1493 DEPART PPNQ 1494 SAVEVALUE 12+,1,XB increment module r o t a t i o n counter 1495 ADVANCE P15 s t a y a l l o t t e d time i n EVEN 1496 LEAVE EVEN 1497 TRANSFER ,PPNCT 1498 FIRN GATE SNF FIRN,BINC i f FIRN f u l l t r y another nursery 1499 ENTER FIRN e l s e occupy a c o t i n FIR nursery 1500 DEPART PPNQ 1501 SAVEVALUE 12+,1,XB increment module r o t a t i o n counter 1502 ADVANCE P15 s t a y a l l o t t e d time i n FIRN 1503 LEAVE FIRN 1504 TRANSFER ,PPNCT 1505 BINC ASSIGN 5+,l module f i r s t t r i e d was f u l l 1506 TEST L P5,7,BRES t r y the next nursery i n the r o t a t i o n 1507 TEST NE P5,P11,PPNPB 1508 TRANSFER FN, 97 go to next nursery Appendix D. The Grace Hospital Simulation Model Code 155 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1509 BRES ASSIGN 5,1 1510 TEST NE P5,PI1,PPNPB 1511 TRANSFER FN, 97 go to next nursery 1512 PPNPB MSAVEVALUE BABPB+,4,1,1,H a l l n u r s e r i e s f u l l 1513 ADVANCE P15 r e c o r d event and stay i n queue 1514 DEPART PPNQ 1515 PPNCT TABULATE PPNZ f i n i s h e d s t a y i n PPN 1516 TRANSFER FN, 96 t r a n s f e r to next l o c a t i o n 1517 * 1518 * END OF HOSPITAL 1519 1520 1521 * 1522 • C o n t r o l of p a t i e n t s l e a v i n g a wait c h a i n e a r l y 1523 LUOUT TEST G P16,AC1,FIN from LOW wait chains 1524 ASSIGN 15,P16-AC1 1525 TABULATE LOWTB 1526 TRANSFER ,FIN 1527 HUOUT TEST G P16,AC1,FIN from HIG wai t chains 1528 ASSIGN 15,P16-AC1 1529 TABULATE HIGTB 1530 TRANSFER ,FIN 1531 FIN TRANSFER FN, 95 1532 RUOUT TEST G PI 6,AC1,RFIN from PAR wait chains 1533 ASSIGN 15,P16-AC1 1534 TABULATE PARTB 1535 RFIN TRANSFER FN, 89 1536 LROUT ASSIGN 15-,P16-AC1 from LOW (temp, i n PAR) 1537 TABULATE LPAR 1538 TRANSFER FN, 88 1539 AUOUT ASSIGN 15-,P16-AC1 from ASESS wait c h a i n 1540 TABULATE ASESZ 1541 TRANSFER FN, 92 1542 TUOUT ASSIGN 15-,P16-AC1 1543 TABULATE TREAZ 1544 TRANSFER FN, 90 from TREAT user chain 1545 DUOUT TEST G P16,AC1,FIN22 from dogwood user c h a i n 1546 TRANSFER ,FIN2 kic k e d out by PP p a t i e n t 1547 EUOUT TEST G P16,AC1,FIN22 from evergreen user c h a i n 1548 FIN2 ASSIGN 15,P16-AC1 k i c k e d out of DOG/EVE e a r l y 1549 TABULATE PPTB 1550 FIN22 TRANSFER FN, 94 t r a n s f e r to next l o c a t i o n 1551 D20UT TEST G P16,AC1,FIN22 from dogwood user c h a i n 1552 UNLINK PPUC,OUT,1,14PF,P14 1553 LEAVE DOG kic k e d out by AP p a t i e n t 1554 PRIORITY. 2 1555 BUFFER allow AP p a t i e n t to take p l a c e 1556 ASSIGN 15,P16-AC1 t r y another PP module 1557 TRANSFER FN, 91 1558 E20UT TEST G P16,AC1,FIN22 from evergreen user c h a i n 1559 UNLINK PPUC,OUT,1,14PF,P14 1560 LEAVE EVE k i c k e d out by AP p a t i e n t 1561 PRIORITY 2 1562 BUFFER allow AP p a t i e n t to take p l a c e 1563 ASSIGN 15,P16-AC1 1564 TRANSFER FN, 91 t r y another PP module 1565 PUOUT TEST G P16,AC1,FIN3 from PP user c h a i n 1566 ASSIGN 15,P16-AC1 i f d i s c h a r g e d e a r l y r e c o r d Appendix D. The Grace Hospital Simulation Model Code 156 L i s t i n g o f H O S P I T A L a t 1 4 : 3 0 : 4 7 o n J U L 1 8 , 1 9 8 9 f o r C C i d = S N A H o n G 1 5 6 7 T E S T N E P 5 , 4 , F I N 3 d o n o t t a b u l a t e i f f r o m D O G 1 5 6 8 T E S T N E P 5 , 5 , F I N 3 o r E V E s i n c e t h e y w i l l b e 1 5 6 9 T E S T N E P 5 , 1 0 , F I N 3 t a b u l a t e d a t D U O U T O R E U O U T 1 5 7 0 T E S T N E P 5 , 1 1 , F I N 3 1 5 7 1 T A B U L A T E P P T B t a b u l a t e t h i s e v e n t , a n d l o s t t i m e 1 5 7 2 F I N 3 T R A N S F E R F N , 9 3 1 5 7 3 * 1 5 7 4 * 1 5 7 5 1 5 7 6 « * » * . * * * * D I S C H A R G E S F R O M H O S P I T A L * * * * * * * * * * * * 1 5 7 7 1 5 7 8 * M o t h e r d i s c h a r g e s 1 5 7 9 D I S M S A V E V A L U E T R A N S + , P 1 0 , 1 5 , 1 t r a n s f e r t a b l e 1 5 8 0 M S A V E V A L U E T R A N S + , P 1 0 , 1 6 , 1 t o t a l r o w 1 5 8 1 M S A V E V A L U E T R A N S + , 1 6 , 1 5 , 1 t o t a l c o l u m n 1 5 8 2 T E S T E P I 1 , 0 , F G G 1 5 8 3 A S S I G N 1 5 , P 1 5 1 5 8 4 F G G A S S I G N 1 5 , V $ D A Y 1 5 8 5 T A B U A L A T E D I S Z a n d t i m e o f d i s c h a r g e 1 5 8 6 T E S T L E P 3 , 4 , D I S 1 1 5 8 7 T A B U L A T E D E L P P d e l i v e r e d m o t h e r s 1 5 8 8 M S A V E V A L U E D I S C H + , 2 , 1 , 1 r e c o r d # d i s c h a r g e s 1 5 8 8 . 2 T E S T N E P 3 , 1 , D I S S P 1 5 8 8 . 4 T E S T N E P 3 , 2 , D I S I N 1 5 8 8 . 6 T E S T N E P 3 , 3 , D I S E L 1 5 8 8 . 8 T A B U L A T E E M C P P 1 5 8 8 . 8 6 T R A N S F E R , O U T 1 5 8 8 . 9 2 D I S E L T A B U L A T E E L C P P 1 5 8 8 . 9 3 T R A N S F E R , O U T 1 5 8 8 . 9 4 D I S I N T A B U L A T E I N S P P 1 5 8 8 . 9 5 T R A N S F E R , O U T 1 5 8 8 . 9 7 D I S S P T A B U L A T E S P O P P 1 5 8 9 T R A N S F E R , O U T 1 5 9 0 D I S 1 T E S T E P 3 , 5 , D I S 2 1 5 9 1 T A B U L A T E P P T O T P P o n l y m o t h e r s 1 5 9 2 M S A V E V A L U E D I S C H + , 2 , 2 , 1 1 5 9 3 T R A N S F E R , O U T 1 5 9 4 D I S 2 T E S T E P 3 , 6 , D I S 3 1 5 9 5 T A B U L A T E U N T O T U n d e l m o t h e r s 1 5 9 6 M S A V E V A L U E D I S C H + , 2 , 2 , 1 1 5 9 7 T R A N S F E R , O U T 1 5 9 8 D I S 3 T A B U L A T E D E L P P 1 5 9 9 T E R M I N A T E 0 1 6 0 0 O U T T E R M I N A T E 0 d e s t r o y t r a n s a c t i o n s 1 6 0 1 * 1 6 0 2 * B a b y i d i s c h a r g e s 1 6 0 3 D I S B M S A V E V A L U E B T R A N + , P 1 0 , 6 , 1 t r a n s f e r t a b l e 1 6 0 4 M S A V E V A L U E B T R A N + , P I 0 , 7 , 1 t o t a l r o w 1 6 0 5 M S A V E V A L U E B T R A N + , 7 , 6 , 1 t o t a l c o l u m n 1 6 0 6 M S A V E V A L U E D I S C H + , 2 , 3 , 1 r e c o r d # o f d i s c h a r g e s 1 6 0 7 T E S T L E P 6 , 3 , D I S B 1 1 6 0 8 T A B U L A T E N B T O T n e w b o r n 1 6 0 9 T R A N S F E R , O U T 1 6 1 0 D I S B 1 T E S T E P 6 , 4 , D I S B 2 1 6 1 1 T A B U L A T E S H T O T s h o r t s t a y b a b i e s ( t o c h i l d r e n s ) 1 6 1 2 T R A N S F E R , O U T 1 6 1 3 D I S B 2 T A B U L A T E P D T O T p e d i a t r i c b a b y 1 6 1 4 T E R M I N A T E 0 Appendix D. The Grace Hospital Simulation Model Code 157 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1615 * 1616 *simulate r e d f l a g c o n d i t i o n a t Grace. 