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Forecasting acute-care hospital beds using intra-regional transfers Hastings, Gerald Leslie 1977

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FORECASTING ACUTE-CARE HOSPITAL BED DEMANDS USING INTRA-REGIONAL TRANSFERS by Gerald L e s l i e Hastings B. Comm., University of B r i t i s h Columbia, 1969 A Thesis Submitted In P a r t i a l F u l f i l l m e n t Of The Requirements For The Degree Of MASTER OF SCIENCE in The Faculty of Graduate Studies Department Of Health Care And Epidemiolgy We acce.pt tku tkci>li> cu, ccrn&o fuming to the. KiiqvJjizd. i>ta.n.dcuid University of B r i t i s h Columbia October, 1977 © Gerald L e s l i e Hastings, 1977 In present ing th is thes is in par t ia l fu l f i lment of the requirements for an advanced degree at the Univers i ty of B r i t i s h Columbia, I agree that the L ibrary sha l l make it f ree ly ava i lab le for reference and study. I fur ther agree that permission for extensive copying of th is thes is for scho lar ly purposes may be granted by the Head of my Department or by h is representa t ives . It is understood that copying or p u b l i c a t i o n of th is thes is fo r f i n a n c i a l gain sha l l not be allowed without my wri t ten permission. Gerald Leslie Hastings Department of Health Care and Epidemiology The Univers i ty of B r i t i s h Columbia 2075 Wesbrook Place Vancouver, Canada V6T 1W5 Date 18 October, 1977 1 1 ABSTRACT Governments i n t h i s country have a mandate from t h e i r electorate to obtain the best s o c i a l return from public investment i n health care. Because of escalating c a p i t a l and operating costs, the acute-care-hospital component of health care has recently come under close scrutiny. Accordingly, governments must forecast public demands f o r h o s p i t a l services i n order to plan the most effective and e f f i c i e n t delivery of these expensive h o s p i t a l services. This thesis examines the B r i t i s h Columbia Ministry of Health's current method of forecasting acute-care-bed requirements which has been applied to the Greater Vancouver Regional Hospital D i s t r i c t (G.V.R.H.D.) and then proposes an improved method which accounts f o r the movement of hospital patients from t h e i r d i s t r i c t of residence to a d i s t r i c t providing h o s p i t a l services. A computer forecasting program was designed using the P r o v i n c i a l forecasting method as a base with the addition of a Transfer Matrix that distributes the acute-care patient-days generated by each of the G.V.R.H.D d i s t r i c t s to those d i s t r i c t s that provide hospital services. With t h i s addition, the computer forecasting program better r e f l e c t s the G.V.R.H.D.' current source and d i s t r i b u t i o n of the demand f o r h o s p i t a l service. The computer forecasting program was v e r i f i e d by comparing i t s Standard Forecast to a manually calculated forecast. The program was then used f i r s t l y to analyse the s e n s i t i v i t y of the forecast of Hospital-Bed Requirements to changes i n the values of the Population and Incidence Rate variables, and secondly, to analyse the effects of alternate p o l i c i e s regarding the input values of the program's variables. i i i . F i r s t l y , the s e n s i t i v i t y analysis showed that i f c e r t a i n equal changes are made to the values of input variables, the s e n s i t i v i t y of the output forecast can vary among the d i s t r i c t s . This aspect of the forecast enhances the value of the program as a method of analysing unexpected relationships. Secondly, the policy analysis showed that the computerized forecasting program can quickly produce alternate forecasts that correspond to alternate p o l i c i e s regarding the values selected f o r the program's variables. The policy-maker can then analyse the effects of these p o l i c i e s and thus be i n a better p o s i t i o n to weigh the costs and the benefits involved. For these reasons, the computer forecasting program developed for t h i s thesis i s an improvement over the current method used i n B r i t i s h Columbia. However, the thesis does describe other current techniques that can, and should, now be incorporated i n t o the computer forecasting program to o f f e r more f l e x i b i l i t y when analysing the effects of possible future conditions. Supervisor i v . TABLE OF CONTENTS ABSTRACT i i LIST OF TABLES v LIST OF FIGURES v i i v i i i ACKNOWLEDGEMENTS CHAPTER I. Introduction 1 I I . Problems of Forecasting Acute-Care-Hospital Bed Requirements 5 I I I . The Development of Techniques f o r Forecasting the Demand f o r Acute-Care-Hospital Beds 12 IV. Current Forecasting Methods 23 V. Methodology 34 VI. Experimental Procedures 43 VII. Results 64 VIII. Discussion 81 IX. Summary and Conclusions 93 GLOSSARY 97 BIBLIOGRAPHY 99 APPENDICES A. Computer Forecasting Program 102 B. Standard Forecast 103 V. vi. V I I . LIST OF FIGURES FIGURE 1. Flow Diagram of the Computer Forecasting Program v i i i . ACKNOWLEDGEMENTS I wish to take t h i s opportunity to sincerely thank Dr. John H. Milsum and Mr. Norman K. Barth fo r t h e i r advice and support during the development of t h i s t h e s i s , and Mr. George Moore and Ms. Joan E.E. Wilson f o r the typing of the manuscript. CHAPTER I INTRODUCTION Hospitals are creatures of t h e i r l o c a l community, and often of only segments of the community. In general, they represent the feelings, rather than the considered judgements of t h e i r community. (Brown, 1967) This thesis studies the planning of future acute-care-hospital bed requirements which i s one aspect of planning f o r health services. Although many techniques have been developed to a s s i s t i n the hospital-planning process, t h e i r effectiveness has been lim i t e d by the fact that frequently there have been no s p e c i f i c p o l i c i e s that f i r s t set the objectives f o r the planning process. This study reviews the history of planning f o r future hospital-bed requirements and the conceptual problems inherent i n techniques that forecast future requirements. I t improves upon the forecasting technique used by the B r i t i s h Columbia Ministry of Health which incorporates several generally recognized components but f a l l s short of the state-of-the-art methods of analysing and forecasting the interrelationships among regional population groups and t h e i r hospitals. S p e c i f i c a l l y , the following problems have been addressed i n t h i s thesis: 1. To develop and validate a computerized method of forecasting future acute-care-hospital bed requirements based on the current B r i t i s h Columbia Hospital Programs' method, but with the addition of a matrix to account for patient transfers within a region and, 2. To exainine the s e n s i t i v i t y of the developed method to selected input variables f o r which inaccuracies could occur i n t h e i r predicted values and, 2 . 3. To study the effects of alternate p o l i c y decisions i n the following areas: a. Population b. Incidence Rates of Hospit a l i z a t i o n c. Inflow d. Infra-Regional Patient Transfers e. Hospital Occupancy Percentage. The problems addressed are very narrow i n conceptual scope, but t h e i r resolution depends on a l o g i c a l understanding of t h e i r r e l a t i o n s h i p to the broader concepts of planning health services now discussed. I f our community had unlimited resources to meet i t s perceived health-care needs, there would be no requirement to allocate or r a t i o n resources - no requirement to plan. Because t h i s i s not so, systems have evolved to r a t i o n our l i m i t e d resources within a spectrum ranging from p o l i t i c a l edict to open market with a price system. To the extent that these systems prove e f f e c t i v e , they w i l l balance o v e r a l l community needs now and i n the future. Unfortunately, there i s no general agreement that our resource a l l o c a t i o n systems are e f f e c t i v e . In the health care sector, rapidly r i s i n g costs are usually viewed as a signal that the resource a l l o c a t i o n system i s out of control. The prediction of the Economic Council of Canada,that expenditures on health care and education would t h e o r e t i c a l l y soon consume the entire Canadian Gross National Product unless changes are made,is constantly i n the back-ground (Economic Council of Canada, 1970). Better "planning" and thus better a l l o c a t i o n i s heralded as the answer. But what i s planning? I t i s an a c t i v i t y that has been described as vaguely as the process of thinking before you act (Gottlieb, 1974) and as s p e c i f i c a l l y as the development and implementation of a course of action which i s expected to lead to desired results given the occurrence of expected events (Bergwall et a l . , 1974). Planning i s an a c t i v i t y that i s concerned with the future having resulted from an a l t e r a t i o n of the present or, as i t i s defined f o r t h i s study, i t i s the management of the future. This d e f i n i t i o n of planning implies the setting of goals and the organization of e f f o r t to a t t a i n them, and opens the question of who should plan f o r future health services. Clearly, the agency responsible f o r the supply of resources has a mandate to ensure the most e f f e c t i v e use of those resources - a mandate to plan. There i s much debate i n the United States over t h i s question as the health sector and, s p e c i f i c a l l y , hospitals struggle to remain independent i n a market economy. However, any agency that wishes to plan the r e l a t i o n -ship of hospitals to other health care and other community requirements must be able to implement i t s strategies. The U.S. Public Health Service recognizes the need for planning due to cost escalations and population changes, but maintains that hospitals should remain independent (U.S.P.H.S., 1961). This independence i s c i t e d by May (1976) as one reason f o r the disappointing performance of America's layers of planning l e g i s l a t i o n . Because most American ho s p i t a l users s t i l l pay f o r services d i r e c t l y to the hospitals or through t h i r d party insurers, the State has been i n a weak position i n proposing central control since i t has not been d i r e c t l y involved i n the transaction between the patient and the h o s p i t a l . Recent U.S. government p a r t i c i p a t i o n i n Medicare and Medicaid, however, has created a f i n a n c i a l lever that may be used to a t t a i n planning goals. In Canada, the health-care system i s d i f f e r e n t from that i n the U.S.A., i n that the federal and p r o v i n c i a l governments finance both hospital care and the major portion of hospital construction, thus acting as t h i r d party agencies on behalf of the consumer. This c e n t r a l i z a t i o n of funding has created a legitimate base for central planning, but i t has also created a problem i n matching the demand and supply of ho s p i t a l services. The consumer demands health care as a r i g h t , but i s not required to regulate his demands since the consumer-provider market system has beenreplaced by "insurance". The State reacts to these demands by regulating the supply of hos p i t a l services according to i t s f i s c a l resources. To complete the c i r c l e , the consumer usually r e s i s t s the tax increases that the State requires to meet the consumer's increasing demands. Thus, t h i s c e n t r a l i z a t i o n of funding has removed the consumer from the connection between service and i t s cost. The problems created by unregulated demands are discussed l a t e r i n t h i s study. In spite of these problems, the State attempts to obtain a balance i n the hospital system by a l t e r i n g the supply of h o s p i t a l services to meet the demand expressed by consumers. Since there i s a lead-time of several years between the i n i t i a t i o n and the completion of h o s p i t a l f a c i l i t i e s , current plans must be based on estimates of future demand i f a balance i s ever to be reached between supply and demand. This thesis studies the process of estimating, or forecasting, the future demand for h o s p i t a l f a c i l i t i e s and i t refines one established fore-casting technique to provide f o r rapid analysis of po l i c y alternatives through use of a forecasting program on a computer. F i n a l l y , the study examines the s e n s i t i v i t y of the technique to changes i n the value of input variables. I t must be c l e a r l y stated at the onset that systems-analysis techniques such as forecasting cannot, and should not, be expected to replace goal setting and decision making; rather, they provide information to a i d the policy makers. To be e f f e c t i v e , these techniques must not only be t h e o r e t i c a l l y sound, but must also successfully analyse r e a l problems. (Bailey, 1975). 5. CHAPTER I I PROBLEMS OF FORECASTING ACUTE-CARE-HOSPITAL BED REQUIREMENTS Hospital planning i s ultimately subjective. I f we t r y to persuade ourselves that i t i s objective, we are deceiving ourselves. (Hudenburg, 1967) Canadian governments have removed most of the health care industry from the market economy. This was not done as a contentious move to co n t r o l , but as an innocuous move to "insure" individuals against the high costs of necessary health services. Government now "reimburses" health care suppliers by acting as the agent of the consumer. Rapidly r i s i n g c a p i t a l and operating costs i n hospitals have forced goverments to determine whether the care consumed i s reasonable. The State i s expected to provide health care services quickly i n response to consumer demands and also to manage the taxpayers' funds prudently. These two tasks often c o n f l i c t ! The State must ra t i o n i t s l i m i t e d resources to society's o v e r a l l demands and thus must compare the perceived health-care needs of the consumer with the demands expressed by other sectors of society. In r e l a t i o n to hospital services, the question the State must ask i s , what IS the type and quantity of acute-hospital care that society should have? A spontaneous response might be "provide what the community needs". This i s an i d e a l i z e d approach but one that i s d i f f i c u l t to implement. G r i f f i t h (1972) defines need as a "concept of health service required by a population to maintain i t at a preconceived l e v e l of health". This value-laden concept i s a l l but impossible to measure. Unless detailed and expensive surveys of the health status of the population are conducted, the true need for h o s p i t a l services cannot be known. The popular substitute f o r need i s demand; "the sum of e x p l i c i t requests f o r a given medical care service either by the patient...or the doctor " ( G r i f f i t h , 1972). Newhouse (1971) suggests abandoning the ine f f e c t i v e concept of "need" and using instead a prediction of future demand f o r services and provision of the necessary corresponding resources. The disadvantage of using t h i s substitute i s that such factors as economic status, s o c i a l pressures, and a v a i l a b i l i t y of resources d i s t o r t true need into demand for services. The advantage of t h i s substitute i s that demand i s expressed i n a c t i v i t y that can be e a s i l y measured. By accepting demand as a substitute f o r need, a judgement i s made that measurability i s more important to planning than i s pertinence. Demand i s expressed i n the u t i l i z a t i o n of acute-care f a c i l i t i e s ; p a r t i c u l a r l y by admissions to hospitals and the number of days that h o s p i t a l beds are occupied. When u t i l i z a t i o n i s expressed as a r a t i o of hospital bed days used (or patient days) per 1000 persons, i t i s l a b e l l e d "THE INCIDENCE RATE OF HOSPITALIZATION" ( G r i f f i t h , 1972). Defi n i t i o n s of such terms used i n t h i s study are contained i n the Glossary. This r a t e , when calculated from current data, i s used as an indicator of the current acute-care demand of a population. When projected to a future point i n time, the rate i s used to estimate future demand f o r h o s p i t a l beds. The supply of acute-care-hospital beds has a strong influence on the u t i l i z a t i o n of those f a c i l i t i e s by the community. The concept that supply creates, within some l i m i t s , i t s own demand (Abel-Smith, 1962) has focused attention on the number of acute-care-hospital beds as a key to attaining more "reasonable" demands on the public treasury. The study by Roemer and Shain (1959) supports the argument that empty h o s p i t a l beds are 7. soon f i l l e d and thus that the supply of beds i s d i r e c t l y l i n k e d to costs. This argument states that as beds are added i n response to demand, they are soon occupied and t h i s u t i l i z a t i o n i s then used as a base f o r requesting more beds i n the future. The s p i r a l must, i n p r a c t i c e , end a t a f i n i t e bed-count. This s t a b i l i z e d bed-count may not r e f l e c t the true requirements f o r acute-care f a c i l i t i e s as consumers may be inappropriately placed. These people may s h i f t to less costly alternatives, when provided, and leave the acute hospitals with i n e f f i c i e n t occupancy l e v e l s . Ensminger (1975) claims that t h i s i s the current s i t u a t i o n i n the United States with higher-than-necessary costs f o r h o s p i t a l care due to the over-building of f a c i l i t i e s . Quality of care may suffer i n t h i s s i t u a t i o n as independent hospitals and t h e i r physicians compete f o r patients and also drain s t a f f and resources from public hospitals. The next major conceptual hurdle i n the planning process i s the projection or forecast of hospital u t i l i z a t i o n . The sophisticated s t a t i s t i c a l tools usually used to produce t h i s forecast do not create quantitative fore-casts without the input of q u a l i t a t i v e judgements. Martin (1975) corr e c t l y comments, "...no matter how complex the mathematics of the p a r t i c u l a r technique appear, every forecasting technique i s a mix of two basic elements, projection of past trends and educated guesses." The d i s t i n c t i o n between these two elements implies serious p o l i c y implications. For example, i f current u t i l i z a t i o n i s applied to a future time, or i f past trends are extrapolated into the future, the i m p l i c i t assumption i s that no change from the status quo i s anticipated. Since h o s p i t a l care i s dynamic, t h i s i s a dubious assumption. The second element, the educated guess, i s interpreted here to mean either the i d e n t i f i c a t i o n and examination of factors that may a l t e r current demand or the establishment of normative 8. demand le v e l s . The f i r s t element, the examination and projection of past trends, i s deterministic; the second, the educated guess, i s dynamic and implies conscious po l i c y formation. Assuming that educated guessing i s necessary, how does one establish normative u t i l i z a t i o n rates; how much hospital care i s enough? Hoge (1958) notes that normative u t i l i z a t i o n rates have been estab-l i s h e d , but that they have been made equal to e x i s t i n g h o s p i t a l u t i l i z a t i o n . This acceptance of the status quo as a norm may be a mistake since there may be unexpressed demand due to a shortage of h o s p i t a l f a c i l i t i e s or over-u t i l i z a t i o n of hospital f a c i l i t i e s due to a high physician-per-population r a t i o . For example, i f a population unit has i n s u f f i c i e n t h o s p i t a l services to meet i t s legitmate demands, u t i l i z a t i o n rates expressing the f u l l use of these f a c i l i t i e s w i l l only indicate what hospital use has occurred, not what use would have occurred i f more f a c i l i t i e s had been available. The formalizing of the current u t i l i z a t i o n rate as a norm for future planning would perpetuate the inadequacy of the present s i t u a t i o n . A l t e r n a t i v e l y , the current h o s p i t a l u t i l i z a t i o n rate may r e f l e c t an o v e r - u t i l i z a t i o n of f a c i l i t i e s . For example, i f a population unit has more physicians than are required to meet i t s legitimate medical demands, hospitals may be inappropriately over-used rather than physicians being appropriately under-used. Again, establishment of t h i s i n f l a t e d h o s p i t a l incidence rate as a norm w i l l not a l t e r the future s i t u a t i o n as an improvement on the present. I t i s c l e a r l y d i f f i c u l t to judge the appropriateness of current h o s p i t a l u t i l i z a t i o n rates. Actual h o s p i t a l occupancy rates and patient waiting l i s t s can a s s i s t i n t h i s review, but they can be influenced by such qua l i t a t i v e factors as the l o c a l patterns of medical practice and the e f f i c i e n c y of the hospitals' management. 9. The appropriateness of l o c a l hospital u t i l i z a t i o n rates may be assessed by comparing l o c a l rates with the u t i l i z a t i o n experience of other countries and d i f f e r e n t health-care-delivery systems, but t h i s may y i e l d inconclusive r e s u l t s as the following example shows. Anderson (1972) reported that the 1968 average INCIDENCE RATE OF HOSPITALIZATION f o r the free-enterprise U.S.A. was 1154/1000 while those of S o c i a l i s t Sweden and England were 1569/1000 and 1132/1000 respectively. No cl e a r pattern emerges from these few samples. S i m i l a r l y , l o c a l INCIDENCE RATES may be compared within a regional area i n an attempt to set norms f o r future planning. Table One shows the age-specific adult INCIDENCE RATES f o r d i s t r i c t s within Greater Vancouver f o r the years 1971 and 1975. TABLE I ANNUAL INCIDENCE RATE OF HOSPITALIZATION PER 1000 PERSONS AGE GROUP 1 5 - 6 9 D i s t r i c t s 1971 1975 Surrey 1292 1141 Delta 881 828 Richmond 907 867 Vancouver 1374 1352 New Westminster 1208 1275 Burnaby 976 941 Coquitlam 891 912 North Vancouver 1247 1035 West Vancouver 1023 941 TOTAL POPULATION 1202 1136 Two of the areas with low u t i l i z a t i o n , Delta and Coquitlam, do not have l o c a l community hospitals. However, other indicators would need to be studied to deternrine whether these two areas were low because of i n s u f f i c i e n t supply of hospital beds or whether the other areas were high because of an oversupply of beds. Such an analysis 10. might lead to reasonable norms for demand. Although the establishment of norms i s d i f f i c u l t , forecasting demand cannot be a useful technique i n the cost-reducing planning process unless e x i s t i n g patterns of u t i l i z a t i o n are changed. Paul Ellwood i n a summary to a work by Melum (1975) states that sophis-t i c a t e d formulas, giving the appearance of pre c i s i o n , act as math-ematical "security blankest" and that health care costs w i l l not be contained unless "courageous c r i t e r i a " are used i n the forecasting of future demands. In other words, Elwood believes that the present u t i l i z a t i o n of hos p i t a l f a c i l i t i e s i s not i d e a l and that future u t i l i z a t i o n should be forced downward by r e s t r i c t i n g the supply of acute care f a c i l i t i e s . This statement implies that, i n general, acute-care-hospital f a c i l i t i e s are inappropriately used and that lower-cost alternatives should be made available to meet the consumer's perceived needs for hospital care. As stated e a r l i e r , the two elements of a forecasting technique are, f i r s t l y , projections of past trends and,secondly, educated guesses. Too often, a simple extrapolation of a past trend i s used to a r r i v e at a forecast without addressing the problems involved i n making educated guesses about value-laden issues. An extrapolation forecast makes these guesses, or p o l i c y decisions by default; i t assumes a continuation of the status quo.. These two elements must be combined and the i m p l i c i t p o l i c y decisions must be stated c l e a r l y i f the r e s u l t i n g forecast i s to be e f f e c t i v e . This chapter has outlined the following basic conceptual problems involved i n planning acute-care-hospital requirements: the concept of need vs. demand, the State as a t h i r d party i n the con-11. sumer-provider r e l a t i o n s h i p , the appropriateness of current h o s p i t a l u t i l i z a t i o n , and, the projection of trends. Since i t i s u n l i k e l y that these problems w i l l be resolved, the following comment by S i r George Godber (Tottie, 1967) may be i r o n i c a l l y appropriate: "Although the number of beds i s a poor measure of hospital need, i t does give a general guide and i t i s the only unit i n common use." 12. CHAPTER I I I THE DEVELOPMENT OF TECHNIQUES FOR FORECASTING THE DEMAND FOR ACUTE-CARE-HOSPITAL BEDS " r^termining bed need, at best, i s an educated guess; but, i n a l l p r o b a b i l i t y , i s better than an uneducated one." (Hudenburg, 1967) Current techniques used to forecast the future demand f o r acute-care-hospital beds have resulted from past i n q u i r i e s i nto the status of hospital bed supply. I t i s relevant to t h i s thesis to trace t h i s development by looking at selected developments which can put the current state-of-the-art into perspective. One of the e a r l i e s t formal recognitions of the need to plan the development of hospitals was made by the New York Academy of Medicine i n 1920 (U.S.P.H.S., 1958). This study used a U.S. Public Health Service estimate that two per cent of the population would be i l l at any point i n time. Thus, by surveying 180 general hospitals i n New York C i t y , i t was determined that there were 5 beds per 1,000 people, or one bed for every fourth i l l person. The Academy f e l t that t h i s was s u f f i c i e n t . This uncomplicated approach has the basic elements of a forecast, namely, a quantitative measure of current demands and a prediction of future demand. S p e c i f i c a l l y , the measure of current demand was f i v e beds f o r every 1,000 persons and the prediction of future demand was t h e i r decision that t h i s usage was acceptable and the assumption that t h i s bed per population r a t i o should be applied to future populations to determine future h o s p i t a l bed requirements. The economic depression of the 19 30's l i m i t e d the growth of 13. hospitals, although the U.S. government began a grant-in-aid program i n 1933 to use hospitals as public works projects (Hodge, 1958). The manpower and material shortages experienced during World War I I aggravated t h i s already slow growth i n the h o s p i t a l bed supply. During t h i s war, many countries recognized that changes i n the post-war h o s p i t a l sector would be necessary. B r i t a i n planned to reorganize i t s entire health services while Canada and the U.S. planned incentives for the construction of new hospital f a c i l i t i e s . The Commission on Hospital Care examined the status of h o s p i t a l f a c i l i t i e s i n the United States i n the early 1940s (Commission on Hospital Care, 1947). A f t e r exploring the d i f f i c u l t i e s of determining need, which are outlined i n Chapter I I , the Commission used the death rate of the population as an indicator of the prevalence of sickness i n the population. They also determined that, on the average, 250 patient-days of care are provided by hospitals f o r every death occurring i n hospitals ( t o t a l patient-days/deaths i n h o s p i t a l s ) ; t h i s i s equivalent to approximately 0.7 hospital beds f o r each death occur-r i n g i n one year (250 days/365 days) at 100% occupancy. Since the gross death rate of the population was known, 10.1%/year., as w e l l as the proportion of t o t a l deaths that occur i n h o s p i t a l s , 50%, i t was possible to forecast the future hospital requirements as described i n Table I I . 