1617 * d i s c h a r g e mothers e a r l y i f few PP rooms are f r e e 1618 FLAG VARIABLE V$PPSPA-S$LOW~S$HIGH 1619 * 1620 GENERATE 1440 1621 ADVANCE 600 wait u n t i l 10 AM 1622 TEST L V$FLAG,15,OUT more than 15 beds f r e e do nothing 1623 UNLINK PPUC,FUOUT,15-V$FLAG 1624 TERMINATE 0 1625 * check i f p a t i e n t s are e l l i g i b l e f o r e a r l y d i s c h a r g e 1626 FUOUT SAVEVALUE 1,P16-AC1,X 1627 TEST E P9,15,RETO on l y d i s c h a r g e i f going t o d i s c h a r g e nex 1628 TRANSFER .5,,RET 50% m e d i c a l l y able to d i s c h a r g e 1629 TEST G XI,300,RET . d i s c h a r g e d soon anyway 1630 TEST L XI,2880,RET s t i l l s t a y i n g more than 2 days 1631 ASSIGN 15,P16-AC1 1632 TABULATE FLAG time l o s t due to e a r l y d i s c h a r g e 1633 MSAVEVALUE RFLAG+,1,1,1,H 1634 ASSIGN 15,-100 1635 TRANSFER FN,93 1636 RETO PRIORITY 5 1637 UNLINK PPUC,FUOUT,1 t r y to d i s c h a r g e someone e l s e 1638 BUFFER 1639 PRIORITY 10 1640 RET LINK PPUC,16 r e t u r n t o wait c h a i n 1641 1642 * 164 3 GENERATE 1440 run f o r 1 day 1644 ADVANCE 630 wait u n t i l 10:30 to take census 1645 MSAVEVALUE CENSU,XH7,1,S$HOLLY,H 1646 MSAVEVALUE CENSU,XH7,2,Q$APDGN,H 1647 MSAVEVALUE CENSU,XH7,4,SSLOW,H 1648 MSAVEVALUE CENSU,XH7,5,S$ASESS,H 1649 MSAVEVALUE CENSU,XH7,6,S$HIGH,H 1650 MSAVEVALUE CENSU,XH7,7,Q$PPNUM,H 1651 MSAVEVALUE CENSU,XH7,8,Q$PPMOD,H 1652 MSAVEVALUE CENSU,XH7,9,S$TREAT,H 1653 MSAVEVALUE CENSU,XH7,10,S$OBN,H 1654 * get 10:30 average census 1655 MSAVEVALUE CSTEN+,1,1,S$HOLLY 1656 MSAVEVALUE CSTEN+,2,1,Q$APDGN 1657 MSAVEVALUE CSTEN+,4,1,S$LOW 1658 MSAVEVALUE CSTEN+,5,1,S$ASESS 1659 MSAVEVALUE CSTEN+,6,1,S$HIGH 1660 MSAVEVALUE CSTEN+,7,1,Q$PPNUM 1661 MSAVEVALUE CSTEN+,8,1,Q$PPMOD 1662 MSAVEVALUE CSTEN+,9,1,S$TREAT 1663 MSAVEVALUE CSTEN+,10,1,S$OBN 1664 MSAVEVALUE CNUM+,1,1,1,H 1665 ADVANCE 810 1666 * get 24:00 average census 1667 MSAVEVALUE CSMID+,1,1,S$HOLLY 1668 MSAVEVALUE CSMID+,2,1,Q$APDGN 1669 MSAVEVALUE CSMID+,4,1,S$LOW 1670 MSAVEVALUE CSMID+,5,1,S$ASESS 1671 MSAVEVALUE CSMID+,6,1,S$HIGH 1672 MSAVEVALUE CSMID+,7,1,Q$PPNUM Appendix D. The Grace Hospital Simulation Model Code 1 5 8 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 1673 MSAVEVALUE CSMID+,8,1,Q$PPMOD 1674 MSAVEVALUE CSMID+,9,1,SSTREAT 1675 MSAVEVALUE CSMID+,10,1,S$OBN 1676 MSAVEVALUE CNUM+,2,1,1,H 1677 SAVEVALUE 7+,l,XH 1678 TEST G XH7,30,END 1679 SAVEVALUE 7,1,XH 1680 END TERMINATE 0 1681 * 1682 GENERATE (310*1440) 1683 BRMULT 123,343,3,7,12333,3445,989,835,9743,983,98499,9931 1684 ,9941,33,23,43,567,87,97653,455,51245,783,623,74329,45,41,34 45,65,7. 1685 ,43,97643,501,5,66667,7753,223,445,555,667,9989,121,221,4423,67,89_ 1686 ,945,6643,7,9,1,3,455,55,7747,89,8543,45435,67667,853,565,343,567,9 1687 ,953,5467,64579,65,15,5667,8783,455,65467,451,341,3123,43241,54457_ 1688 ,95,69561,3411,111,3311,56511,45423,5565,7783,991,99123,98743,9343_ 1689 ,965,249,9521,98451,953,94543,945,9555,883,473,945,923,9453,995,7241 1690 ,941,1,35,9,9943,765,73421,83,889,8883,88881,883,667,3343,933,945,5 1691 ,95,689,97423,9945,953,9945,9925,99999,9241,4545,555,5555,55555,221 1692 ,965,54567,667,545,453,4545,5467,53,34345,655,65545,65665,441,1,33_ 1693 ,1333,565,543,343,34567,9565,55,6667,8843,565,45561,13,131,343,9_ 1694 ,91,345,56763,5463,64543,6437,655,56321,111,1111,11111,2223,67,7_ 1695 ,9443,545,56781,2231,445,44555,65545,893,9973,3445,343,23341,5445_ 1696 ,95,64563,5447,5667,77,777,7777,77777,1,87,783,5435,4545,65453,45_ 1697 ,7,775,431,441,43463,99,9999,9997,9921,9943,9943,4841,9983,99843_ 1698 ,9963,54561,1,7,111,11145,65561,24457,67,567,8785,78763,5653,989_ 1699 ,91,323,4323,453,767,7777,5445,'7883,7893,34221,41,43,789,9763,89_ 1700 ,8823,111,453,7467,667,45465,111,4657,665 1701 TERMINATE 0 1702 * 1703 GENERATE 1440 1704 TERMINATE 1 end of one day 1705 * 1706 * 1 "7 0 "7 **************************************** 1708 *storages - places i n the hospital 1709 ARB STORAGE 16 arbutus PP module 1710 BAL STORAGE 15 balsam PP module 1711 CED STORAGE 16 cedar PP module 1712 DOG STORAGE 16 dogwood AP/PP module 1713 EVE STORAGE 15 evergreen PP module 1714 FIR STORAGE 16 f i r PP module 1715 TREAT STORAGE 6 1 treatment room in each PP module 1716 HOLLY STORAGE 26 holly AP module 1717 LOW STORAGE 11 low r i s k delivery area 1718 ASESS STORAGE 4 4 assessment rooms in low risk 1719 HIGH STORAGE 8 high r i s k , includes 4 intensive care beds 1720 OR STORAGE 3 operating rooms 1721 PAR STORAGE 4 post anaesthetic recovery rooms 1722 ARBN STORAGE 16 arbutus nursery 1723 BALN STORAGE 15 balsam nursery 1724 CEDN STORAGE 16 cedar nursery 1725 DOGN STORAGE 16 dogwood nursery 1726 EVEN STORAGE 15 evergreen nursery 1727 FIRN STORAGE 16 f i r nursery 1728 LRN STORAGE 11 low r i s k delivery nursery 1729 HRN STORAGE 8 high r i s k delivery nursery 1730 OBN STORAGE 10 observation nursery Appendix D. The Grace Hospital Simulation Model Code 159 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 APDGN EQU APEVN EQU ORWAI EQU DOSNU EQU PPNUM EQU PPMOD EQU EXPO EQU 100, Q 101, Q 500,Q 200,Q 300, Q 301, Q 69, Y * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *matric CLASS APPBL LDPBL PPPBL BABPB TRANS BTRAN RFLAG CENSU CSTEN CSMID CNUM DISCH ARRIV BDEL ORCAT APNUM ARRIV CLASS TRANS BTRAN APPBL LDPBL PPPBL BABPB APNUM BDEL ORCAT RFLAG CENSU CSTEN CSMID CNUM es ( f o r MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX MATRIX EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU EQU saving va X,8,10 H,5,3 H,5,3 H,3,2 H,4,l X,16,16 X,7,7 H,2,l H,31,10 X,10,l X,10,1 H,2,l X,2,3 H,31,2 X,4,l X,6,3 X,2,9 10,M 20,M 30, M 31, M 50,M 52,M 54,M 56,M 60,M 70,M 72,M 80,M 90, M 91, M 92, M 93, M lues only) s t o r e a l l the c l a s i f i c a t i o n s s t o r e problems when AP f u l l s t o r e problems when L&D f u l l s t o r e problems when PP f u l l s t o r e problems when a Baby module i s f u l l t r a n s f e r t a b l e f o r mothers t r a n s f e r t a b l e f o r babies s t o r e number of e a r l y d i s c h a r g e s from f i e s t o r e d a i l y 10 AM census of v a r i o u s place 10:30 t o t a l census 24:00 t o t a l census # days i n average census s t o r e number of mother/baby d i s c h a r g e s s t o r e # mothers t o a r r i v e each day # d e l i v e r i e s d e l t y p e i n OR Undel vs. Del i n AP * * * * * * * * * * * * * •tables LOWTB HIGTB PARTB OBNTB PPTB FLAG LOW2 ASESZ HIGHZ ORZ * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLE P15,30,30,10 s t o r e LOW preempted times P15,30,30,10 s t o r e HIGH preempted times P15,10,10,10 s t o r e PAR preempted times P15,360,360,10 s t o r e OBN preempted times P15,360,360,10 s t o r e PP preempted times P15,360,360,10 s t o r e PP preempts by f l a g system P15,120,120,30 t a b u l a t e time i n LOW P15,30,30,20 t a b u l a t e time i n ASESS P15,120,120,30 t a b u l a t e time i n HIGH P15,15,15,30 t a b u l a t e time i n OR Appendix D. The Grace Hospital Simulation Model Code 160 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 1789 ORHR TABLE P15,60,60,25 time of day i n OR 1790 ORDAY TABLE P 1 5 , l , l , 8 day of week i n OR 1791 PARZ TABLE P15,15,15,30 t a b u l a t e time i n PAR 1792 LPAR TABLE P15,30,30,20 t a b u l a t e time i n PAR from LOW 1793 APZ TABLE P15,1440,1440,30 t a b u l a t e time i n AP 1794 STILZ TABLE P15,1440,1440,20 t a b u l a t e s t i l l b i r t h time i n 1795 PPZ TABLE P15,1440,1440,30 t a b u l a t e time i n PP 1796 PPZ2 TABLE P12,1440,1440,30 t a b u l a t e d e l i v time i n PP 1797 DOSZ TABLE P15,60,60,30 t a b u l a t e time i n DOS 1798 TREAZ TABLE P15,60,60,20 t a b u l a t e time i n TREAT 1799 DISZ TABLE P15,60,60,25 t a b u l a t e d i s c h a r g e hour 1800 LRNZ TABLE P15,30,30,20 t a b u l a t e time i n LRN 1801 HRNZ TABLE P15,30,30,20 t a b u l a t e time i n HRN 1802 OBNZ TABLE P15,1440,1440,20 t a b u l a t e time i n OBN 1803 PPNZ TABLE P15,1440,1440,20 t a b u l a t e time i n PPN 1804 ATIME TABLE P16,60,60,25 a r r i v a l time of DOS 1805 ARATE TABLE P16,20,20,30 a r r i v a l r a t e of d e l i v 1806 ATIM2 TABLE P16,60,60,25 a r r i v a l time of d e l i v 1807 DOSDL TABLE XH10,60,60,25 d e l i v e r y time of day f o r DOS 1808 DL TABLE XH10,60,60,25 d e l i v e r y time of day others 1809 DELAP TABLE (M1+P13),1440,1440,30 d e l i v b e f o r e d e l i v e r y 1810 DELPP TABLE (M1-P13),720,720,30 d e l i v a f t e r d e l i v e r y 1810. .2 1810. ,6 SPOPP TABLE (M1-P13),720,720,30 spont a f t e r d e l i v e r y 1810. ,7 INSPP TABLE (M1-P13),720,720,30 i n s t a f t e r d e l i v e r y 1810. ,8 1810. ,9 ELCPP TABLE (M1-P13),720,720,30 e l - C a f t e r d e l i v e r y 1810. ,95 EMCPP TABLE (M1-P13),720,720,30 em-C a f t e r d e l i v e r y 1811 UNTOT TABLE Ml, 1440, 1440, 30 undel i n h o s p i t a l 1812 PPTOT TABLE Ml,720,720,30 PPonly i n h o s p i t a l 1813 NBTOT TABLE Ml, 1440, 1440, 20 newborn i n h o s p i t a l 1814 SHTOT TABLE Ml,20,20,20 sh o r t stay i n h o s p i t a l 1815 PDTOT TABLE Ml,1440,1440,30 P e d i a t r i c i n h o s p i t a l 1816 ORWAI QTABLE ORWAI,15,15,20 t a b u l a t e time w a i t i n g f o r OR 1817 * 1818 APZ EQU 10,T 1819 STILZ EQU 12,T. 1820 LOWZ EQU 20,T 1821 ASESZ EQU 22,T 1822 LPAR EQU 23,T 1823 LOWTB EQU 25,T 1824 HIGHZ EQU 30,T 1825 HIGTB EQU 35,T 1826 ORZ EQU 40,T 1827 ORHR EQU 41,T 1828 ORDAY EQU 42,T 1829 PARZ EQU 50,T 1830 PARTB EQU 55,T 1831 DOSZ EQU 60,T 1832 PPZ EQU 70,T 1833 PPZ2 EQU 71,T 1834 TREAZ EQU 75,T 1835 PPTB EQU 77,T 1836 FLAG EQU 80,T 1837 DISZ EQU 90,T 1838 LRNZ EQU 100,T 1839 HRNZ EQU 110,T 1840 OBNZ EQU 120,T Appendix D. The Grace Hospital Simulation Model Code 161 L i s t i n g o f H O S P I T A L a t 1 4 : 3 0 : 4 7 o n J U L 1 8 , 1 9 8 9 f o r C C i d = S N A H o n G 1 8 4 1 O B N T B E Q U 1 2 5 , T 1 8 4 2 P P N Z E Q U 1 3 0 , T 1 8 4 3 A T I M 2 E Q U 1 5 0 , T 1 8 4 4 A T I M E E Q U 1 5 1 , T 1 8 4 5 A R A T E E Q U 1 5 2 , T 1 8 4 6 D O S D L E Q U 1 5 5 , T 1 8 4 7 D L E Q U 1 5 6 , T 1 8 4 8 D E L A P E Q U 1 6 0 , T 1 8 4 9 D E L P P E Q U 1 6 1 , T 1 8 4 9 . 2 S P O P P E Q U 1 6 2 , T 1 8 4 9 . 4 I N S P P E Q U 1 6 3 , T 1 8 4 9 . 6 E L C P P E Q U 1 6 4 , T 1 8 4 9 . 8 E M C P P E Q U 1 6 5 , T 1 8 5 0 U N T O T E Q U 1 6 8 , T 1 8 5 1 P P T O T E Q U 1 6 9 , T 1 8 5 2 N B T O T E Q U 1 7 0 , T 1 8 5 3 S H T O T E Q U 1 7 1 , T 1 8 5 4 P D T O T E Q U 1 7 2 , T 1 8 5 5 * 1 8 5 6 * 1 8 5 7 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 1 8 5 8 " f u n c t i o n s 1 8 5 9 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 1 8 6 0 * 1 8 6 1 * G e o g t o A P c a t e g o r y f o r S p o n t . d e l i v e r i e s 1 8 6 2 * f u n c t i o n § 1 - 3 1 8 6 3 1 F U N C T I O N R N 2 5 3 , D 8 1 8 6 4 0 . 5 3 1 , 1 / 0 . 5 6 2 , 2 / 0 . 7 1 1 , 3 / 0 . 7 4 7 , 4 / 0 . 8 1 3 , 5 / 0 . 8 8 2 , 6 / 0 . 9 0 3 , 7 / 1 . 0 , 8 1 8 6 5 2 F U N C T I O N R N 2 , D 8 1 8 6 6 0 . 4 0 8 , 1 / 0 . 4 6 5 , 2 / 0 . 5 9 9 , 3 / 0 . 6 8 3 , 4 / 0 . 7 4 8 , 5 / 0 . 8 0 9 , 6 / 0 . 8 4 3 , 7 / 1 . 0 , 8 1 8 6 7 3 F U N C T I O N R N 3 , D 8 1 8 6 8 0 . 1 7 5 , 1 / 0 . 3 1 5 , 2 / 0 . 5 0 8 , 3 / 0 . 5 9 6 , 4 / 0 . 6 3 1 , 5 / 0 . 6 4 9 , 6 / 0 . 7 0 2 , 7 / 1 . 0 , 8 1 8 6 9 * 1 8 7 0 * G e o g t o A P c a t e g o r y f o r I n s t . d e l i v e r i e s 1 8 7 1 * f u n c t i o n s # 4 - 6 1 8 7 2 4 F U N C T I O N R N 4 , D 8 1 8 7 3 0 . 5 1 9 , 1 / 0 . 5 4 8 , 2 / 0 . 6 9 2 , 3 / 0 . 7 5 , 4 / 0 . 7 8 8 , 5 / 0 . 8 7 5 , 6 / 0 . 9 1 3 , 7 / 1 . 0 , 8 1 8 7 4 5 F U N C T I O N R N 5 , D 8 1 8 7 5 0 . 3 6 6 , 1 / 0 . 4 3 6 , 2 / 0 . 6 6 1 , 3 / 0 . 7 3 1 , 4 / 0 . 7 4 5 , 5 / 0 . 8 3 , 6 / 0 . 8 4 4 , 7 / 1 . 0 , 8 1 8 7 6 6 F U N C T I O N R N 6 , D 7 1 8 7 7 0 . 2 , 1 / 0 . 4 , 3 / 0 . 5 , 4 / 0 . 6 , 5 / 0 . 7 , 6 / 0 . 8 , 7 / 1 . 0 , 8 1 8 7 8 * 1 8 7 9 * G e o g t o A P c a t e g o r y f o r E l e c C - s e c t i o n s 1 8 8 0 * f u n c t i o n s 1 1 - 1 3 1 8 8 1 1 1 F U N C T I O N R N 7 , D 5 1 8 8 2 0 . 0 9 0 , 1 / 0 . 1 3 5 , 5 / 0 . 2 3 9 , 6 / 0 . 2 9 9 , 7 / 1 . 0 , 8 1 8 8 3 1 2 F U N C T I O N R N 8 , D 5 1 8 8 4 0 . 1 4 0 , 1 / 0 . 2 1 0 , 4 / 0 . 3 5 0 , 5 / 0 . 3 9 7 , 6 / 1 . 0 , 8 1 8 8 5 1 3 F U N C T I O N R N 9 , D 4 1 8 8 6 0 . 1 1 1 , 5 / 0 . 2 2 2 , 6 / 0 . 3 3 3 , 7 / 1 . 0 , 8 1 8 8 7 * 1 8 8 8 * G e o g t o A P c a t e g o r y f o r E m C - s e c t i o n s 1 8 8 9 * f u n c t i o n s 1 4 - 1 6 1 8 9 0 1 4 F U N C T I O N R N 1 0 , D 8 1 8 9 1 0 . 2 8 8 , 1 / 0 . 3 3 6 , 2 / 0 . 5 8 6 , 3 / 0 . 6 5 3 , 4 / 0 . 7 2 , 5 / 0 . 7 3 9 , 6 / 0 . 8 0 8 , 7 / 1 . 0 , 8 1 8 9 2 1 5 F U N C T I O N R N 1 1 , D 8 1 8 9 3 0 . 2 8 6 , 1 / 0 . 3 1 8 , 2 / 0 . 3 6 6 , 3 / 0 . 4 4 5 , 4 / 0 . 6 5 1 , 5 / 0 . 6 9 9 , 6 / 0 . 7 9 4 , 7 / 1 . 