14. TABLE I I FORECASTING TECHNIQUE USED BY THE COMMISSION ON HOSPITAL CARE U.S.A. Forecast Annual Deaths i n Hospitals per 1000 Persons Example: 5.05/1000 - yr. Forecast Annual Deaths per 1000 Persons 10.1/1000 - yr. Forecast Proportion of Total Deaths Occurring i n Hospitals 0.5 Forecast Annual Hospital-Bed Require-ment at 100% Occupancy Per 1000 Persons Example: 3.54/1000 - yr. Forecast Annual X Deaths i n Hospitals per 1000 Persons 5.05/1000 - yr. X 0.7 Beds per Hospital Death 0.7 Forecast Annual Hospital-Bed-Requirement at Desired Occupancy Percentage Example: 4.71/1000 - yr. Forecast Annual Requirement at 100% Occupancy 3.54/1000 yr. Desired Occupancy Percentage 75^ 15. This c a l c u l a t i o n used a 1944 U.S. death rate and a projected 1946 proportion of deaths i n hospitals to forecast a 1946 require-ment of approximately f i v e h ospital beds per 1000 persons. The Commission forecast the requirement for maternity beds separately, i n p a r t i c u l a r the forecast number of these beds were d i r e c t l y r e lated to the number of b i r t h s occurring i n hospitals. The p r a c t i c a l operation size of hospitals within the estab-l i s h e d geographic areas was determined from the average d a i l y requirement for beds, the AVERAGE DAILY CENSUS. Because hospitals with a low average d a i l y census were unable to maintain a high occupancy, the planned occupancy rates for the hospitals varied with the expected average d a i l y census. These refinements enabled the study to vary the supply of hospital beds to s u i t l o c a l conditions, providing a better approach than e a r l i e r f i x e d r a t i o s per population u n i t . This work of the Commission on Hospital Care i n the United States resulted i n the Hospital Survey and Construction Act (Hill-Burton) of 1946 (Somers, 1969). This Act was designed to provide federal funds f o r l o c a l h o s p i t a l construction on a cost-sharing basis, provided that each state conducted a survey of current assets and projected demands. The specified forecasting formula applied the current incidence rate f o r an area to an estimate of the future population. This projected annual demand i n h o s p i t a l patient-days was converted to h o s p i t a l bed-equivalents and adjusted by the desired occupancy of the hospitals to y i e l d the projected demand f o r hospital beds. These steps are summarized i n Table I I I . 16. TABLE I I I FORECASTING TECHNIQUE USED BY THE HOSPITAL SURVEY AND CONSTRUCTION ACT U.S.A. 1. Forecast Annual Demand for Hospita l i z a t i o n (Patient-Days/yr.) Current Incidence Rate X of Hospitalization (Patient-Days/yr.) Forecast Population (Population i n 1000's) 2. Forecast Average Daily Census Forecast Total Annual Demand For Hospitalization 365 (Patient-Days/yr) (Patient-Days/yr.) (days/yr.) 3. Forecast Hospital Bed Need Beds/day Forecast Average Daily Census (Patient-Days/day) (or Beds/Day) Desired Occupancy +10 Percentage ( % ) (Beds) 17. I n i t i a l l y , the Occupancy Percentage was set at 80% (or 0.8) with the additional 10 beds as an adjustment for small hospitals that are unable to maintain t h i s desired occupancy. Note here that, f o r simplic-i t y , the method of varying the desired Occupancy Percentage i n r e l a t i o n to the expected Average Daily Census of each h o s p i t a l used by the Commission on hospital care, was not incorporated into the H i l l - B u r t o n formula. Subsequently, i n 1972, the occupancy rate was raised to 85% and i n 1973, the addition of 10 beds was deleted from the formula. This Act required the establishment of state planning agencies as a condition for federal p a r t i c i p a t i o n i n h o s p i t a l construction programs and i t provided the agencies with a uniform planning method. In recent years, however, the planning method has been c r i t i c i z e d ( H i l l , 1971) because i t assumes that current usage as expressed as the Incidence Rate i s legitimate and then applies that Incidence Rate to future population estimates. I f the current Incidence Rate i s inappropriate f o r whatever reason, the discrepancy can be compounded i n the future, as was explained i n Chapter I I . However, despite i t s t h e o r e t i c a l def i c i e n c i e s , the Act did stimulate hospital construction i n a period of generally agreed shortage. Canada, l i k e the United States, experienced a post-World War I I shortage of h o s p i t a l f a c i l i t i e s . The Canadian government implemented a National Health Program i n 1948 to provide federal funds on a cost-shared basis to provinces for acute-care-hospital construction. Like the H i l l - B u r t o n program, federal grants were conditional on p r o v i n c i a l surveys of health services. The hospital-insurance program of the Province of B r i t i s h Columbia, therefore, required a comprehensive analysis of h o s p i t a l needs and such a study was commissioned (Hamilton, 1949). The h o s p i t a l 18. plan subsequently recommended was based on forecasts of "need" using the bed/death and bed/birth methods of the Commission on Hospital Care discussed e a r l i e r . The plan specified h o s p i t a l regions created from census t r a c t d i v i s i o n s with a three-tiered structure of community c l i n i c s , community hospitals and regional hospitals. Some of these regional hospitals were teaching centres. Some 15% of demand at the community c l i n i c and h o s p i t a l l e v e l was to be referred to regional hospitals and a further 5% to the teaching hospitals. The Plan's forecast f o r 1971 was a bed/1000 population r a t i o of 7.09. Compared with recent standard of 4.25* t h i s i s an incredibly high r a t i o , which may indicate the p e r i l s of forecasting f o r a 20 year period! Further work was done i n B r i t i s h Columbia i n the early 1950s to determine the number of acute-care-hospital beds needed for the Lower Fraser Valley Hospital Region. The work was done by the former B.C. Department of Health and Welfare (Grigg and Whelen, 1954), based on 1952 data from the newly formed B.C. Hospital Insurance Service. Past trends i n h o s p i t a l i z a t i o n , projected population growth, transpor-t a t i o n f a c i l i t i e s and inter-regional relationships were examined to forecast the change i n the t o t a l number of patient-days over a time period. The reason f o r the use of t o t a l patient-days as a base f o r the forecast rather than the more usual rate of patient-days per 1,000 population i s curious, and not explained. This work, however, did contribute a new feature to the growing l i s t of sophisticated forecasting techniques. S p e c i f i c a l l y , since accurate information on * 1977 B.C. Hospital Programs Prov i n c i a l Average-Care-Hospital Bed per 1000 Target Ratio. 19. hospital usage was available from the new universal hospital-insurance program, the source and d i s t r i b u t i o n of patients was known and could, therefore, be used i n forecasting the future demand at Lower Fraser Valley hospitals. In the mid 1950s, the Swedish hospital system was reorganized to overcome the l i m i t a t i o n s experienced by the 25 independent county councils responsible f o r hospital care due to t h e i r o v e r a l l population bases. Af t e r transportation and geographic studies were conducted, the country was divided into several s e l f - s u f f i c i e n t h o s p i t a l regions, each serving approximately one m i l l i o n persons. Each region has a regional h o s p i t a l o f f e r i n g specialized services as w e l l as county and community hospitals i n a three-tiered system. In determining the organization of f a c i l i t i e s , the optimal size of departments f o r needed services was considered along with the usual demographic character-i s t i c s of the population. Using f i f t e e n years of experience, standard sized units were determined f o r medical s p e c i a l i t i e s with bed-to-population r a t i o s . Tottie and Janzon (1967) report that the bed-to-population r a t i o s were used as a guide i n the forecasting of demand but that s o c i a l factors such as housing and family care of the aged as w e l l as geographic factors were important considerations i n the al l o c a t i o n of future f a c i l i t i e s . This extensive national plan was mainly based on subjective judgements of l o c a l conditions but i t d i d add to the planning a r t the techniques of developing and using r a t i o s of specialty-beds-to-population and, a f t e r the t o t a l number of specialty beds had been determined, establishing r a t i o n a l l y sized groups of specialty beds. In Great B r i t a i n , following World War I I , the creation of the National Health Service reorganized the delivery of medical and 20. h o s p i t a l care. However, no e x p l i c i t forecast was made of the future demand f o r h o s p i t a l f a c i l i t i e s . By 1962, national standards were set f o r the demand expected i n 1975, (National Health Service, 1966). A 3.3/1,000 hospital-bed-to-population r a t i o was set f o r acute care and a 0.58/1,000 r a t i o was set f o r maternity. The combined 3.9 bed to population r a t i o appears as a target to be met rather than as an estimate of consumer demand because the 1966 statement on the b u i l d -ing program emphasizes that acute care i s not the whole picture and that alternatives such as home care and day care can be improved. , This use of targets i s an important change from the usual technique of extrapolating from past trends to forecast the demand for h o s p i t a l services at a future point i n time. Despite the d i f f i c u l t i e s inherent with the setting of normative h o s p i t a l i z a t i o n rates, noted i n Chapter I I , the National Health Service established a public-policy objective to change the system of hospital care and set ho s p i t a l building targets a f t e r comparing estimates of future need with the policy objectives. In the early 1960s, the Canadian government commissioned a broad study on the state of the nation's health services (Royal Commission on Health Services, 1964). Part of i t s mandate was to report on the future need for health services. Although the Com-mission c a r e f u l l y stated that i t could not "predict" the future demand f o r beds, i t did extrapolate the 1958-61 h o s p i t a l i z a t i o n experience to estimate that the 1971 demand would be 1,995 patient days per 1,000 population f o r acute hospital care. The Commission exarnined occupancy rates and a r b i t r a r i l y increased the average rate from 80.0% to 81.6% when expressing the demand forecast i n terms of hosp i t a l beds. The Report of the Commission states that 21. the forecast was only intended to indicate a "general order of magnitude of the need for physical f a c i l i t i e s . " Because of i t s generality, the forecast could only be used to show what might happen i f past trends were to continue. In f a c t , the Greater Vancouver Regional Hospital D i s t r i c t ' s incidence rate of h o s p i t a l i z a t i o n i n 1971 was 1,380 patient-days/1000 persons-year, 31% below the Royal Commission's estimate of 1995/1000 for the 1971 national average. The trend i n that era of increasing usage of acute-care hospitals did not i n fact continue. By the early 1960s, the United States had evaluated the perfor-mance of the Hil l - B u r t o n l e g i s l a t i o n of 1946 and found i t less s a t i s -factory than expected. Thus May (1967) states that while the l e g i s l a t i o n did expand the stock of hospital f a c i l i t i e s , unfortunately the forecast-ing formula tended to entrench l o c a l patterns. Further, the area-wide planning agencies created under Hill-Burton did not have authority over a l l hospitals which made coordination of development d i f f i c u l t . Funding for planning agencies was improved by federal l e g i s -l a t i o n i n 1961. To provide guidance to these agencies, the U.S. Public Health Service and the American Hospital Association published a planning manual i n the same year. This publication i s comprehen-sive i n i t s review of factors influencing planning decisions, but continues to apply current incidence rates to future populations i n order to estimate future demands, thus deserving the basic c r i t i c i s m of the 1946 Hill-Burton method already noted. The manual does introduce one normative variable, however, because i t suggests that "desirable" medical-surgical occupancy rates should be between 85-90%. In summary of the period from the early 1900s to the 1960s, 22. the techniques f o r forecasting the future demand f o r acute care hospital beds have evolved from simple s p e c i f i c a t i o n of h o s p i t a l beds per population r a t i o s to those of complex use rates, population forecasts, and occupancy equations. The next chapter completes the review by examining current forecasting methods. 23. CHAPTER IV CURRENT FORECASTING METHODS Current methods used to forecast the future demand f o r acute-care-hospital beds have evolved from e f f o r t s such as those described i n the previous chapter. These techniques are now usually used to j u s t i f y expansion of services to meet the "needs" of growing pop-ulations and to contain the "unnecessary" growth of expensive acute hos p i t a l care - depending on the user's frame of reference. Some techniques are more complicated than others, but they a l l can be broken down into some set of the stages l i s t e d i n Table IV. Many refinements can be made to these basic relationships to focus on s p e c i f i c diseases, populations, and age groups. However, no matter how sophisticated the technique may be, fundamental d i f -f i c u l t i e s remain with the use of incidence rates, population fore-casts and occupancy percentages. Before the forecast process can begin, there must be agreement on the d e f i n i t i o n of the population groups whose demands f o r h o s p i t a l care are to be forecast. For convenience, these groups are usually organized communities with p o l i t i c a l boundaries. Hospital service areas must also be known i f reasonable forecasts of demand are to be made f o r i n d i v i d u a l hospitals. Since the geographic boundaries of these two area types do not usually coincide, adjustments must be made i n the forecast to r e f l e c t the flow of patients among the areas. These adjustments are indicated by the reference to RELEVANCE INDICES i n Equation 3, and are described l a t e r i n t h i s chapter. The follow-ing examples describe the creation of population groups. 24. TABLE IV EQUATIONS OF THE STANDARD FORECASTING METHOD 1. FORECAST INCIDENCE RATE OF HOSPITALIZATION Patient-Days/10 0 0-yr. FORECAST HOSPITAL ADMISSIONS RATE FORECAST x AVERAGE LENGTH OF STAY PER ADMISSION Admissions/1000/yr. Days per Admission 2 . FORECAST GROSS TOTAL DEMAND FOR HOSPITALIZATION Patient-Days/yr. FORECAST FORECAST INCIDENCE RATE x POPULATION OF HOSPITALIZATION Patient-Days /1000-yr. Population i n 1000's. FORECAST NET TOTAL DEMAND FOR HOSPITALIZATION Patient-Days/yr. FORECAST RELEVANCE INFLOW GROSS TOTAL x INDICES + DEMAND Patient-Days Proportions Patient-/yr. days/yr. FORECAST AVERAGE DAILY CENSUS Patient-Days/day (beds) FORECAST NET TOTAL DEMAND Patient-Days/yr. * 365 Days/yr. FORECAST HOSPITAL BED REQUIREMENTS beds FORECAST AVERAGE DAILY CENSUS beds DESIRED OCCUPANCY PERCENTAGE 25. The province of Ontario uses a planning guide that 80% of a population group's need f o r hospital care should be met by l o c a l hos-p i t a l s , a further 10% by d i s t r i c t hospitals, and the remaining 10% by regional or teaching hospitals (Task Force on the Cost of Health Services 1970). These service areas must be defined before t h i s hierachy of care l e v e l s can be established. For example, the province of Alberta used 1971 h o s p i t a l insurance data on patient-flow patterns to define the boundaries of acute-care-hospital regions (Paine and Wilson, 1974). The flow part ems were then incorporated into fore-casts of bed demand f o r each of the population groups organized as hospital regions. In B r i t i s h Columbia, regional hospital d i s t r i c t s were arranged to coincide with the p o l i t i c a l regional d i s t r i c t s i n order to f a c i l i t a t e f i n a n c i a l cost sharing. Unfortunately, these h o s p i t a l regions were established f o r adininistrative convenience and do not necessarily r e f l e c t the pattern of patient flow from community to regional hospitals as do the h o s p i t a l regions of Alberta. The data on patient flow pat-terns i n B.C. are a v a i l a b l e , however, and were used by Anderson (1974) to estimate the requirements f o r a proposed centre to serve the r e f e r r a l needs i n obstetrics and paediatrics for the whole province. This analysis developed a working d e f i n i t i o n of t e r t i a r y care which was used to forecast the future inflow to the proposed centre. Unfortun-ate l y , the techniques he established have not been used to analyse broader inter-regional patient flow problems. Once the population groups have been defined by methods such as those j u s t described, the forecasting process outlined i n Table IV can be applied. The f i r s t Equation i n the standard forecasting method develops 26. a measure of ho s p i t a l use by a s p e c i f i c population by multiplying a forecast of the HOSPITAL ADMISSIONS RATE by a forecast of the AVERAGE LENGTH OF STAY. This count of "patient-days" i s usually expressed i n terms of units of one thousand persons and time units of one year to form a use rate defined as the INCIDENCE RATE OF HOSPITALIZATION. The forecast of t h i s Incidence Rate at a future point i n time i s a fundamental step and can be done i n two ways. The conventional method i s to extrapolate the current rate a f t e r examining past trends and then to make adjustments f o r expected future developments i n health care. A more refined, but no less subjective method i s to f i r s t fore-cast the Hospital Admissions Rate f o r the population and then multiply t h i s rate by the forecast Average Length of Stay per admission to y i e l d an Incidence Rate expressed as patient-days per thousand of population. In e i t h e r method, the essential question asked i s " W i l l past trends continue, and i f not, by how much should they be altered?" Here, a multitude of influencing factors can be considered, such as; the supply of health care personnel, the supply of h o s p i t a l f a c i l i t i e s , advances i n medical technology, and patterns of organization and t r e a t -ment. Nevertheless, i n the end, a subjective judgement must be made as to what numerical value i s to be given to the Incidence Rate. I f the softness of t h i s estimate i s recognized i n interpreting the r e s u l t s , then the f i n a l forecast can remain a useful planning t o o l . In many cases, however, once the quantification of subjective judgement i s made, the chosen numerical value i s used to produce r e s u l t s that suffer from spurious accuracy. A reasonable way to a l e r t the user to t h i s uncertainty i s to specify a range involving both a minimum and a max-imum rate, as i s done by the state planning agencies of New York and 27. I l l i n o i s (Melum, 1975). Although the range i s s t i l l based on subjective judgement, any u n j u s t i f i e d implication of precision i s removed. The second Equation i n the standard forecast method i s the application of the FORECAST INCIDENCE RATE OF HOSPITALIZATION to a forecast of the FUTURE POPULATION to produce GROSS TOTAL DEMAND FOR HOSPITALIZATION. The subject of population forecasting i s complex and w i l l not be discussed i n t h i s examination beyond the comment that i t can suffer from the same problem of spurious accuracy. The steady pattern of population growth i n the years following World War I I i s no longer a r e l i a b l e trend because b i r t h rates, immigration and migration patterns, and economic conditions are a l l i n a state of fl u x . To r e f l e c t t h i s uncertainty, ranges should be again used. For example, a study of the hos p i t a l bed needs of Scarborough, Ontario, used three estimates of the future population (most l i k e l y , next most l i k e l y , and least most l i k e l y ) as a base of alternate forecasts (Thompson, 1971). In t h i s way, the forecast can be appropriately used to r e f l e c t d i f f e r e n t possible outcomes rather than stati n g a single figure and masking the inherent uncertainty i n the components. Taking t h i s approach one step further, p r o b a b i l i t i e s could be assigned to each alternate forecast, which would give the poli c y maker an indic a t i o n of the degree of r i s k that the chosen forecast w i l l not be accurate. The t h i r d Equation of the 'standard forecasting method converts the forecast GROSS TOTAL DEMAND of the subject population group to a forecast of the NET TOTAL DEMAND through the use of RELEVANCE INDICES that d i s t r i b u t e the Gross Total Demands of in d i v i d u a l sub-regional d i s t r i c t s to other d i s t r i c t s . This r e a l l o c a t i o n accounts f o r the flow of patients from t h e i r d i s t r i c t of residence to the d i s t r i c t where 28. t h e i r h o s p i t a l treatment i s provided. Since the geographic boundaries of the specified sub-regional d i s t r i c t s do not usually coincide with the service areas of the individual hospitals, t h i s flow of patients across d i s t r i c t boundaries may s i g n i f i c a n t l y a f f e c t the Net Total Demand of in d i v i d u a l d i s t r i c t s . For example, Table V shows a hypothetical Region with three d i s t r i c t s ; D i s t r i c t A, D i s t r i c t B, and D i s t r i c t C. Each d i s t r i c t has forecast a GROSS TOTAL DEMAND f o r hospital services and a flow of patient demand, expressed i n patient-days, to each other d i s t r i c t , and to d i s t r i c t s outside the Region, l a b e l l e d OUTFLOW. The proportions that d i s t r i b u t e each d i s t r i c t ' s forecast Gross Total Demand have been named RELEVANCE INDICES (Johnstone, 1971). INFLOW patient-days from outside the Region are then added to the d i s t r i c t s ' demand t o t a l s to form the NET TOTAL DEMAND forecasts. Table 5 shows that, although D i s t r i c t A has a forecast GROSS TOTAL DEMAND of 20,000 patient-days of h o s p i t a l care, the D i s t r i c t ' s hospitals are forecast to receive only 13,500 patient-days, the net res u l t of the transfers i n and out. On the other hand, D i s t r i c t B's hospitals are forecast to receive 115,000 patient-days although that D i s t r i c t ' s Gross Total Demand i s only 100,000 patient-days. This flow of patient demand r e f l e c t s such factors as the personal preference of the patient, geography, and the a v a i l a b i l i t y of services. Relevance Indices can d i s t r i b u t e a d i s t r i c t ' s forecast Gross Total Demand either among other d i s t r i c t s i n a region, or among i n d i v -i d u a l hospitals i n a region. For convenience, the example i n Table V has grouped the hospitals within the boundaries of a d i s t r i c t i n to one unit. This grouping permits the use of a single RELEVANCE INDEX to transfer patient-days from one d i s t r i c t to a l l the hospitals within 29. another d i s t r i c t . However, since the objective of forecasting the demand fo r hospital f a c i l i t i e s i s to determine the required future s i z e of indivi d u a l h o s p i t a l s , the forecast NET TOTAL DEMAND of a d i s t r i c t must be allocated among the hospitals within that d i s t r i c t at t h i s point i n the forecast, or a f t e r either of the next two equations. The i n d i v i d u a l Relevance Indices must be forecast to define a patient flow pattern at a future point i n time. Although the current flow pattern can be applied to a forecast of Gross Total Demand, the " w i l l present trends continue?" question must be answered. The fourth Equation reduces the forecast annual NET TOTAL DEMAND to a dai l y volume. Because the smallest unit of h o s p i t a l care i s assumed to be one bed used by one person for one day, the forecast average dai l y volume i n patient days i s also the forecast AVERAGE DAILY CENSUS of the hospital(s) located i n the forecast area. The f i f t h Equation compensates for the fact that there w i l l be fluctuations i n the d a i l y hospital census due to the stochastic nature of demands f o r patient admissions to hospitals. While many ho s p i t a l procedures can be scheduled, maternity cases, accident cases, and urgent i l l n e s s e s occur randomly and cause fluctuations i n the d a i l y census. Most planning studies have examined hospital records and state that e f f i c i e n t l y managed hospitals operate i n the range of 75-90% average occupancy with the balance to 100% held as a reserve f o r peak demand occasions. Since t h i s adjustment appears to accommodate the f l u c -tuations, the standard forecasting method selects a DESIRED OCCUPANCY PERCENTAGE to convert AVERAGE DAILY CENSUS into a higher number of acute-care-hospital-beds that w i l l e f f e c t i v e l y s a t i s f y the demands on nearly a l l occasions. The compensation for demand f l u c t u a t i o n i s a s t a t i s t i c a l problem that does not have a universally recognized 30. TABLE V EXAMPLE OF RELEVANCE INDICES APPLIED TO A HYPOTHETICAL REGION DISTRICT A DISTRICT B DISTRICT C FORECAST GROSS TOTAL DEMAND (Patient-D a y s ) ^ 20,000 100,000 50,000 RELEVANCE INDICES To A: To B: To C: OUTFLOW TOTAL 0.40 0.40 0.15 0.05 1.00 0.00 0.90 0.09 0.01 1.00 0.08 0.30 0.60 0.02 1.00 TRANSFER: (PATIENT-DAYS) From A: From B: From C: INFLOW: 8,000 0 5,000 500 8,000 90,000 15,000 2,000 3,000 9,000 30,000 1,000 FORECAST NET TOTAL DEMAND (PATIENT-DAYS) 13,500 115,000 43,000 31. solution. The selection of a DESIRED OCCUPANCY PERCENTAGE i s conven-ient because i t can be link e d to past experience but i t i s s t i l l based on value judgements which d i f f e r from one planner to another. Because the d i s t i n c t i o n between operating e f f i c i e n c y and bed-capacity e f f i c i e n c y i s not cl e a r , the significance of occupancy percentages can be deceptive. Low occupancy can r e s u l t from either an i n e f f i c i e n t operation or from an oversupply of beds; the reverse applies to high occupancy. Forecasts that use fix e d occupancy rates seldom discuss the basis of the choice other than to state that, "Informed and experienced judgement seems to be the best option presently available f o r deciding upon desirable occupancy rates" (Martin, 1975). The problem can be approached from another angle by changing the focus of the forecast from the population as a whole to the i n d i v i d u a l h o s p i t a l . Using the forecast average d a i l y census as the base size of a h o s p i