0 , 8 1 8 9 4 1 6 F U N C T I O N R N 1 2 , D 8 Appendix D. The Grace Hospital Simulation Model Code 162 L i s t i n g 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 0.048,1/0.191,2/0.381,3/0.429,4/0.477,5/0.572,6/0.667,7/1.0,8 * *Geog to AP category for Undelivered mothers * functions 24-26 24 FUNCTION RN13,D8 0.352,1/0.443,2/0.488,3/0.533,4/0.613,5/0.67,6/0.806,7/1.0,8 25 FUNCTION RN14,D8 0.384,1/0.521,2/0.589,3/0.616,4/0.643,5/0.657,6/0.78,7/1.0,8 26 FUNCTION RN15,D8 0.235,1/0.382,2/0.441,3/0.5,4/0.647,5/0.676,6/0.764,7/1.0,8 * •Delivery Type to PPcat * functions # 31-36 RN16,D2 31 FUNCTION 0.925,1/1.0,2 32 FUNCTION 0.831,3/1.0,4 33 FUNCTION 0.891,5/1.0,6 34 FUNCTION 0.814,7/1.0,8 35 FUNCTION 1.0,9 36 FUNCTION 1.0,10 RN17,D2 RN18,D2 RN19,D2 RN20,D1 RN21,D1 * APcat to Baby 1 Health * functions # 51-58 51 FUNCTION RN22,D4 0.01,1/0.04,2/0.992,3/1.0,4 52 FUNCTION RN23,D4 0.18,1/0.629,2/0.64,3/1.0,4 53 FUNCTION RN24,D4 0.036, 1/0.196,2/0.966,3/1.0, 4 54 FUNCTION RN25,D4 0.12,1/0.289,2/0.972,3/1.0,4 55 FUNCTION RN26,D4 0.022,1/0.16,2/0.994,3/1.0,4 56 FUNCTION RN27,D4 0.264,1/0.333,2/0.944,3/1.0,4 57 FUNCTION RN28,D4 0.181,1/0.446,2/0.844,3/1.0,4 58 FUNCTION RN29,D4 0.016,1/0.083,2/0.979,3/1.0,4 * * health of tw i n / t r i p l e t * function # 60 60 FUNCTION RN30,D4 0.225,1/0.6,2/0.775,3/1.0,4 * •random number of delivered mothers to arrive at Grace next month 70 FUNCTION RN31,C2 0.0,607/1.0,626 * •% of mothers assign the various delivery types 71 FUNCTION RN32,D4 0.6483,SPONT/0.8102,INST/0.8355,ELC/1.0,EMC Appendix D. The Grace Hospital Simulation Model Code 163 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 1953 *random time in minutes into a day 1954 72 FUNCTION RN33,C2 1955 0.0,0/1.0,1441 1956 * 1957 *day of the month 1 to 31 1958 73 FUNCTION RN34,C2 1959 0.0,1/1.0,32 1960 * 1961 *random time between 15-20 (relative to 0AM start time) 1962 76 FUNCTION RN35,C2 1963 0.0,900/1.0,1201 1964 * 1965 *random time between 6-14 (relative to 0AM start time) 1966 77 FUNCTION RN36,C2 1967 0.0,360/1.0,841 1968 * 1969 "delivery type to geog. location 1970 81 FUNCTION RN37,D3 1971 0.57,1/0.924,2/1.0,3 1972 82 FUNCTION RN38,D3 1973 0.562,1/0.946,2/1.0,3 1974 83 FUNCTION RN39,D3 1975 0.563,1/0.924,2/1.0,3 1976 84 FUNCTION RN40,D3 1977 0.553,1/0.888,2/1.0,3 1978 85 FUNCTION RN41,D3 1979 0.429,1/0.762,2/1.0,3 1980 86 FUNCTION RN42,D3 1981 0.451,1/0.825,2/1.0,3 1982 ******************************************* 1983 *TRANSFER FUNCTIONS 1984 ************* 1985 * 1986 "transfer location translation function 1987 100 FUNCTION P9,D17 1988 l,ADM/2,DOS/3,AP/4,APLOW/5,APHIG/6,APOR/7,APPAR/8,LOW/ 1989 9,HIGH/10,OR/11,PAR/12,PP/ 1990 13,PPOR/14,PPPAR/15,DIS/18,STILL/20,DELIV 1991 * 1992 "transfer location translation function for Day of Delivery 1993 98 FUNCTION P5,L6 1994 1,DARB/2,DBAL/3,DCED/4,DDOG/5,DEVE/6,DFIR 1995 1996 "transfer location translation function for Post Partum 1997 99 FUNCTION P5,L6 1998 1,ARB/2,BAL/3,CED/4,DOG/5,EVE/6,FIR 1999 * 2000 "transfer location translation function for babies 2001 96 FUNCTION P9,L6 2002 l,ADMB/2,LRN/3,HRN/4,OBN/5,PPN/6,DISB 2003 * 2004 "transfer location translation function for babies in Postpartum 2005 97 FUNCTION P5,L6 2006 1,ARBN/2,BALN/3,CEDN/4,DOGN/5,EVEN/6,FIRN 2007 * 2008 * 2009 95 FUNCTION P10,D4 2010 4,APLF/5,APHF/8,LOWF/9,HIGF Appendix D. The Grace Hospital Simulation Model Code L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 2011 * 2012 94 FUNCTION P5,D4 2013 4,DOG11/5,EVE11/10,DDG11/11,DEV11 2014 * 2015 93 FUNCTION P5,D12 2016 1,ARB1/2,BAL1/3,CED1/4,D0G1/5,EVE1/6,FIR1/7,DARB1/8,DBAL1/ 2017 9,DCED1/10,DDOG1/11,DEVE1/12,DFIR1 2018 * 2019 92 FUNCTION P10,D2 2020 4,APASU/8,ASSU 2021 * 2022 91 FUNCTION P10,D2 2023 2,DOST/12,PPT2 2024 * 2025 90 FUNCTION P10,D2 2026 2,DTRIN/12,TREIN 2027 * 2028 89 FUNCTION P10,D5 2029 4,APLP1/7,APPF/8,LP1/11,PARF/14,PPPF 2030 * 2031 88 FUNCTION P10,D2 2032 4,APLOT/8,LPOUT 2033 * 2034 "Admission for APcat (UNDEL) 2035 * functions # 101-108 2036 101 FUNCTION RN43.D4 2037 0.060,3/0.627,4/0.672,5/1.0,20 2038 102 FUNCTION RN44,D3 2039 0.043,3/0.695,4/1.0,5 2040 103 FUNCTION RN45,D3 2041 0.273,3/0.818,4/1.0,5 2042 104 FUNCTION RN46,D3 2043 0.125,3/0.875,4/1.0,5 2044 105 FUNCTION RN47,D4 2045 0.500,3/0.643,4/0.857,5/1.0,20 2046 106 FUNCTION RN48,D3 2047 0.286,3/0.857,4/1.0,20 2048 107 FUNCTION RN49,D3 2049 0.708,4/0.916,5/1.0,20 2050 108 FUNCTION RN50,D4 2051 0.366,3/0.854,4/0.952,5/1.0,20 2052 * 2053 "Admission for PPonly 2054 * function # 109 2055 109 FUNCTION RN51,D3 2056 0.476,8/0.571,9/1.0,12 2057 * 2058 ************ 2059 "ANTE PARTUM 2060 * 2061 "from AP for Undeliveried mothers 2062 * functions # 111-118 2063 111 FUNCTION RN52,D3 2064 0.063,5/0.084,8/1.0,15 2065 112 FUNCTION RN53,D3 2066 0.200,5/0:233,6/1.0,15 2067 113 FUNCTION RN54,D4 2068 0.188,4/0.313,5/0.376,9/1.0,15 Appendix D. The Grace Hospital Simulation Model Code 165 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2069 114 FUNCTION RN55,D2 2070 0.200,5/1.0,15 2071 115 FUNCTION RN56,D1 2072 1.0,15 2073 116 FUNCTION RN57,D2 2074 0.143,4/1.0,15 2075 117 FUNCTION RN58,D3 2076 0.042,4/0.084,5/1 .0,15 2077 118 FUNCTION RN59,D3 2078 0.044,5/0.133,6/1 .0,15 2079 * 2080 *from APLOW 2081 * i 2082 121 FUNCTION RN60,D2 2083 0.887,3/1.0,5 2084 122 FUNCTION RN61,D2 2085 0.44,3/1.0,5 2086 123 FUNCTION RN62,D2 2087 0.851,3/1.0,5 2088 124 FUNCTION RN63,D1 2089 1.0,3 2090 125 FUNCTION RN64,D1 2091 1.0,3 2092 126 FUNCTION RN65,D2 2093 0.875,3/1.0,5 2094 127 FUNCTION RN66,D3 2095 0.759,3/0.966,5/1 .0,6 2096 128 FUNCTION RN67,D2 2097 0.8,3/1.0,5 2098 * 2099 *from APHIGH 2100 * 2101 131 FUNCTION RN68,D2 2102 0.938, 3/1 .0,4 2103 132 FUNCTION RN69,D1 2104 1.0,3 2105 133 FUNCTION RN70,D2 2106 0.95,3/1.0,4 2107 134 FUNCTION RN71,D2 2108 0.889,3/1.0,4 2109 135 FUNCTION RN72,D2 2110 0.933,3/1.0,4 2111 136 FUNCTION RN73,D1 2112 1.0,3 2113 137 FUNCTION RN74,D1 2114 1.0,3 2115 138 FUNCTION RN75,D2 2116 0.95,3/1.0,6 2117 * 2118 *from APPAR 2119 * 2120 150 FUNCTION RN76,D2 2121 0.625,3/1.0,5 2122 * 2123 *from AP f o r d e l i v e r e d mo 2124 * 2125 161 FUNCTION RN77,D2 2126 0.05,5/1.0,19 f u n c t i o n s # 121-128 f u n c t i o n s # 131-138 f u n c t i o n # 150 f u n c t i o n s # 161-168 Appendix D. The Grace Hospital Simulation Model Code 166 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2127 