t a l , s t a t i s t i c a l theory can be used to determine the operating size that w i l l accommodate most of the demand fluctu a t i o n . Blumberg (1961) states that the Poisson d i s t r i b u t i o n may describe the f l u c t u -ations i n the demand f o r h o s p i t a l f a c i l i t i e s i f there are no serious bed shortages. Using t h i s d i s t r i b u t i o n , the standard deviation i s precisely the square root of the mean, which i s the average d a i l y census i n t h i s case. Since the pro b a b i l i t y that the demand fluctuations w i l l not exceed the mean plus three standard deviations i s s u f f i c i e n t l y high, i . e . , 0.997, the desired ho s p i t a l bed count can be determined by the following formula: j FORECAST HOSPITAL FORECAST ^\ /FORECAST BED REQUIREMENT AVERAGE \ / AVERAGE DAILY CENSUS W DAILY V CENSUS This method accommodates the r e a l i t y that small hospitals exper-32. ience wider demand fluctuations that do large hospitals. Thus, i n order to accommodate the peak periods, small hospitals must have a larger proportional bed reserve, which i n turn w i l l lower t h e i r average occupancy percentage. For example, an a r b i t r a r y average 90% occupancy percentage may not then be r e a l i s t i c f o r a 75 bed h o s p i t a l . Table VI i l l u s t r a t e s the relationship between the forecast AVERAGE DAILY CENSUS and the DESIRED HOSPITAL BED COUNT using the Poisson method. TABLE VI RELATIONSHIP OF AVERAGE DAILY CENSUS TO DESIRED HOSPITAL BED COUNT FORECAST SQUARE ROOT FORECAST HOSPITAL OCCUPANCY AVERAGE DAILY OF A.D.C. BED REQUIREMENT PERCENTAGE CENSUS (A.D.C.) _____ 1600 40 1720 93% 400 20 460 87% 100 10 130 77% 25 5 40 63% Table VI c l e a r l y shows that smaller hospitals require a larger bed margin above the forecast Average Daily Census to accommodate random fluctuations i n demand. These fluctuations force smaller hospitals to operate at occupancy percentages lower than those that can be attained by larger hospitals. When very small h o s p i t a l units are considered, the Poisson method w i l l indicate wide census swings and, thus, large required bed reserves. In r e a l i t y , however, the hospital admissions f o r scheduled procedures dampen these swings, making the Poisson method inappropriate. To overcome t h i s problem, the state planning agency of Alabama only uses the Poisson method f o r larger hospital u n i t s , and uses the t r a d i t i o n a l occupancy guides f o r smaller units (Melum, 1975). These f i v e Equations, noted i n Table IV, summarize current methods used to forecast the GROSS TOTAL DEMAND f o r h o s p i t a l services for a s p e c i f i c population group, and to transform t h i s t o t a l i n t o a forecast of HOSPITAL BED REQUIREMENTS for groups of hospitals or indivi d u a l hospitals. 34. CHAPTER V METHODOLOGY During the summer of 1976, separate examinations of the future acute-care-bed requirements of the Greater Vancouver Regional Hospital D i s t r i c t (G.V.R.H.D.) were being conducted by both the Regional and Pro v i n c i a l hospital-planning agencies. The method used by B r i t i s h Columbia Hospital Programs (B.C.H.P.) followed a t r a d i t i o n a l fore-casting pattern as described i n Chapter IV to estimate the 1981 demand for each of the nine sub-Regional d i s t r i c t s that make up the G.V.R.H.D. However, t h i s method d i d not account f o r intra-Regional patient flow and did not d i r e c t l y l i n k a forecast of the net demands of the s i x sub-Regional d i s t r i c t s that have hospitals to the proposed bed capacities of those hospitals. For these reasons, the proposed bed capacities were not unanimously accpeted within the Region. In addition, there were differences of opinion on both the future pop-ula t i o n estimates and the forecast incidence rates used by B.C.H.P. In order to discuss these differences of opinion, the G.V.R.H.D. altered the values of the input variables used by B.C.H.P. and then manually calculated alternate forecasts. The discussion of p o l i c y issues was hampered by the slow response of the manual forecasting method. To overcome these d i f f i c u l t i e s , I developed f o r the G.V.R.H.D., a modification of the B.C.H.P. forecast i n the form of a computer program with interchangeable data f i l e s . This enabled a quick response-time to questions about "what would happen i f ...?" The B.C.H.P. fore-cast was straight forward i n i t s method and i t did break down the sub-Regional population groups into age c l a s s i f i c a t i o n s that had d i s t i n c t 35. hospital use patterns. However, i t did not incorporate such current techniques as the use of high and low ranges for incidence rate and population forecasts, the use of occupancy factors related to the size of in d i v i d u a l h o s p i t a l s , and, as mentioned e a r l i e r , the use of a mechanism to account f o r intra-regional transfers and to all o c a t e inflow among the d i s t r i c t s . The computer forecasting program that I developed could have incorporated a l l of these techniques but would then have confused the Regional and P r o v i n c i a l p o l i c y makers by making them choose the "more correct" forecast. To be useful, the forecasting program had to be d i r e c t l y comparable to the " o f f i c i a l " B.C.H.P. method and s t i l l provide a t o o l for the analysis of alternative values f o r the accepted variables. The most important area of concern was a method of incorpor-ating the infra-Regional transfers. The B.C.H.P. forecast had no such method. I decided to duplicate the B.C.H.P. method up to the forecast of the GROSS TOTAL DEMAND for each d i s t r i c t . At t h i s point, the GROSS DEMAND and the INFLOW to the G.V.R.H.D. were i n t e r n a l l y allocated to the Region's d i s t r i c t s according to the current patient-flow patterns. By using t h i s approach, the two agencies could agree on the forecast of the basic GROSS TOTAL DEMAND but debate the a l l o c a t i o n of required f a c i l i t i e s . The computer forecasting program was organized so that d i f f e r e n t values of variables could be incorporated and the r e s u l t i n g alternate forecasts quickly produced. Examples of such alternate forecasts are described i n Chapter VI. The computer program was validated by comparing the GROSS TOTAL DEMAND t o t a l s calculated by the computer forecasting method and the B. C.H.P. method. A summary of t h i s comparison i s discussed i n Chapter VI. 36. THE COMPUTER FORECAST COMPONENTS The following section describes the components (variables and processes) of the computer forecasting program and t h e i r i n t e r - r e l a t i o n -ships. These inter-relationships are shown on the fold-out flow diagram, Figure 1. DISTRICTS The twelve municipalities and three e l e c t o r a l areas of the G.V.R.H.D. are organized into nine school d i s t r i c t s . Because hos-p i t a l insurance records note the school d i s t r i c t as the patient's place of o r i g i n , these school d i s t r i c t s can be conveniently used as the basic population groups f o r G.V.R.H.D. planning. These d i s t r i c t s are l i s t e d i n Table VII. N6. 36 37 38 39 40 41 43 44 45 TABLE VII SUB-REGIONAL DISTRICTS OF THE GREATER VANCOUVER REGIONAL HOSPITAL DISTRICT SCHOOL DISTRICT Surrey Delta Richmond Vancouver New Westminster Burnaby Coquitlam North Vancouver West Vancouver SUB-REGIONAL DISTRICT Surrey /-North Delta \. Ladner Richmond Vancouver New Westminster Burnaby Coquitlam } North Shore In most cases, the d i s t r i c t s are reasonable geographic e n t i t i e s 37. for h o s p i t a l planning purposes. However, i n t h i s t h e s i s , two modific-ations were made to better s u i t the population concentrations. D i s t r i c t No. 37, Delta, has two d i s t i n c t population centres, each having d i f -ferent relationships with neighbouring areas. Hence, North Delta with 48% of the population and Ladner with 52% were created. They each were assumed to have the same per capita experience f o r h o s p i t a l use as f o r Delta as a whole. The second modification concerned D i s t r i c t s 44 and 45, North and West Vancouver, which are separated from the r e s t of the G.V.R.H.D. by water and can reasonably be considered as one e n t i t y f o r hospital planning purposes. The re s u l t i n g combined u n i t , l a b e l l e d "North Shore", assumed a population weighted average of the per capita ho s p i t a l use experience of North and West Vancouver. POPULATION The POPULATION of each d i s t r i c t was grouped into the c l a s s i f -ications shown i n Table V I I I . TABLE VIII POPULATION AGE - SEX GROUPS AGE CLASSIFICATION 0 - 1 4 yrs. Paediatric 15 - 44 yrs. female Maternity 15 - 69 yrs. Adult Medical £ Surgical (less maternity) 70 + yrs. G e r i a t r i c Medical £ Surgical Each of these groups was considered to be a separate population having no in t e r a c t i o n with the others. Separate regional forecasts were made f o r each population group and then these forecasts were summed 3 8 . to produce the t o t a l Regional forecast. INCIDENCE RATES Separate INCIDENCE RATES OF HOSPITALIZATION for each population group In each d i s t r i c t were used. I would have preferred t o use separate forecasts of HOSPITAL ADMISSION RATES per 1000 population and AVERAGE LENGTHS OF STAY to determine the INCIDENCE RATES as shown by the dotted l i n e s i n Figure 1. However, to ensure that the two forecasts would be as s i m i l a r as possible i n format, I used the B.C.H.P. INCIDENCE RATES. GROSS DEMAND The POPULATION of each d i s t r i c t age group was mu l t i p l i e d by i t s corresponding forecast INCIDENCE PATE to produce the GROSS DEMAND for h o s p i t a l i z a t i o n expressed i n patient-days per year by d i s t r i c t . TRANSFER MATRIX The GROSS DEMAND fo r each d i s t r i c t was dis t r i b u t e d among the other G.V.R.H.D. d i s t r i c t s and outside the Region by multiplying the GROSS DEMANDS by the Relevance Indices of the TRANSFER MATRIX defined below. Relevance Indices, as discussed i n Chapter IV, usually r e f l e c t the proportion of a population's t o t a l h o s p i t a l use that i s serviced by each hospital i n a region. At the time t h i s study was under-taken, the future number and location of G.V.R.H.D. hospitals was uncertain. To avoid the problem r e s u l t i n g from t h i s uncertainty, the intra-Regional r e f e r r a l s were transformed into a d i s t r i c t - b y - d i s t r i c t matrix rather than a d i s t r i c t - b y - h o s p i t a l matrix; that i s , the Relevance Indices were for patient flows among d i s t r i c t s of patient o r i g i n and d i s t r i c t s of patient treatment rather than among d i s t r i c t s of patient o r i g i n and hospitals of patient treatment. A TRANSFER MATRIX was computed from 1975 data f o r each of the four age-sex groups. Table IX shows a t y p i c a l TRANSFER MATRIX used i n th i s study. The numbers i n each row show, f o r the d i s t r i c t of patient *********************** TRANSFER MATRIX ASSUMED *********************** PATIENT ORIGIN ******* S ND SURREY .550 .000 NORTH DELTA .350 .0 00 LADNER .350 .00 0 RICHMOND .000 .000 VANCOUVER .000 .000 NEW WEST .UOO .000 BURNABY .0U0 .0 00 COQUITLAM .000 .000 NORTH SHORE .UOO .000 AREA OF HOSPITAL TREATMENT ************************** L .000 .000 .000 ,000 ,000 ,0 00 ,000 .0 00 000 R .000 .100 .100 .400 .000 .000 .000 .000 .000 V , 250 ,400 ,400 ,550 ,900 200 450 300 350 NW .150 . 100 .100 .000 , ouu , /oo ,200 ,600 000 B . 05u .050 ,050 ,050 ,100 ,050 ,3 50 050 000 .000 . 000 .000 .000 .000 .000 .UOO ,uoo ,000 N3 .000 .000 . OuO ,000 .000 ,000 ,000 ,000 650 OUT .000 . 000 .000 .000 .000 .050 .000 .050 .000 TOTAL 1 . 000 1.000 1 . 000 1. OuO 1. 000 1 .000 1 .000 1 .OuO 1.000 CO CD TABLE IX: TYPICAL TRANSFER MATRIX (Paediatric Age-Sex Group) 40. o r i g i n , the proportions of the GROSS DEMAND that are treated i n the other G.V.R.H.D. d i s t r i c t s . For example, the number .250 i n the Surrey Row and "V" column, means that 25% of the d i s t r i c t of Surrey's demand for hospital care i s treated i n Vancouver f o r t h i s p a r t i c u l a r age group forecast. C l e a r l y , the numbers i n each row must t o t a l 1.0. The columns define the d i s t r i c t s where the patients are treated, and consist of the same nine d i s t r i c t s of o r i g i n plus the column "OUT", representing OUTFLOW f o r treatment outside the G.V.R.H.D. and thus beyond the scope of t h i s study. With regard to the patient-day allocations w i t h i n a d i s t r i c t , i t was assumed that once the FORECAST HOSPITAL BED REQUIREMENTS of a d i s t r i c t were determined, then the a l l o c a t i o n of those requirements to exi s t i n g and new hospitals within that d i s t r i c t would need to be the subject of a more detailed study. INFLOW The hospitals i n the G.V.R.H.D. o f f e r Regional r e f e r r a l services to adjacent communities and t e r t i a r y r e f e r r a l services f o r the whole province of B r i t i s h Columbia. In 1975, the patient-day volume from outside the G.V.R.H.D. that was serviced by Regional hospitals was the equivalent of approximately 720 acute-care-hospital beds * or 16% of the G.V.R.H.D's. own patient care volume. This i s a large volume and i t s d i s t r i b u t i o n among G.V.R.H.D. hospitals i s an important consider-ation when determining s p e c i f i c future requirements. * The inflow from outside the G.V.R.H.D. was 223,402 patient days i n 1975. At 85% occupancy, t h i s i s the equivalent of 720 beds. Data sources: B.C.H.P. data on magnetic tape. 41 For the purpose of the computer forecast, the INFLOW was stated as a percentage of the G.V.R.H.D. GROSS DEMAND i n patient days; a separate percentage was used f o r each age-sex group. NET DEMAND After the INFLOW was determined, i t was allocated among the d i s t r i c t s according to the specified percentages. The d i s t r i b u t e d INFLOW was then added to the DISTRIBUTED GROSS DEMAND to form the NET DEMAND forecast f o r each d i s t r i c t . AVERAGE DAILY CENSUS In order to convert the forecast NET DEMAND recorded i n patient-days to hospital bed equivalents, the t o t a l s were divided by 365 to produce the forecast AVERAGE DAILY CENSUS. OCCUPANCY PERCENTAGE The B.C.H.P. target OCCUPANCY PERCENTAGES were used i n the computer forecasting programme. I should have preferred to use the Poisson d i s t r i b u t i o n method, described i n Chapter IV, that varies the planned occupancy with the forecast AVERAGE DAILY CENSUS of the i n d i v -id u a l h o s p i t a l . However, to avoid confusing the more important issue of the recognition of intra-Regional transfers, I adopted the B.C.H.P. policy of se t t i n g target OCCUPANCY PERCENTAGES, no matter how inapprop-r i a t e they may be when applied to s p e c i f i c hospitals. FORECAST HOSPITAL BED REQUIREMENTS The forecast AVERAGE DAILY CENSUS was divided by i t s correspond-ing OCCUPANCY PERCENTAGE to produce the FORECAST HOSPITAL BED REQUIRE-MENTS f o r each age-sex group of each d i s t r i c t . BALANCE OF BEDS REQUIRED The program was extended by a simple step to compare the FORECAST HOSPITAL BED REQUIREMENTS with the bed t o t a l s proposed by B.C.H.P. f o r 42. the target date, i n this case, 1981. This comparison produced the BALANCE OF BEDS REQUIRED to meet the forecast. I f the FORECAST HOSPITAL BED REQUIREMENTS are adopted as targets, this calculation provides the policy analysts with the incremental changes necessary to modify the proposed bed totals to match the forecast requirements of the d i s t r i c t s . 43. CHAPTER VI EXPERIMENTAL PROCEDURES FORECAST PROCEDURE The structure of the forecasting process was translated into a computer program using the BASIC language. A copy of the program i s attached as Appendix A. I t was designed from the sequential steps suggested i n the other current forecasting methods noted i n Chapter IV, and the forecast produced by B.C.H.P. The forecasting program was designed f o r use on a time-sharing computer f a c i l i t y with input through cathode-ray-tube terminals and output from either the terminals or pri n t e r s . In order to o f f e r maximum f l e x i b i l i t y i n producing forecasts f o r policy analysis, the f i l e s containing the values of the program variables are external to the forecast program. This allows the user to create a sp e c i f i c forecast from any selected data sets. In addition, the program can be run for one or more age-sex group forecasts with the option of combining the separate runs into a summary forecast. A series of instructions appear on the terminal screen and lead the user through the process i n t e r -a c t i v e l y . Users can operate the program without having to know the d e t a i l s of either i t s i n t e r n a l processes or the l i n k s to the data f i l e s , but the user must know the names of the, data f i l e s because they are required as inputs to allow the program to function. The program output displays i n tabular form both the values i n i t i a l l y specified by the user fo r the program variables, and the comparison between the required and planned hospital beds for those d i s t r i c t s which contain hospitals. The d i s t r i c t s are then regrouped to four geographic areas and the comparison i s repeated. This information i s produced f o r 44. each run; a run consists of a forecast f o r one age-sex group or a summary of two or more age-sex-group forecasts. DATA The computer forecasting program was created to explore alternatives to the B.C.H.P. forecast, and to f a c i l i t a t e the resolution of differences of opinion on polic y issues. Thus, i t was necessary to avoid disagreements about the method used i n the computer program since such disagreements would have pre-empted worthwhile discussion about the G.V.R.H.D.'s contention that the B.C.H.P. planning proposal was not appropriate because i t didn't recognize intra-Regional patient transfers. In order to avoid such disagreements, the structure of the computer program was based on the B.C.H.P. forecast, as were the primary input data. The computer program could then be used to provide alternate forecasts f o r the examination of policy options by a l t e r i n g the input data. POPULATION In the autumn of 1976, there was considerable debate over the projections of the G.V.R.H.D. population. The preliminary release of the 1976 S t a t i s t i c s Canada census showed that the previously rapid growth of the G.V.R.H.D. had severely slowed. These r e s u l t s made e a r l i e r 1981 population projections appear u n r e a l i s t i c . Consequently, B.C.H.P. adjusted t h e i r 1981 population projections of the nine G.V.R.H.D. school d i s t r i c t s and used past census data to estimate the d i v i s i o n of these t o t a l s into the four age-sex groups. The forecasts of the d i s t r i c t s ' t o t a l population were rounded to the nearest thousand, but, f o r some unexplained reason, the age-sex-group forecasts appeared accurate to one d i g i t . This was not reasonable i n l i g h t of the tentative nature of the 45. o r i g i n a l forecast. To improve on t h i s , I rounded the data as c l o s e l y as possible to the nearest 50 persons without substantially s h i f t i n g the mix of the age groups or a l t e r i n g the t o t a l forecast f o r each d i s t r i c t . INCIDENCE RATES The Incidence Rates of Hospitalization were used d i r e c t l y from the B.C.H.P. forecast. The Pr o v i n c i a l planners had examined the general decline i n h o s p i t a l i z a t i o n and judged that the trend would continue to 1981. Their estimate was also influenced by the government's adopted p o l i c y of strengthening the delivery of extended and intermediate care and reducing the inappropriate use of acute-care-hospital f a c i l i t i e s . This planned reduction i n acute care h o s p i t a l i z a t i o n was not s p e c i f i c a l l y j u s t i f i e d by a quantitative r e l a t i o n , but i t was i m p l i c i t l y included i n the forecast incidence rates. These two data sets were the primary base used to forecast the Gross Demand f o r h o s p i t a l i z a t i o n f o r each of the d i s t r i c t s by age-sex group. Up to t h i s point, the two forecasts produced e s s e n t i a l l y i d e n t i c a l r e s u l t s , with any differences being due to the rounding of the population t o t a l s f o r i n d i v i d u a l age-sex groups. TRANSFER MATRIX The data used to produce the transfer matrix did not come d i r e c t l y from the B.C.H.P. forecast because t h i s component of the computer program was an addition to the P r o v i n c i a l method. B.C.H.P. has f o r several years produced data on the source and destination of G.V.R.H.D. ho s p i t a l patients. This information i s compiled from hospital-insurance data and made a v a i l -able to the Region, but i s not published. As of December 1976, the l a t e s t compiled information from B.C.H.P. was based on 1974 data. The basic 1975 46. data tapes were i n use at the University of B r i t i s h Columbia and special arrangements were made through the Division of Health Services, Research and Development* to extract the data on intra-G.V.R.H.D. patient transfers i n a form consistent with the B.C.H.P. format. The data was processed using routines contained i n the S t a t i s t i c a l Package f o r the Social Sciences (S.P.S.S.) available at the U.B.C. Computing Centre. The patient transfer data, i n patient days, was organized to show matrices of d i s t r i c t of patient o r i g i n (9) by ho s p i t a l of patient treatment (17), f o r each age-sex group. These matrices were converted manually into Transfer Matrices of Relevance Indices showing d i s t r i c t of patient o r i g i n (9) by d i s t r i c t of patient treatment ( 9 + 1 for outflow). These indices were i n i t i a l l y computed to three places of decimal f o r 1975 data. To make the Relevance Indices consistent with the uncertainty of the data used i n the e a r l i e r portion of the forecast, the use of accuracy to the t h i r d decimal-place had to be changed because i t gave a f a l s e implication of precision. A Relevance Index with an implied accuracy to .001 cannot legitimately be applied to a patient day t o t a l format derived from a population estimate rounded to the nearest 1000 persons. To resolve t h i s problem, the Relevance Indices were f i r s t rounded to the nearest 1% and then to the nearest 5% to te s t the s e n s i t i v i t y of the computations to such changes. The rounding to the nearest 5% produced r e s u l t s that only varied from the base r e s u l t s by approximately 1%; t h i s v a r i a t i o n was considered acceptable i n a t t a i n i n g an internal-data consistency f o r the computer forecasting program. The future a l l o c a t i o n of patients to Regional hospitals was a highly controversial subject since i t could a f f e c t the operating size of each *Division of Health Services, Research and Development Co-ordinator's O f f i c e , Health Sciences Centre, U.B.C. Vancouver, B.C. 47. h o s p i t a l . In order to study the effects of alternate p o l i c i e s , I ran the computer forecasting program with an alternate Transfer Matrix to r e f l e c t an alternate bed d i s t r i b u t i o n policy. This analysis i s described l a t e r i n t h i s chapter. The 1975 pattern of patient r e f e r r a l s within the G.V.R.H.D. was used as the 1981 Transfer Matrix f o r the Standard Forecast produced by the computer program. This was done to introduce the concept of the Transfer Matrix with ininimal controversy; the " i f present trends continue" approach. INFLOW The B.C.H.P. forecast accounted f o r the Inflow of patients into the G.V.R.H.D. by subtracting the Outflow from the Inflow to create a net Inflow expressed as a percentage of the t o t a l G.V.R.H.D. ho s p i t a l usage. B.C.H.P. studied the h i s t o r i c a l pattern of net Inflow to the G.V.R.H.D. before the 1981 rate was forecast. Because the Transfer Matrix of the computer program incorporates the Outflow, i t was decided to separate Inflow from Outflow rather that use the B.C.H.P. composite Inflow rate. The data on the Inflow of patients into the G.V.R.H.D. and on t h e i r d i s t r i b u t i o n among the Region's hospitals was obtained from the analysis that produced the Transfer Matrix. For the purpose of forecasting the Net Demand for h o s p i t a l services i n the G.V.R.H.D., the Inflow to the G.V.R.H.D. should be related to the Gross Demand of the B r i t i s h Columbia population outside the G.V.R.H.D., the source of the Inflow to the Region. However, since a population forecast, consistent with the one used f o r the G.V.R.H.D., was not available f o r the rest . of the province, I decided to r e l a t e the Inflow to the Gross Demand of the G.V.R.H.D. as a second-best method. This convenience produces r e s u l t s j u s t as acceptable as the more t h e o r e t i c a l l y correct method since i t i s reasonable to assume that 48. the Gross Demand of the B.C. population outside of the G.V.R.H.D. w i l l be subject to the same influence as the Gross Demand of the G.V.R.H.D. and thus w i l l fluctuate similarly to the Gross Demand of the G.V.R.H.D. The actual 1975 Inflow i n patient-days for each age-sex group was expressed as a percentage of the total 1975 Gross Demand of that age-sex group. These percentages were then used i n the forecasting program to produce forecast Inflow. The distribution of the total inflow among the Region's dis t r i c t s was expressed as proportions of the total Inflow i n the Inflow Transfer Vector. For example, New Westminster received .05 of the total referrals i n the adult age-sex group (ages 15-69) i n 1975. In order to avoid spurious accuracy, and to be consistent with the previous use of 1975 data, the Inflow percentages and the Inflow Transfer Vector's percentages were rounded. Since a 2 - 3% change i n the Inflow percentages caused significant absolute changes i n the forecast Inflow patient-days, the Inflow percentages were rounded to the nearest 1%. Because such changes to the Inflow Transfer Vector's percentages did not produce significant absolute changes i n the dis-tribution of Inflow patient-days, the percentages were rounded to the nearest 5%, consistent with the Transfer Matrix Relevance Indices. OCCUPANCY PERCENTAGES The Occupancy Percentages used to transform the Net Demand i n patient-days by d i s t r i c t to Forecast Hospital Bed Requirements were those used by B.C.H.P.: 80% for maternity, 85% for paediatrics, and 90% for adult. The reason for this choice has been discussed i n Chapter V. PLANNED BEDS The f i n a l data set used i n the computerized forecasting program 49. i s the sum of the hospital beds serving each age group that i s planned f o r each d i s t r i c t by 1981. These t o t a l s were obtained from an unpublished B.C.H.P. working paper e n t i t l e d "Review of the 1981 Bed Matrix". Any other proposal could have been incorporated since i t i s only used by the program as a benchmark f o r comparison with the G.V.R.H.D. forecast bed requirements. However, since part of the objective of t h i s thesis was to compare the re s u l t s of the two forecasting techniques using the same basic data and the same basic method except f o r the addition of the transfer matrix i n the computer forecasting program, the use of the B.C.H.P. proposal was appropriate. VERIFICATION The computer forecasting program was validated by producing a te s t forecast using a neutral* Transfer Matrix and then comparing the forecast of NET DEMAND patient-days f o r each age-sex group of each d i s t r i c t with the equivalent B.C.H.P. forecast. A se l e c t i o n of the results i s l i s t e d i n Table X. Since both the forecasts use the same data, the comparison should show absolutely no va r i a t i o n . There i s s l i g h t v a r i a t i o n i n the r e s u l t s that i s caused by the rounding of the B.C.H.P. population forecast t o t a l s . The reasons f o r t h i s rounding have been noted i n Chapter V. The va l i d a t i o n process confirmed that the computer program contained the same i n i t i a l structure as does the B.C.H.P. forecast and that the complexity of the structure created i n the computer program to accommodate intra-Regional patient transfers had not contaminated the c a l c u l a t i o n sequence. *The Neutral Transfer Matrix had values of 1.0 on the main diagonal to correspond with the f a c t that the B.C.H.P. forecast has no matrix. 