162 FUNCTION RN7 8,D2 2128 0.267,5/1.0,19 2129 163 FUNCTION RN79,D3 2130 0.021,4/0.125,5/1 .0,19 2131 164 FUNCTION RN80,D3 2132 0.042,4/0.125,5/1 .0,19 2133 165 FUNCTION RN81,D2 2134 0.273,5/1.0,19 2135 166 FUNCTION RN82,D3 2136 0.130,4/0.348,5/1 .0,19 2137 167 FUNCTION RN83,D4 2138 0.042,4/0.333,5/0 .375,6/1 .0,19 2139 168 FUNCTION RN84,D3 2140 0.034,4/0.138,5/1 .0, 19 2141 * 2142 * 2143 •Admission f o r APcat ( d e l i v e r i e s ) 2144 * f u n c t i o n s 2145 171 FUNCTION RN85,D4 2146 0.004,3/0.034,4/0 .040,5/1 .0,20 2147 172 FUNCTION RN86,D3 2148 0.185,4/0.222,5/1 .0,20 2149 173 FUNCTION RN87,D4 2150 0.011,3/0.217,4/0 .248,5/1 .0,20 2151 174 FUNCTION RN88,D4 2152 0.118,3/0.279,4/0 .338,5/1 .0,20 2153 17 5 FUNCTION RN89,D4 2154 0.133,3/0.160,4/0 .240,5/1 .0,20 2155 176 FUNCTION RN90,D4 2156 0.110,3/0.219,4/0 .247,5/1 .0,20 2157 177 FUNCTION RN91,D4 2158 0.070,3/0.326,4/0 .396,5/1 .0,20 2159 178 FUNCTION RN92,D4 2160 0.076,3/0.176,4/0 .194,5/1 .0,20 2161 * 2162 * * * * * * * * * * * * * * * 2163 •DELIVERY SUITE 2164 •from LOW 2165 * f u n c t i o n s 2166 201 FUNCTION RN93,D3 2167 0.1,9/0.11,10/1.0,12 2168 202 FUNCTION RN94,D3 2169 0.126,9/0.234,10/1.0,12 2170 203 FUNCTION RN95,D2 2171 0.222,9/1.0,10 2172 204 FUNCTION RN96,D2 2173 0.200,9/1.0,10 2174 205 FUNCTION RN97,D3 2175 0.2,10/0.8,12/1.0 ,15 2176 206 FUNCTION RN98,D2 2177 0.042,9/1.0,15 2178 209 FUNCTION RN99,D1 2179 1.0,2 2180 * 2181 •from HIGH 2182 * f u n c t i o n s 2183 211 FUNCTION RN100,D3 2184 0.079,8/0.09,10/1 .0,12 # 171-178 #. 211-216 Appendix D. The Grace Hospital Simulation Model Code L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on 2185 2186 2187 2188 2189 2190 2191 2192 2193 2194 2195 2196 2197 2198 2199 2200 2201 2202 2203 2204 2205 2206 2207 2208 2209 2210 2211 2212 2213 2214 2215 2216 2217 2218 2219 2220 2221 2222 2223 2224 2225 2226 2227 2228 2229 2230 2231 2232 2233 2234 2235 2236 2237 2238 2239 2240 2241 2242 212 FUNCTION RN101,D3 0.107,8/0.161,10/1.0,12 213 FUNCTION RN102,D1 1.0,10 214 FUNCTION RN103,D3 0.052,8/0.896,10/1.0,12 215 FUNCTION RN104,D2 0.5,12/1.0,15 216 FUNCTION RN105,D1 1.0,15 219 FUNCTION RN106,D1 1.0,10 functions # 221-225 RN107,D1 *from OR * 221 FUNCTION 1.0,11 222 FUNCTION RN108,D5 0.544,8/0.595,9/0.838,11/0.983,12/1.0,15 223 FUNCTION RN109,D1 1.0,11 224 FUNCTION RN110,D1 1.0,11 225 FUNCTION RN111,D2 0.5,9/1.0,11 *from PAR * functions # 231-235 231 FUNCTION RN112,D2 0.083, 9/1.0,12 232 FUNCTION RN113,D1 1.0,12 233 FUNCTION RN114,D2 0.008, 9/1.0,12 234 FUNCTION RN115,D2 0.043, 9/1.0,12 235 FUNCTION RN116,D1 1.0,9 'from day of surgery (DOS) 249 FUNCTION 0.069,9/1.0,10 function # 249 RN117,D2 *entry to Labour and Delivery from the AP subsection * functions 251-256 251 FUNCTION RN118,D3 0.319,8/0.957,9/1.0,10 252 FUNCTION RN119,D2 0.3,8/1.0,9 253 FUNCTION RN120,D2 0.167,9/1.0,10 254 FUNCTION RN121,D3 0.25,8/0.75,9/1.0,10 256 FUNCTION RN122,D2 0.5,8/1.0,9 * •entry to Labour and Delivery from admitting Appendix D. The Grace Hospital Simulation Model Code 168 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2243 * f u n c t i o n s 261-266 2244 261 FUNCTION RN123,D2 2245 0.916,8/1.0,9 2246 262 FUNCTION RN124,D2 2247 0.877,8/1.0,9 2248 263 FUNCTION RN125,D2 2249 0.818,8/1.0,9 2250 264 FUNCTION RN126,D2 2251 0.868,8/1.0,9 2252 265 FUNCTION RN127,D2 2253 0.833,8/1.0,9 2254 266 FUNCTION RN128,D2 2255 0.793,8/1.0,9 2256 269 FUNCTION RN129,D2 2257 0.706,2/1.0,8 2258 * 2259 ******************** 2260 *POST PARTUM SECTION 2261 *from PP 2262 * f u n c t i o n s # 301-309 2263 301 FUNCTION RN130,D2 2264 0.039,13/1.0,15 2265 302 FUNCTION RN131,D2 2266 0.063,13/1.0,15 2267 303 FUNCTION RN132,D2 2268 0.06,13/1.0,15 2269 304 FUNCTION RN133,D1 2270 1.0,15 2271 305 FUNCTION RN134,D2 2272 0.019,13/1.0,15 2273 306 FUNCTION RN135,D1 2274 1.0,15 2275 307 FUNCTION RN136,D1 2276 1.0,15 2277 308 FUNCTION RN137,D2 2278 0.056,13/1.0,15 2279 309 FUNCTION RN138,D1 2280 1.0,15 2281 * 2282 2283 2284 * 2285 " t r a n s f e r f u n c t i o n s f o r babies 2286 *from LRN 2287 * f u n c t i o n s # 401-405 2288 401 FUNCTION RN139,D2 2289 0.125,4/1.0,5 2290 402 FUNCTION RN140,D2 2291 0.148,4/1.0,5 2292 403 FUNCTION RN141,D3 2293 0.062,4/0.995,5/1.0,6 2294 404 FUNCTION RN142,D1 2295 1.0,6 2296 405 FUNCTION RN143,D1 2297 1.0,5 2298 * 2299 *from HRN 2300 * f u n c t i o n s #411-415 Appendix D. The Grace Hospital Simulation Model Code L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2301 411 FUNCTION RN144,D4 2302 0.03,2/0.575,4/0.908,5/1.0,6 2303 412 FUNCTION RN145,D2 2304 0.338,4/1.0,5 2305 413 FUNCTION RN146,D3 2306 0.009,2/0.121,4/1.0,5 2307 414 FUNCTION RN147,D1 2308 1.0,6 2309 415 FUNCTION RN148,D1 2310 1.0,5 2311 2312 *from OBN 2313 * f u n c t i o n s # 421-425 2314 421 FUNCTION RN149,D2 2315 0.778,5/1.0,6 2316 422 FUNCTION RN150,D2 2317 0.9,5/1.0,6 2318 423 FUNCTION RN151,D2 2319 0.981,5/1.0,6 2320 425 FUNCTION RN152,D2 2321 0.25,5/1.0,6 2322 * 2323 *from PPN 2324 * f u n c t i o n s #431-435 2325 431 FUNCTION RN153,D2 2326 0.064,4/1.0,6 2327 432 FUNCTION RN154,D2 2328 0.015,4/1.0,6 2329 433 FUNCTION RN155,D2 2330 0.014,4/1.0,6 2331 435 FUNCTION RN156,D2 2332 0.083,4/1.0,6 2333 * 2334 "admission f o r BABIES 2335 * f u n c t i o n s # 501-505 2336 501 FUNCTION RN157,D4 2337 0.283,2/0.906,3/0.981,4/1.0,5 2338 502 FUNCTION RN158,D4 2339 0.406,2/0.895,3/0.955,4/1.0,5 2340 503 FUNCTION RN159,D4 2341 0.599,2/0.952,3/0.973,4/1.0,5 2342 504 FUNCTION RN160,D2 2343 0.146,2/1.0,3 2344 505 FUNCTION RN161,D3-2345 0.087,2/0.739,4/1.0,5 2346 * 2347 ******************************************************** 2348 "LENGTH OF STAY FUNCTIONS 2349 ************* 2350 * 2351 "ANTE PARTUM SECTION (LOS) 2352 " i n AP 2353 * f u n c t i o n s # 1111-1118 2354 1111 FUNCTION RN162,C13 2355 0.0,200/0.229,1200/0.354,2000/0.542,3000/0.667,4000/0.708,5000/ 2356 0.771,6000/0.812,7000/0.917,12000/0.937,17000/0.958,20000/ 2357 0.979,25000/1.0,32000 2358 1112 FUNCTION RN163,C14 Appendix D. The Grace Hospital Simulation Model Code 170 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2359 0.0,200/0.100,1200/0.267,2200/0.433,3000/0.434,4000/0.500,5000/ 2360 0.600,6000/0.633,9000/0.767,13000/0.833,14000/0.900,20000/ 2361 0.933,23000/0.967,26000/1.0,70000 2362 1113 FUNCTION RN164,C11 2363 0.0,200/0.125,1200/0.312,2050/0.375,3000/0.437,4000/0.562,5000/ 