50. TABLE X COMPARISON OF GROSS DEMAND I N PATIENT DAYS OF PAEDIATRIC AGE GROUP AND TOTAL POPULATIONS BY DISTRICT BETWEEN THE B.C.H.P. AND THE G.V.R.H.D. FORECASTS PAEDIATRIC AGE GROUP TOTAL POPULATION BCHP GVRHD % GVRHD VARIATION BCHP GVRHD % GVRHD VARIATION SURREY 15,345 15,342 0.02 185,879 185,882 0.00 DELTA 9,030 9,030 0.00 61,892 61,828 0.10 RICHMOND 8,293 8,296 0.04 88,145 88,084 0.07 VANCOUVER 27,000 27,000 0.00 649,520 649,515 0.00 NEW WEST. 3,093 3,088 0.16 57,430 57,488 0.10 BURNABY 11,025 11,025 0.00 153,293 153,290 0.00 COQUITLAM 10,605 10,609 0.04 92,853 92,845 0.01 NORTH SHORE 9,608 9,595 0.14 158,012 158,103 0.01 TOTAL 93,999 93,986 0.01 1,447,024 1,447,036 0.00 51. THE SENSITIVITY ANALYSIS The B.C.H.P. forecast was made from the interaction of many variables such as population, age group and incidence rate. It is true that any change in input variables could be manually traced through the maze of calculations to explain the interactions, but, considering the number of changes possible, such a procedure would be impractical. The introduction of a Transfer Matrix would have made the interaction even more complex i f calculated manually. The computerization of the fore-cast made i t feasible to study the effect on the final FORECAST OF HOSPITAL BED REQUIREMENTS of a change in the value of any one of the variables. Since the computerized forecasting program incorporates non-linear relations, any given input change in the value of a variable does not necessarily produce a proportional change in a given output forecast. For example, since the age mix varies among the districts as do the incidence rates of hospitalization, an equal proportional change in each district to the value of either, or both of these variables would produce disproportionate changes in the net demand for hospital services in each district because of the non-linear relations introduced by the Transfer Matrix. In order to examine this aspect of the forecast program, several controlled changes made to the input data were compared with the corres-ponding changes produced i n the output forecast. This experiment was called a SENSITIVITY ANALYSIS. The six primary variables (population, incidence rate, inflow, distribution of inflow, transfers, and occupancy percentage) could produce an unmanageable set of interactions i f a f u l l sensitivity study were undertaken. It was decided to restrict the analysis to the two most controversial variables: population and incidence 52. rate. The B.C.H.P. forecasts of the G.V.R.H.D. population's rate of growth, its age distribution, and its geographic distribution were based on both the preliminary federal census and on past distributions. However, with-out the benefit of a detailed census, the G.V.R.H.D. believed that there was l i t t l e likelihood that the forecasts would be accurate. The B.C.H.P. forecasts of Incidence Rates of Hospitalization were based partly on the assumption that alternate facilities to acute care would be available to reduce the acute-care Incidence Rates. There was some doubt when the forecast was discussed in 1976 whether these alternate facilities really would be available and, therefore, some doubt whether the lower Incidence Rates could be achieved. Since there was no consensus on the values of these variables, the computer forecasting program was used to explore how sensitive the forecasting process was to changes in the values of the Population and Incidence Rate of Hospitalization variables. First, the possibility of the geriatric age group (70+ years) rising to 10% of the total population was considered. Since the Incidence Rate projected for that group is almost four times the regular adult rate, such a change would be expected to reveal any unexpected results from obscure interactions. Secondly, a change in the Incidence Rate for this age group also would be expected to reveal unexpected sensitivities. Table XI outlines the eight runs that were made to analyse the sensitivity of the computer forecasting technique. RUN ONE: This run was used as the standard for the analysis since i t contained the base data from the B.C.H.P. 1981 forecast with the addition of 1975 transfer and inflow data. 53. TABLE XI INPUT CHANGES MADE FOR THE SENSITIVITY ANALYSIS RUN AGE GROUP POPULATIONS INCIDENCE RATES ONE GERIATRIC ADULT STANDARD STANDARD STANDARD STANDARD TWO GERIATRIC ADULT PLUS 64% STANDARD MINUS GERIATRIC INCREASE STANDARD THREE GERIATRIC ADULT PLUS 64% -10% MINUS GERIATRIC INCREASE STANDARD FOUR GERIATRIC ADULT PLUS 64% STANDARD MINUS GERIATRIC INCREASE -10% FIVE GERIATRIC ADULT PLUS 64% -10% MINUS GERIATRIC INCREASE -10% SIX GERIATRIC ADULT PLUS 64% +10% MINUS GERIATRIC INCREASE STANDARD SEVEN GERIATRIC ADULT PLUS 64% STANDARD MINUS GERIATRIC INCREASE +10% EIGHT GERIATRIC ADULT PLUS 64% +10% MINUS GERIATRIC INCREASE +10% 54. RUN TWO: In t h i s run, the percentage of the g e r i a t r i c age group was increased from approximately 6% to 10% of the t o t a l G.V.R.H.D. population; an increase of approximately 64%. This change brought the t o t a l G.V.R.H.D. g e r i a t r i c population from 69,175 to 113,500. The e x i s t i n g age-group r a t i o s vary among d i s t r i c t s and, ujifortunately, i t was not possible to estimate how these r a t i o s would vary from each other i n the future, therefore, proportional changes, rather than absolute changes were made to the g e r i a t r i c populations of each d i s t r i c t , that i s , the g e r i a t r i c population of each d i s t r i c t was increased by 64%. In turn, t h i s meant that the adult population i n any given d i s t r i c t was decreased by an amount equal to the g e r i a t r i c population increase so that the combined a d u l t - g e r i a t r i c pop-ul a t i o n group remained constant i n t o t a l . This population s h i f t was retained i n each of the following s e n s i t i v i t y runs. A l l other variables had standard values. RUN THREE: The incidence rates of the g e r i a t r i c population group i n each d i s t r i c t were decreased by 10%, while the adult incidence rates remained at standard l e v e l s . RUN FOUR: The incidence rates of the adult population group i n each d i s t r i c t was decreased by 10% while the g e r i a t r i c incidence rates remained at standard l e v e l s . RUN FIVE: The incidence rates of both the g e r i a t r i c and the adult pop-u l a t i o n groups i n each d i s t r i c t were decreased by 10%. RUN SIX: The incidence rate f o r the g e r i a t r i c population i n each d i s t r i c t group was increased by 10%, while the adult incidence rates remained at standard l e v e l s . RUN SEVEN; The incidence rates of the adult population group i n each d i s t r i c t were increased by 10%, while the g e r i a t r i c incidence rates remained at standard l e v e l s . 55. RUN EIGHT: The incidence rate of both the g e r i a t r i c and adult population groups i n each d i s t r i c t were increased by 10%. THE POLICY ANALYSIS The P r o v i n c i a l Ministry of Health and the Greater Vancouver Regional Hospital D i s t r i c t share i n the costs of hosp i t a l construction within the G.V.R.H.D. The agencies, therefore, have assumed a mandate from t h e i r electorates to ensure that the most ef f e c t i v e changes i n h o s p i t a l service r e s u l t from the expenditure of public funds for h o s p i t a l construction. In order to forecast the expenditures required f o r h o s p i t a l construction, these two agencies must agree on the future values of the variables used i n the forecast of the demand for hospital services. However, a l l of these variables can be influenced, to some degree, by po l i c y decisions. For example, future POPULATION t o t a l s can be influenced by immigration p o l i c i e s , by economic p o l i c i e s and by urban-planning p o l i c i e s ; future RELEVANCE INDICES can be influenced by geographic s h i f t s i n population, by hospital operating p o l i c i e s and by hospital construction p o l i c i e s . To e f f e c t i v e l y discharge t h e i r mandate, the funding agencies must analyse the effects of alternate policy positions. The computer fore-casting program, described i n Chapter V, was designed to r e a d i l y accept alternate input data so that alternate FORECASTS of HOSPITAL BED REQUIRE-MENTS can be used to study the effects of the alternate p o l i c y positions that the data r e f l e c t . The following sections describe the alternate p o l i c y positions which were analysed by comparing the corresponding forecast produced by the computer forecasting program to the Standard Forecast. 56. A. POPULATION During the summer of 1976, the G.V.R.H.D. was forecasting a 1981 Population of the Region of 1,322,000 persons, a t o t a l which proved to be 16% higher than the B.C.H.P. forecast which was made l a t e r i n the year based upon the interim r e s u l t s of the 1976 federal census. Since the G.V.R.H.D. questioned the accuracy of the 1976 federal census and, thus, the B.C.H.P. population forecast f o r 1981, the computer forecasting program was used to analyse the effects of a 10% increase i n the B.C.H.P. population forecast f o r 1981. Table XII shows the d e t a i l s of t h i s i n -crease . B. INCIDENCE RATES OF HOSPITALIZATION The B.C.H.P. forecast of the 1981 G.V.R.H.D. Incidence Rates of Hospital i z a t i o n was based on the assumption that alte r n a t i v e l e v e l s of care w i l l "soon" be avai l a b l e , and thus, the acute-care Incidence Rates should f a l l . Since the G.V.R.H.D. questioned t h i s assumption, the com-puter forecasting program was used to analyse the effects of a 10% increase i n the 1981 Incidence Rates of Hosp i t a l i z a t i o n f o r each age-sex group i n each d i s t r i c t as forecast by B.C.H.P. Table XIII l i s t s the ov e r a l l increase by d i s t r i c t . The increased Incidence Rates l i s t e d were calculated by the program by div i d i n g the increased Total Gross Demand, i n patient-days, of each d i s t r i c t by that d i s t r i c t ' s population. Because of t h i s c a l c u l a t i o n , the increased Incidence Rates l i s t e d are not exactly 110% of the Standard Rates^because of rounding errors. C. INFLOW The G.V.R.H.D's. Inflow (patient-days) expressed as a percentage of the Gross Demand was assumed to remain constant to 1981; that i s , remain equal to the 1975 percentage. However, the G.V.R.H.D. was aware that t h i s 57. TABLE XII 1981 FORECAST G.V.R.H.D. POPULATION TOTALS AT 110% OF 1981 STANDARD POPULATION FORECAST DISTRICT SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WESTMINSTER BURNABY COQUITLAM NORTH SHORE STANDARD FORECAST 145,000 36,000 39,000 90,000 400,000 37,000 140,000 103,000 145,000 110% STANDARD 159,500 39,600 42,900 99,000 440,000 40,700 154,000 113,300 159,500 TOTAL 1,135,000 1,248,500 58. TABLE XIII 1981 FORECAST G.V.R.H.D. INCIDENCE RATES OF HOSPITALIZATION (PATIENT-DAYS/1000 POPULATION-YEAR) AT 110% of 1981 STANDARD INCIDENCE RATES FORECAST DISTRICT SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WESTMINSTER BURNABY COQUITLAM NORTH SHORE STANDARD 110% FORECAST STANDARD 1281 1410 825 909 823 907 978 1076 1623 1786 1553 1709 1094 1204 901 991 1090 1199 TOTAL 1274 1402 59. Inflow percentage may f a l l as a r e s u l t of the construction of more specialized h o s p i t a l f a c i l i t i e s outside the Region. The effects of t h i s hospital construction p o l i c y were analysed by reducing the G.V.R.H.D's. Inflow percentage by 10.0%. For example, the adult Inflow percentage of 19.0% was reduced by 10.0% to form an alternative Inflow percentage of 17.1%*. When t h i s percentage was applied to the Adult Gross Demand i n the Standard Forecast of 895,830 patient-days, the Inflow decreased from 170,208 to 153,187 patient-days, a reduction of 10%. Table XIV l i s t s the standard and the alt e r n a t i v e Inflow percentages TABLE XIV 1981 FORECAST INFLOW PERCENTAGES AT 0.9% OF 1981 STANDARD INFLOW PERCENTAGES AGE-SEX GROUP STANDARD INFLOW PERCENTAGE ALTERNATE INFLOW PERCENTAGE PAEDIATRIC 38.0 34.2 MATERNITY 8.0 7.2 ADULT 19.0 17.1 GERIATRIC 7.0 6.3 * See the Standard Forecast i n Appendix B. 60. The Inflow Transfer Vector that distributes the annual Inflow patient-days among the d i s t r i c t s of the G.V.R.H.D. was not altered to analyse the effects of an alternate Inflow d i s t r i b u t i o n p o l i c y because the Inflow i s currently d i s t r i b u t e d to specialized f a c i l i t i e s and no change i n these f a c i l i t i e s i s contemplated. D. TRANSFER MATRIX The Transfer Matrix used by the computer forecasting program to produce the Standard Forecast, r e f l e c t s the 1975 pattern of i n t r a -G.V.R.H.D. patient transfers. The use of t h i s pattern i n the forecast process means that the pattern i s not expected to change. However, as the G.V.R.H.D's population s h i f t s towards the sub-urban d i s t r i c t s , i t i s reasonable to assume that a greater proportion of these d i s t r i c t s ' annual Gross Demands for h o s p i t a l services should be accommodated by hospitals w i t h i n these d i s t r i c t s . The computer forecast-ing program was used to analyse the effect of the alternate p o l i c y that 80% of a d i s t r i c t ' s annual Gross Demands f o r acute-care h o s p i t a l services i s to be accommodated by the d i s t r i c t ' s own hospitals, with a further 10% to be transferred to more specialized regional r e f e r r a l h o s p i t a l s , and with the remaining 10% to be transferred to the ter t i a r y - c a r e services provided by designated'.hospitals i n Vancouver. Table XV displays the Transfer Matrix which was used to r e f l e c t t h i s alternate policy. The 80-10-10 policy was adapted to f i t the f o l -lowing c h a r a c t e r i s t i c s of the G.V.R.H.D.: 1. SURREY 80% of Gross Demand retained i n Surrey with 10% to the nearest regional r e f e r r a l h o s p i t a l , i n New Westminster, and 10% to the t e r t i a r y care hospitals i n *********************** TRANSFER MATRIX ASSUMED * * * * * * * * * * * * * * * * * * * * * * * PATIENT ORIGIN ******* S ND SURREY .800 .000 NORTH DELTA .800 .000 LADNER .000 .000 RICHMOND .000 .000 VANCOUVER .000 .000 NEW WEST .000 .000 BURNABY .00 0 .000 COQUITLAM .000 .000 NORTH SHORE .000 .000 AREA OF HOSPITAL TREATMENT * * * * * * * * * * * * * * * * * * * * * * * * * * L .000 .000 .800 .000 .000 .000 .000 .000 .000 R .000 .000 .000 .800 .000 .000 .000 .000 .000 V 100 100 200 200 950 ,100 ,150 ,100 200 NW .100 .100 .000 .000 .000 .900 .150 .100 .000 B .000 .000 .000 .000 .050 .000 .700 .000 .000 C .000 .000 .000 .000 .000 .000 .000 .800 .000 NS .000 .000 .000 .000 .000 .000 .000 .000 .800 OUT .000 .000 .000 .000 .000 .000 .000 .000 .000 TOTAL 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 TABLE XV: THE ALTERNATE TRANSFER MATRIX 62. Vancouver. 