2364 0.750,6000/0.812,11000/0.875,22000/0.876,35000/1.0,60000 2365 1114 FUNCTION RN165,C5 2366 0.0,200/0.400,1200/0.600,2000/0.800,3000/1.0,7000 2367 1115 FUNCTION RN166,C10 2368 0.0,2500/0.083,3500/0.084,5000/0.250,6800/0.417,9000/ 2369 0.500,10000/0.583,13000/0.833,16000/0.917,23000/1.0,51000 2370 1116 FUNCTION RN167,C6 2371 0.0,1000/0.286,2000/0.429,3000/0.714,7000/0.857,8000/1.0,32000 2372 1117 FUNCTION RN168,C14 2373 0.0,200/0.042,1200/0.125,2000/0.333,3000/0.417,4000/0.542,5000/ 2374 0.583,6000/0.708,7000/0.750,8000/0.751,10000/0.833,11000/ 2375 0.917, 13000/0.958,28000/1.0,50000 2376 1118 FUNCTION RN169,C16 2377 0.0,200/0.133,1200/0.267,2000/0.311,3000/0.4 67,4000/0.64 4,5000/ 2378 0.667,6000/0.689,7000/0.756,8000/0.778,9000/0.822,14000/ 2379 0.911,18000/0.912,25000/0.933,28000/0.956,31000/1.0,55000 2380 * 2381 * i n APLOW 2382 * f u n c t i o n s # 1121-1128 2383 1121 FUNCTION RN170,C19 2384 0.0,0/0.094,50/0.208,100/0.358,150/0.566,200/0.642,250/0.717,300/ 2385 0.736,350/0.792,400/0.849,450/0.85,600/0.925,650/0.926,800/ 2386 0.943,850/0.962,900/0.963,1150/0.981,1200/0.982,1450/1.0,1500 2387 1122 FUNCTION RN171,C11 2388 0.0,0/0.08,50/0.24,100/0.4,150/0.56,200/0.84,250/0.88,300/0.92,350/ 2389 0.96,400/0.961,800/1.0,850 2390 1123 FUNCTION RN172,C16 2391 0.0,0/0.001,50/0.064,100/0.298,150/0.596,200/0.66,250/0.745,300/ 2392 0.872,350/0.894,400/0.915,450/0.916,800/0.936,850/0.957,900/ 2393 0.96,1000/0.979,1100/1.0,1500 2394 1124 FUNCTION RN173,C10 2395 0.0,0/0.105,50/0.211,100/0.474,150/0.737,200/0.75,250/0.842,300 2396 0.895,350/0.947,600/1.0,800 2397 1125 FUNCTION RN174,C4 2398 0.0,0/0.4,50/0.6,100/1.0,300 2399 1126 FUNCTION RN175,C9 2400 0.0,0/0.062,50/0.25,100/0.562,150/0.75,200/0.812,350/0.875,600/ 2401 0.937,700/1.0,800 2402 1127 FUNCTION RN176,Clr 2403 0.0,0/0.103,50/0.207,100/0.448,150/0.483,200/0.69,250/0.724,300/ 2404 0.828,350/0.897,450/0.966,650/1.0,2000 2405 1128 FUNCTION RN177,C11 2406 0.0,0/0.057,50/0.143,100/0.314,150/0.543,200/0.743,250/0.857,300/ 2407 0.886,450/0.914,700/0.971,750/1.0,850 2408 * 2409 * i n APHIG 2410 * f u n c t i o n s # 1131-1138 2411 1131 FUNCTION RN178,C18 2412 0.0,100/0.062,150/0.125,200/0.126,250/0.25,300/0.312,350/0.313,400 2413 0.437,450/0.5,500/0.501,650/0.562,700/0.687,750/0.75,800/0.751,1150 2414 0.812,1200/0.875,1350/0.937,1500/1.0,2000 2415 1132 FUNCTION RN179,C21 2416 0.0,150/0.03,200/0.091,250/0.152,300/0.212,350/0.213,400/0.242,450 Appendix D. The Grace Hospital Simulation Model Code 171 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G .2417 0.273,500/0.333,550/0.455,600/0.456,650/0.606,700/0.636,750/ 2418 0.667,800/0.697,850/0.727,900/0.788,1150/0.818,1400/0.848,1500/ 2419 0.94,1600/1.0,5000 2420 1133 FUNCTION RN180,C15 2421 0.0,0/0.05,50/0.1,100/0.15,150/0.2,250/0.3,350/0.35,450/0.55,500/ 2422 0.6,550/0.65,600/0.75,650/0.8,750/0.85,900/0.9,950/1.0,3000 2423 1134 FUNCTION RN181,C11 2424 0.0,50/0.111,100/0.112,550/0.222,600/0.223,700/0.333,750/0.444,800/ 2425 0.556,850/0.778,950/0.889,1000/1.0,1500 2426 1135 FUNCTION RN182,C15 2427 0.0,0/0.133,50/0.134,150/0.2,200/0.201,350/0.267,400/0.333,450/ 2428 0.334,550/0.467,600/0.667,650/0.668,800/0.8,850/0.867,900/ 2429 0.933,950/1.0,5000 2430 1136 FUNCTION RN183,C11 2431 0.0,150/0.111,200/0.112,500/0.222,550/0.333,600/0.444,650/ 2432 0.445,700/0.556,750/0.667,800/0.8,900/1.0,1050 2433 1137 FUNCTION RN184,C21 2434 0.0,100/0.08,150/0.16,200/0.2,250/0.201,300/0.24,350/0.32,400/ 2435 0.36,450/0.48,500/0.52,550/0.56,600/0.561,750/0.64,800/0.68,900/ 2436 0.76,950/0.8,1050/0.84,1100/0.88,1200/0.92,1300/0.96,1600/1.0,2000 2437 1138 FUNCTION RN185,C19 2438 0.0,0/0.1,50/0.15,100/0.3,150/0.301,250/0.350,300/0.351,350/ 2439 0.4,400/0.45,450/0.5,500/0.55,600/0.6,650/0.65,700/0.75,750/ 2440 0.8,850/0.85,1050/0.9,1150/0.95,1250/1.0,4000 2441 * 2442 * i n APOR 2443 * f u n c t i o n # 1140 2444 1140 FUNCTION RN186,C9 2445 0.0,0/0.001,4 0/0.125,55/0.25,65/0.5,73/0.625,80/0.75,100/0.875,120/ 2446 1.0,200 2447 * 2448 * i n APPAR 2449 * f u n c t i o n # 1150 2450 1150 FUNCTION RN187,C8 2451 0.0,60/0.125,80/0.25,100/0.375,120/0.5,150/0.625,200/0.875,220/1.0,2 2452 * 2453 * 2454 *ANTE PARTUM SECTION (LOS) 2455 * i n AP f o r mothers who w i l l d e l i v e r t h i s s e s s i o n i n h o s p i t a l 2456 * f u n c t i o n s # 1161-1168 2457 1161 FUNCTION RN188,C3 2458 0.0,200/0.750,1200/1.0,2000 2459 1162 FUNCTION RN189,C9 2460 0.0,200/0.250,1200/0.437,2000/0.625,3000/0.687,4000/0.812,5000/ 2461 0.875,6000/0.937,11000/1.0,32000 2462 1163 FUNCTION RN190,C9 24 63 0.0,200/0.633,1200/0.755,2000/0.796,3000/0.797,4000/0.878,5000/ 2464 0.918,9000/0.959,10000/1.0,60000 2465 1164 FUNCTION RN191,C12 2466 0.0,200/0.250,1200/0.375,2000/0.500,3000/0.542,4000/0.543,5000/ 2467 0.625,6000/0.750,7000/0.833,12000/0.875,19000/0.917,21000/ 2468 1.0,40000 2469 1165 FUNCTION RN192,C10 2470 0.0,200/0.409,1230/0.682,2000/0.727,3000/0.728,4000/0.818,5000/ 2471 0.864,6000/0.909,17000/0.955,31000/1.0,55000 2472 1166 FUNCTION RN193,C13 2473 0.0,200/0.458,1300/0.625,2000/0.667,3000/0.708,4000/0.709,9000/ 2474 0.750,10000/0.792,17000/0.833,20000/0.875,21000/0.917,22000/ Appendix D. The Grace Hospital Simulation Model Code 172 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2475 0.958,27000/1.0,50000 2476 1167 FUNCTION RN194,C11 2477 0.0,200/0.214,1200/0.429,2000/0.571,3000/0.607,4000/0.643,5000/ 2478 0.714,9000/0.821,12000/0.857,17000/0.929,21000/1.0,50000 2479 1168 FUNCTION RN195,C8 2480 0.0,200/0.548,1200/0.806,2000/0.807,6000/0.903,9000/0.935,12000/ 2481 0.968,15000/1.0,45000 2482 * 2483 ****************************** 2484 "DELIVERY SUITE SECTION (LOS) 2485 * i n LOW 2486 * f u n c t i o n s # 1201-1206 2487 1201 FUNCTION RN196,C32 2488 0.0,0/0.046,60/0.086,120/0.151,180/0.255,240/0.352,300/0.445,360/ 2489 0.521,420/0.599,480/0.651,540/0.708,600/0.748,660/0.78,720/ 2490 0.807,780/0.826,840/0.857,900/0.876,960/0.894,1020/0.913,1080/ 2491 0. 926, 1140"/0. 945, 1200/0. 951, 1260/0. 964, 1320/0. 968, 1380/0. 971, 1440/ 2492 0.976,1500/0.979,1560/0.987,1620/0.989,1800/0.995,2300/0.998,10000/ 2493 1.0,30000 2494 1202 FUNCTION RN197,C30 2495 0.0,0/0.054,60/0.102,120/0.18,180/0.21,240/0.263,300/0.275,360/ 2496 0.317,420/0.383,480/0.413,540/0.449,600/0.497,660/0.563,720/ 2497 0.611,780/0.647,840/0.683,900/0.743,960/0.76,1020/0.796,1080/ 2498 0.814,1140/0.85,1200/0.88,1260/0.898,1320/0.928,1380/0.94,1440/ 2499 0.952,1500/0.964,1560/0.97,1620/0.982,1680/1.0,2300 2500 1203 FUNCTION RN198,C8 2501 0.0,0/0.333,80/0.444,100/0.555,120/0.666,140/0.777,160/0.888,180/ 2502 1.0,1000 2503 1204 FUNCTION RN199,C33 2504 0.0,0/0.05,50/0.15,100/0.3,150/0.336,200/0.379,250/0.407,300/ 2505 0.436,350/0.437,400/0.471,450/0.486,500/0.514,550/0.593,600/ 2506 0.629,650/0.657,700/0.693,750/0.729,800/0.757,850/0.771,900/ 2507 0.786,950/0.807,1000/0.836,1050/0.85,1100/0.864,1150/0.871,1200/ 2508 0.9,1250/0.907,1300/0.943,1350/0.950,1400/0.957,1450/0.964,1500/ 2509 0.978,1600/1.0,2250 2510 1205 FUNCTION RN200,C7 2511 0.0,0/0.1,60/0.5,120/0.501,180/0.7,240/0.9,300/1.0,480 2512 1206 FUNCTION RN201,C16 2513 0.0,0/0.042,60/0.083,120/0.167,180/0.417,240/0.418,300/0.458,360/ 2514 0.542,420/0.625,480/0.708,540/0.792,600/0.833,660/0.834,720/ 2515 0.917,780/0.958,840/1.0,1800 2516 1209 FUNCTION RN202,C17 2517 0.0,0/0.3,20/0.4,4 0/0.467,60/0.468,80/0.533,100/0.534,120/ 2518 0.6,140/0.601,160/0.7,180/0.701,200/0.733,220/0.767,240/ 2519 0.833,260/0.9,280/0.933,340/1.0,540 2520 2521 * i n HIGH 2522 * f u n c t i o n s # 1211-1216 2523 1211 FUNCTION RN203,C32 2524 0.0,0/0.034,60/0.062,120/0.107,180/0.18,240/0.236,300/0.264,360/ 2525 0 .315 ,420/0.36 , 480/0 . 438 ,540/0.494,600/0.551,660/0 . 596 ,720/0 . 657 ,780 , 2526 0.725,840/0.753,900/0.775,960/0.809,1020/0.826,1080/0.848,1140/ 2527 0.876,1200/0.904,1260/0.927,1320/0.933,1380/0.938,1440/0.955,1500/ 2528 0.961,1560/0.966,1620/0.972,1800/0.978,2000/0.995,3000/1.0,5000 2529 1212 FUNCTION RN204,C30 2530 0.0,0/0.054,60/0.071,120/0.107,180/0.161,240/0.179,300/0.214,360/ 2531 0.25,420/0.357,540/0.411,600/0.429,660/0.43,720/0.464,780/0.5,840/ 2532 0 .536,900/0.554,960/0.589,1020/0.625 ,1080/0.732,1140/0.733,1200/ Appendix D. The Grace Hospital Simulation Model Code 173 L i s t i n g of HOSPITAL a t 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2533 0.75,1260/0.768,1320/0.786,1380/0.839,1440/0.84,1500/0.911,1560/ 2534 0.929,1620/0.946,1680/0.982,2200/1.0,3400 2535 1213 FUNCTION RN205,C4 2536 0.0,0/0.6,120/0.8,240/1.0,750 2537 1214 FUNCTION RN206,C21 2538 0.0,0/0.197,90/0.342,180/0.447,270/0.487,360/0.553,450/0.632,540/ 2539 0.658,630/0.711,720/0.75,810/0.776,900/0.829,990/0.855,1080/ 2540 0.868,1170/0.882,1260/0.895,1350/0.921,1440/0.934,1530/0.961,1800/ 2541 0.974,2070/1.0,2520 2542 1215 FUNCTION RN207,C4 2543 0.0,0/0.25,60/0.75,540/1.0,2000 2544 1216 FUNCTION RN208,C7 2545 0.0,240/0.25,300/0.251,420/0.375,4 80/0.376,600/0.5,660/1.0,1000 2546 1219 FUNCTION RN209,C3 2547 0.0,0/0.875,70/1.0,2500 2548 * 2549 * i n OR 2550 * f u n c t i o n s # 1221-1225 2551 1221 FUNCTION RN210,C6 2552 0.0,30/0.167,60/0.5,70/0.583,80/0.833,90/1.0,180 2553 1222 FUNCTION RN211,C12 2554 0.0,30/0.095,40/0.143,50/0.238,60/0.476,70/0.571,80/0.619,90/ 2555 0.81,100/0.857,110/0.905,230/0.952,260/1.0,500 2556 1223 FUNCTION RN212,C18 2557 0.0,20/0.008,30/0.009,40/0.016,50/0.04,60/0.096,70/0.14 4,80/ 2558 0.28,90/0.4,100/0.512,110/0.648,120/0.76,130/0.856,140/0.912,150/ 2559 0.952,160/0.976,170/0.992,220/1.0,230 2560 1224 FUNCTION RN213,C19 2561 0.0,30/0.005,40/0.044,50/0.099,60/0.209,70/0.357,80/0.495,90/ 2562 0.637,100/0.725,110/0.819,120/0.852,130/0.896,140/0.934,150/ 2563 0.962,160/0.967,170/0.973,180/0.984,210/0.995,270/1.0,340 2564 1225 FUNCTION RN214,C3 2565 0.0,80/0.5,125/1.0,225 2566 * 2567 * i n PAR 2568 * f u n c t i o n s # 1231-1236 2569 1231 FUNCTION RN215,C9 2570 0.0,30/0.083,40/0.167,50/0.333,60/0.417,70/0.583,80/0.667,90/ 2571 0.833,100/1.0,220 2572 1232 FUNCTION RN216,C5 2573 0.0,20/0.2,30/0.21,100/0.6,120/1.0,220 2574 1233 FUNCTION RN217,C18 2575 0.0,30/0.008,40/0.016,50/0.088,60/0.176,70/0.328,80/0.464,90/ 2576 0.6,100/0.672,110/0.768,120/0.84,130/0.896,140/0.928,150/ 2577 0.952,160/0.976,170/0.984,180/0.992,310/1.0,560 2578 1234 FUNCTION RN218,C22 2579 0.0,30/0.011,40/0.016,50/0.044,60/0.093,70/0.198,80/0.319,90/ 2580 0.456,100/0.566,110/0.637,120/0.709,130/0.802,140/0.852,150/ 2581 0.907,160/0.918,170/0.934,180/0.951,190/0.956,200/0.962,210/ 2582 0.973,220/0.989,270/1.0,360 2583 1235 FUNCTION RN219,C2 2584 0.0,20/1.0,50 2585 * 2586 * i n DOS 2587 * f u n c t i o n # 1249 2588 1249 FUNCTION RN220,C28 2589 0.0,0/0.01,50/0.108,100/0.284,150/0.441,200/0.490,250/0.491,300/ 2590 0.500,350/0.501,500/0.510,550/0.511,650/0.520,700/0.529,750/ Appendix D. The Grace Hospital Simulation Model Code 174 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2591 0.530,800/0.549,850/0.559,900/0.569,950/0.608,1000/0.627,1050/ 2592 0.706,1100/0.765,1150/0.843,1200/0.863,1250/0.902,1300/0.941,1350/ 2593 0.971,1400/0.98,1450/1.0,1500 2594 * 2 5 9 5 * * * * * * * * * * * * * * * * * * * * 2596 *POST PARTUM SECTION 2597 * i n PP 2598 *LOS i n PP before a PP OR v i s i t 2599 * f u n c t i o n # 1299 2600 1299 FUNCTION RN221,C14 2601 0.0,0/0.171,500/0.2,1000/0.4,1500/0.629,2000/0.714,2500/0.857,3000/ 2602 0.858,3500/0.886,4000/0.943,4500/0.944,5500/0.971,6000/0.972,7000/ 2603 1.0,7500 2604 *random a d d i t i o n a l time i n PP a f t e r 0 AM 2605 * f u n c t i o n # 1300 2606 1300 FUNCTION RN222,C20 2607 0.0,-800/0.004,0/0.006,300/0.007,4 80/0.009,540/0.077,600/0.129,660/ 2608 0.312,720/0.557,780/0.723,84 0/0.841,900/0.898,960/0.933,1020/ 2609 0.953,1080/0.962,1140/0.975,1200/0.988,1260/0.996,1320/0.999,1380/ 2610 1.0,1440 2611 2612 *number of days spent i n Post Partum 2613 * f u n c t i o n s # 1301-1309 2614 1301 FUNCTION RN223,D8 2615 0.051,0/0.261,1/0.836,2/0.959,3/0.991,4/0.996,5/0.998,6/1.0,9 2616 1302 FUNCTION RN224,D5 2617 0.017,0/0.184,1/0.801,2/0.968,3/1.0,4 2618 1303 FUNCTION RN225,D7 2619 0.045,0/0.199,1/0.814,2/0.949,3/0.987,4/0.994,7/1.0,12 2620 1304 FUNCTION RN226,D3 2621 0.037,1/0.593,2/1.0,3 2622 1305 FUNCTION RN227,D6 2623 0.019,2/0.208,3/0.868,4/0.953,5/0.991,6/1.0,13 2624 1306 FUNCTION RN228,D5 2625 0.077,2/0.231,3/0.769,4/0.923,5/1.0,7 2626 1307 FUNCTION RN229,D8 2627 0.007,0/0.020,1/0.046,2/0.222,3/0.882,4/0.954,5/0.987,6/1.0,7 2628 1308 FUNCTION RN230,D7 2629 0.086,3/0.657,4/0.828,5/0.885,6/0.942,7/0.971,8/1.0,13 2630 1309 FUNCTION RN232,D6 2631 0.235,0/0.294,1/0.412,2/0.647,3/0.941,4/1.0,6 2632 * 2633 * i n PPOR 2634 * f u n c t i o n # 1310 2635 1310 FUNCTION RN233,C13 2636 0.0,20/0.028,30/0.194,40/0.306,50/0.444,60/0.556,70/0.694,80/ 2637 0.806,90/0.861,100/0.889,110/0.89,120/0.972,130 / l.0,160 2638 * 2639 * i n PPPAR 2640 * f u n c t i o n # 1320 2641 1320 FUNCTION RN234,C18 2642 0.0,40/0.028,50/0.083,60/0.194,70/0.25,80/0.278,90/0.417,100/ 2643 0.611,110/0.694,120/0.778,130/0.833,140/0.861,150/0.917,160/ 2644 0.918,200/0.944,210/0.945,260/0.972,270/1.0,310 2645 * 2646 ******************************************** 2647 *LOS f o r Babies 2648 * i n LRN Appendix D. The Grace Hospital Simulation Model Code 175 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 2649 * functions # 1401-1405 2650 1401 FUNCTION RN235,C17 2651 0,0/0.0625,35/0.125,47/0.1875,66/0.25,79/0.3125,83/0.375,86/ 2652 0.4375,88/0.5,90/0.5625,99/0.625,111/0.6875,121/0.75,129/ 2653 0.8125,134/0.875,140/0.9375,150/1.0,170 2654 1402 FUNCTION RN236,C11 2655 0.0,0/0.0555,30/0.241,60/0.482,90/0.704,120/0.852,150/0.87,180/ 2656 0.925,210/0.96,240/0.981,270/1.0,300 2657 1403 FUNCTION RN237,C14 2658 0.0,0/0.0416,30/0.154,60/0.373,90/0.603,120/0.79,150/0.901,190/ 2659 0.955,210/0.972,240/0.977,270/0.986,300/0.997,400/0.999,500/1.0,1000 2660 1404 FUNCTION RN238,C5 2661 0.0,0/0.5,10/0.667,20/0.833,110/1.0,120 2662 1405 FUNCTION RN239,C3 2663 0.0,100/0.5,200/1.0,300 2664 * 2665 * i n HRN 2666 * functions # 1411-1415 2667 1411 FUNCTION RN240,C12 2668 0.0,0/0.242,30/0.394,60/0.485,90/0.606,120/0.788,150/0.879,180/ 2669 0.909,210/0.939,240/0.94,1000/0.97,1300/1.0,1600 2670 1412 FUNCTION RN241,C12 2671 0.0,0/0.138,30/0.277,60/0.477,90/0.615, 120/0.862, 150/0.908, 180/ 2672 0.923,210/0.969,240/0.97,370/0.985,400/1.0,600 2673 1413 FUNCTION RN242,C18 2674 0.0,0/0.077,30/0.174,60/0.316,90/0.4 98,120/0.696,150/0.841,180 2675 0.912,210/0.938,240/0.953,270/0.976,300/0.979,330/0.982,360/ 2676 0.985,430/0.991,530/0.994,620/0.996,750/1.0,1000 2677 1414 FUNCTION RN243,C10 2678 0.0,0/0.743,10/0.771,20/0.8,30/0.801,40/0.857,50/0.886,60/ 2679 0.943,70/0.971,80/1.0,90 2680 2681 * i n OBN 2682 * functions # 1421-1425 2683 1421 FUNCTION RN244,C15 2684 0.0,0/0.185,1000/0.481,2000/0.556,3000/0.593,4000/0.741,5000/ 2685 0.815,6000/0.816,7000/0.852,8000/0.853,12000/0.889,13000/ 2686 0.926,14000/0.927,15000/0.963,16000/1.0,20000 2687 1422 FUNCTION RN245,C17 2688 0.0,0/0.125,400/0.475,800/0.675,1200/0.775,1600/0.8,2000/ 2689 0.801,2800/0.825,3200/0.875,3600/0.876,4000/0.9,4400/ 2690 0.901,5600/0.925,6000/0.95,8000/0.975,10000/0.99,15000/ 2691 1.0,24000 2692 1423 FUNCTION RN246,C21 2693 0.0,0/0.222,250/0.556,500/0.694,750/0.75,1000/0.806,1250/ 2694 0.833,1500/0.852,1750/0.88,2000/0.898,2250/0.917,2500/ 2695 0.935,2750/0.944,3000/0.945,3250/0.954,3500/0.955,3750/ 2696 0.963,4000/0.972,4800/0.981,6500/0.991,8000/1.0,9000 2697 1425 FUNCTION RN247,C18 2698 0.0,0/0.0625,1000/0.125,2000/0.1875,3000/0.25,4000/0.3125,5000/ 2699 0.3126,9000/0.375,10000/0.4375,12000/0.5,15000/0.5625,18000/ 2700 0.625,21000/0.6875,26000/0.75,31000/0.8125,37000/0.875,40000/ 2701 0.9375,42000/1.0,45000 2702 * 2703 * i n PPN 2704 * functions # 1431-1435 2705 1431 FUNCTION RN248,C13 2706 0.0,0/0.0625,1000/0.104,2000/0.208,3000/0.354,4000/0.667,5000/ Appendix D. The Grace Hospital Simulation Model Code L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 for CCid=SNAH on G 2707 0. 771,6000/0.854,7000/0.917,8000/0.9375,9000/0.958,10000/ 2708 0. 959,11000/1.0,12000 2709 1432 FUNCTION RN249,C18 2710 0. 0,0/0 .015,1000/0 .023,2000/0.099,3000/0.366,4000/0.55,5000/ 2711 0. 672,6000/0.756,7000/0.855,8000/0.908,9000/0.923,10000/ 2712 0. 962,11000/0.969, 12000/0.97,13000/0.977,14000/0.985,16000/ 2713 0. 992,20000/1.0,30000 2714 1433 FUNCTION RN250,C16 2715 0. 0,0/0 .017,1000/0 .037,2000/0.09,3000/0.331,4000/0.651,5000/ 2716 0. 752,6000/0.856,7000/0.965,8000/0.983,9000/0.991,10000/ 2717 0. 993,11000/0.997,12000/0.998,13000/0.999,14000/1.0,25000 2718 1435 FUNCTION RN251,C11 2719 0. 0,0/0 .083,1000/0 M67,2000/0.333,3000/0.417,4000/0.5,5000/ 2720 0. 583,5500/0.667,6000/0.833,7000/0.917,8000/1.0,10000 2721 * 2722 * 2723 START 310,NP run for this many days 2724 RESET 2725 INITIAL MX$CLASS(1-8,1-10),0/MH$APPBL(l-5,l-3),0 2726 INITIAL MH$LDPBL(l-5,1-3),0/MH$PPPBL(1-3,1-2),0 2727 INITIAL MH$BABPB(l-4,1),0/MH$RFLAG(1-2,1),0 2728 INITIAL MH$CENSU(1-31,1-10),0/MX$DISCH(1-2,1-3),0 2729 INITIAL MX$CSTEN(1-10,1),0/MX$CSMID(l-10,1) , 0 2730 INITIAL MH$CNUM(l-2,1),0 2731 INITIAL MX$BDEL(l-4,1),0/MX$ORCAT(l-6,l-3),0 2732 INITIAL MX$APNUM(l-2,1-9),0/MX$TRANS(1-16,1-16) ,0 2733 INITIAL MX$BTRAN(l-7,1-7),0 2734 INITIAL XH7, 1 2735 INITIAL XH5,31 2736 START 620 2737 * RESET 2738 * INITIAL MX$CLASS(1-8,1-10),0/MH$APPBL(l-5,l-3),0 2739 * INITIAL MH$LDPBL(l-5,1-3),0/MH$PPPBL(1-3,1-2) ,0 2740 * INITIAL MH$BABPB(l-4,1),0/MH$RFLAG(1-2,1),0 2741 * INITIAL MH$CENSU(1-31,1-10),0/MX$DISCH(1-2,1-3),0 2742 * INITIAL MX$CSTEN(1-10,1),0/MX$CSMID(1-10,1),0 2743 * INITIAL MH$CNUM(l-2,1),0 2744 * INITIAL MX$BDEL(l-4,1),0/MX$ORCAT(l-6,l-3) ,0 2745 * INITIAL MX$APNUM(l-2,1-9),0/MX$TRANS(1-16,1-16),0 2746 * INITIAL MX$BTRAN(l-7,1-7) ,0 2747 * INITIAL XH7,1 2748 * INITIAL XH5,31 2749 * START 62 2750 * RESET 2751 * INITIAL MX$CLASS(1-8,1-10),0/MH$APPBL(l-5,l-3),0 2752 * INITIAL MH$LDPBL(l-5,1-3),0/MH$PPPBL(1-3,1-2),0 2753 INITIAL MH$BABPB(l-4,1),0/MHSRFLAG(1-2,1),0 MH$CENSU(1-31,1-10),0/MX$DISCH(1-2,1-3),0 2754 * INITIAL 2755 * INITIAL MX$CSTEN(1-10,1),0/MX$CSMID(l-10,1),0 2756 * INITIAL MH$CNUM(l-2,1),0 2757 * INITIAL MX$BDEL(l-4,1),0/MX$ORCAT(l-6,l-3),0 2758 * INITIAL MX$APNUM(l-2,1-9),0/MX$TRANS(1-16,1-16) ,0 2759 * INITIAL MX$BTRAN(l-7,1-7) , 0 2760 * INITIAL XH7,1 2761 * INITIAL XH5,31 2762 * START 62 2763 * RESET 2764 * INITIAL MX$CLASS(1-8,1-10),0/MH$APPBL(l-5,l-3),0 Appendix D. The Grace Hospital Simulation Model Code 177 L i s t i n g of HOSPITAL at 14:30:47 on JUL 18, 1989 f o r CCid=SNAH on G 2765 * INITIAL MH$LDPBL(l-5,1-3),0/MH$PPPBL(l-3,1-2),0 2766 * INITIAL MH$BABPB(l-4,1),0/MH$RFLAG(1-2,1),0 2767 * INITIAL MH$CENSU(1-31,1-10),0/MX$DISCH(l-2,l-3),0 2768 * INITIAL MX$CSTEN(1-10,1),0/MX$CSMID(1-10,1),0 2769 * INITIAL MH$CNUM(l-2,1),0 2770 * INITIAL MX$BDEL(l-4,1),0/MX$ORCAT(l-6,l-3),0 2771 INITIAL MX$APNUM(l-2,1-9),0/MX$TRANS(1-16,1-16),0 2772 * INITIAL MX$BTRAN(l-7,l-7),0 2773 * INITIAL XH7,1 2774 * INITIAL XH5,31 2775 * START 62 2776 END 2777 2778 

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