2. NORTH DELTA North Delta i s adjacent to Surrey's h o s p i t a l and thus, was given the same pattern as Surrey. 3. LADNER 80% retained i n Ladner with both the 10% regional and 10% t e r t i a r y transfers to Vancouver. 4. RICHMOND 80% retained i n Richmond with both the 10% regional and 10% t e r t i a r y transfers to Vancouver. 5. VANCOUVER 5% of Vancouver's Gross Demand to Burnaby because Burnaby's hos p i t a l i s on the boundary between these two d i s t r i c t s . The remaining 95% to remain i n Vancouver. 6. NEW WESTMINSTER 90% retained in New Westininster because of the lo c a t i o n there of a regional r e f e r r a l h o s p i t a l . 10% to Vancouver. 7. BURNABY 70% retained i n Burnaby and 5% each to Vancouver and New Weslaninster because of Burnaby's adjacency to nearby hospitals. A further 10% to the regional r e f e r r a l h o s p i t a l i n New Westminster. A further 10% to t e r t i a r y care hospitals i n Vancouver. 8. COQUITLAM 80% retained i n Coquitlam with 10% to New Westnrinster and 10% to Vancouver. 9. NORTH SHORE 80% retained i n the North Shore with 10% each to the regional and t e r t i a r y hospitals i n Vancouver. E. OCCUPANCY PERCENTAGE The B.C.H.P. forecast used "target" percentages f o r each age-sex group to compensate f o r fluctuations i n the demand f o r h o s p i t a l admissions. As described i n Chapter IV, a method using the Poisson d i s t r i b u t i o n can be used to account f o r the relationship between the si z e of the i n d i v i d u a l 63. hospital's forecast Average Daily Census and the expected range of demand fluctuations. To analyse the effects of using t h i s approach, rather than the "target" occupancy percentage approach, the forecast Average Daily Census for each d i s t r i c t was pro-rated to each of the d i s t r i c t ' s hospitals on the basis of e x i s t i n g h o s p i t a l bed capacities. From t h i s base, the forecast Hospital-Bed Requirement f o r each ho s p i t a l was calculated using the f o l -lowing formula: These Forecast Hospital-Bed Requirements were grouped by d i s t r i c t and then compared to the corresponding t o t a l s i n the Standard Forecast. The following Chapter gives the results of THE STANDARD FORECAST, THE SENSITIVITY ANALYSIS and THE POLICY ANALYSIS discussed i n t h i s Chapter. FORECAST HOSPITAL-BED REQUIREMENT FORECAST AVERAGE DAILY CENSUS 64. CHAPTER VII RESULTS THE STANDARD FORECAST The computer forecasting program was loaded with data described i n Chapter VI and produced the STANDARD FORECAST; a copy of t h i s output forecast i s attached as Appendix B. Tables XVI to XIX show the compar-ison between B.C.H.P's. planning proposal (labelled PLANNED BEDS) and the Standard Forecast produced by the computer forecasting program (labelled G.V.R.H.D's. NEEDED BEDS) with the Standard Forecast as the base. This comparison i s made f o r each of the following age-sex groups: Paediatric, Maternity, A l l Adult, and Total. The Adult (ages 15-69) and G e r i a t r i c (age 70 +) groups were combined for t h i s comparison because the B.C.H.P. method does not di f f e r e n t i a t e G e r i a t r i c acute-care hospital beds from other Adult beds i n the f i n a l proposal. Note, however, that t h e i r requirements are treated separately during the fore-cast. 65. TABLE XVI COMPARISON BETWEEN B.C.H.P. AND G.V.R.H.D. FORECASTS OF 1981 G.V.R.H.D. REQUIREMENTS FOR PAEDIATRIC ACUTE-CARE BEDS AREA B.C.H.P's. G.V.R.H.D's. (DISTRICT) PLANNED BEDS NEEDED BEDS BALANCE SURREY 44 43 1 LADNER 0 0 0 RICHMOND 26 14 12 VANCOUVER 200 254 -54 NEW WESTMINSTER 55 51 4 BURNABY 37 29 8 COQUITLAM 0 0 0 NORTH SHORE 24 26 -2 TOTAL 386 417 -31 66. TABLE XVII COMPARISON BETWEEN B.C.H.P. AND G.V.R.H.D. FORECASTS OF 1981 G.V.R.H.D. REQUIREMENTS FOR MATERNITY ACUTE-CARE BEDS AREA B.C.H.P's. G.V.R.H.D's. (DISTRICT) PLANNED BEDS NEEDED BEDS BALANCE SURREY 50 41 9 LADNER 0 0 0 RICHMOND 30 25 5 VANCOUVER 120 140 -20 NEW WESTMINSTER 40 46 -6 BURNABY 25 26 1 COQUITLAM 0 0 0 NORTH SHORE 32 34 -2 TOTAL 297 312 -15 67. TABLE XVIII COMPARISON BETWEEN B.C.H.P. AND G.V.R.H.D. FORECASTS OF 1981 G.V.R.H.D. REQUIREMENTS FOR ALL ADULT ACUTE-CARE BEDS AREA B.C.H.P's. G.V.R.H.D's. (DISTRICT) PLANNED BEDS NEEDED BEDS BALANCE SURREY 322 391 -69 LADNER 75 0 75 RICHMOND 173 133 40 VANCOUVER 2,616 2,705 -89 NEW WESTMINSTER 573 566 7 BURNABY 360 251 109 COQUITLAM 75 0 75 NORTH SHORE 400 408 - 8 TOTAL 4,594 4,454 140 68. TABLE XIX COMPARISON BETWEEN B.C.H.P. AND G.V.R.H.D. FORECASTS OF 1981 G.V.R.H.D. REQUIREMENTS FOR TOTAL ACUTE-CARE BEDS AREA B.C.H.P's G.V.R.H.D's. (DISTRICT) PLANNED BEDS NEEDED BEDS BALANCE SURREY 416 475 -59 LADNER 75 0 75 RICHMOND 229 172 57 VANCOUVER 2,936 3,099 -163 NEW WESTMINSTER 668 663 5 BURNABY 422 306 116 COQUITLAM 75 0 75 NORTH SHORE 456 468 -12 TOTAL 5,277 5,183 94 69. THE SENSITIVITY ANALYSIS The eight computer runs described i n ChapterVI provided a data base on changes i n the forecast NET DEMAND which the computer program produced i n response to changes made from the standard a d u l t - g e r i a t r i c population mixes and incidence rates. Since the separate paediatric and maternity forecasts were not affected by these data a l t e r a t i o n s , they were excluded from the s e n s i t i v i t y analysis. A. SENSITIVITY TO POPULATION CHANGES Runs 1 and 2 were compared to determine the " s e n s i t i v i t y " i n the NET DEMAND ( i n patient-days) of the combined d i s t r i c t a d u l t - g e r i a t r i c age groups, to increases i n the percentages of eld e r l y people related to the t o t a l adult population groups i n each d i s t r i c t . Table XX summarizes t h i s comparison and l i s t s the " s e n s i t i v i t y " defined as the percentage change i n NET DEMAND f o r each 1% increase i n the g e r i a t r i c population percentage of the t o t a l adult group. Note that t h i s d e f i n i t i o n i s used fo r convenience i n understanding the significance f o r the NET DEMAND of an increase i n the percentage of t o t a l population that i s g e r i a t r i c ; f o r example, from 6 to 7%. This " s e n s i t i v i t y " i s not the same as the formal S e n s i t i v i t y which i s defined as the percentage change i n OUTPUT ( i n t h i s case, NET DEMAND) r e s u l t i n g from a one percent change i n INPUT ( i n t h i s case, absolute POPULATION t o t a l s ) . B. SENSITIVITY TO INCIDENCE RATE CHANGES 1. Runs 2 and 3 were compared to determine the percentage change i n the NET DEMAND ( i n patient days) of the combined a d u l t - g e r i a t r i c age groups by d i s t r i c t that resulted from a 10% decrease i n the g e r i a t r i c incidence rates while the adult incidence rates were held constant. Table XXI summarizes t h i s comparison and includes a l i s t i n g of the s e n s i t i v i t y of 70. NET DEMAND by d i s t r i c t to a 1% decrease i n the g e r i a t r i c incidence rates. 2. Runs 2 and 5 were compared to determine the percentage change i n the NET DEMAND that resulted from a 10% increase i n the g e r i a t r i c incidence rates while the adult rates were held constant. The calculated sensi-t i v i t i e s were i d e n t i c a l to those i n the previous analysis, B - l , and therefore, were not tabulated. 3. Runs 2 and 4 were compared to determine the percentage change i n NET DEMAND that resulted from a 10% decrease i n the adult incidence rates while the g e r i a t r i c incidence rates were held constant. Table XXII summarizes t h i s comparison and includes a l i s t i n g of the s e n s i t i v i t y of NET DEMAND to a 1% decrease i n the adult incidence rates. 4. Runs 2 and 7 were compared to determine the percentage change i n NET DEMAND that resulted from a 10% increase i n the adult incidence rates while the g e r i a t r i c incidence rates were held constant. The calculated s e n s i t i v i t i e s were i d e n t i c a l to those i n the previous analysis, B-3, and therefore, were not tabulated. 5. Runs 2 and 5 were compared to determine the percentage change i n NET DEMAND that resulted from a 10% decrease i n both the g e r i a t r i c and the adult incidence rates. Table XXIII summarizes t h i s comparison and includes a l i s t i n g of the s e n s i t i v i t y of NET DEMAND to a 1% decrease i n both the g e r i a t r i c and the adult incidence rates. 6. Runs 2 and 8 were compared to determine the change i n NET DEMAND that resulted from a 10% increase i n both the g e r i a t r i c and the adult incidence rates. The calculated s e n s i t i v i t i e s were i d e n t i c a l to those i n the previous a n a l y s i s , B-5, and therefore, were not tabulated. 71. TABLE XX "SENSITIVITY" OF TOTAL ADULT NET DEMAND (IN PATIENT DAYS) TO A 1% INCREASE IN THE PERCENTAGE OF GERIATRIC POPULATION TO THE TOTAL ADULT POPULATION 1. 2. 3. 4. 5. Net Demand Change Ge r i a t r i c G e r i a t r i c " S e n s i t i v i t y " D i s t r i c t Total Adult In Net (Standard) Demand % Percent (Standard) Percent Increase (Col. 3 * Col. 5) Surrey 128,364 21,792 16.98 7.99 5.12 3.32 Richmond 43,573 5,351 12.28 5.18 3.33 3.69 Vancouver 888,610 109,621 12.34 10.49 6.72 1.84 New West. 185,981 23,196 12.47 11.80 7.57 1.65 Burnaby 82,346 16,195 19.67 6.33 4.06 4.84 North Shore 134,302 17,790 13.25 6.10 3.92 3.38 TOTAL 1,463,176 193,945 13.26 7.90 5.07 2.62 72. TABLE XXI D i s t r i c t Surrey Richmond Vancouver New West. Burnaby North Shore SENSITIVITY OF TOTAL ADULT NET DEMAND (IN PATIENT DAYS) TO A 1% DECREASE IN THE GERIATRIC INCIDENCE RATES 1. 3. G e r i a t r i c Net Demand Change % Change Incidence Total Adult In Net Net Rate (Run 2) Demand Demand Change 150,156 49,924 998,231 209,177 98,541 151,092 - 6,728 - 4.48 - 10.0 - 1,652 - 3.38 - 10.0 -38,791 - 3.89 - 10.0 - 7,755 - 3.71 - 10.0 - 4,898 - 4.97 - 10.0 - 5,702 - 3.75 - 10.0 S e n s i t i v i t y (Col. 3 * Col.4) 0.45 0.34 0.39 0.37 0.50 0.37 TOTAL 1,657,121 -65,526 - 3.95 - 10.0 0.40 73. TABLE XXII SENSITIVITY OF TOTAL ADULT NET DEMAND (IN PATIENT-DAYS) TO A 1 % DECREASE IN THE ADULT INCIDENCE RATES D i s t r i c t Net Demand Change Total Adult In Net (Run 2) Demand Adult % Incidence S e n s i t i v i t y Change Rate (Col. 3 * Net Demand % Change Col. 4) Surrey 150 ,156 - 8 ,317 - 5.53 - 10 .0 0 .55 Richmond 49 ,924 - 3, ,257 - 6.65 - 10, .0 0 .67 Vancouver 998 ,231 -61. ,022 - 6.11 - 10. .0 0, .61 New West. 209 ,177 -13. ,170 - 6.30 - 10. .0 0, .63 Burnaby 98 ,541 - 4. ,956 - 5.03 - 10. ,0 0. ,50 North Shore 151 ,092 - 9. ,383 - 6.17 - 10. 0 0. ,62 TOTAL 1,657,121 - 100,105 - 6.04 - 10.0 0.60 74. TABLE XXIII SENSITIVITY OF TOTAL ADULT NET DEMAND (IN PATIENT-DAYS) TO A 1% DECREASE IN BOTH THE GERIATRIC AND THE ADULT INCIDENCE RATES D i s t r i c t Net Demand Change % Change S e n s i t i v i t y Total Adult In Net Change Incidence (Col. 3 + (Run 2) Demand Net Demand Rates Col. 4) Surrey 150 ,156 - 15. ,045 - 10 .02 - 10 .0 1 .00 Richmond 48 ,924 - 4, ,909 - 10, .03 - 10 .0 1. .00 Vancouver 998 ,231 - 99, ,813 - 10. .00 - 10, .0 1, .00 New West. 209, ,177 - 20. ,925 - 10. .00 - 10. .0 1. .00 Burnaby 98. ,541 - 9. ,854 - 10. ,00 - 10. ,0 1. ,00 North Shore 151. ,092 - 15, ,086 - 9. 92 - 10. ,0 0. 99 TOTAL 1,657,121 165,632 - 10.00 - 10.0 1.00 75. THE POLICY ANALYSIS A. POPULATION The population of the G.V.R.H.D's age-sex groups by d i s t r i c t were increased by 10%, as explained i n Chapter VI, and the resu l t s were compared to the Standard Forecast. Table XXIV shows t h i s comparison with the Standard Forecast as the base. B. INCIDENCE RATES The incidence rates of the G.V.R.H.D's. age-sex groups by d i s t r i c t were increased by 10%, as explained i n Chapter VI and the r e s u l t s were compared to the Standard Forecast. The calculated r e s u l t s were i d e n t i c a l to the previous p o l i c y analysis, Population,and therefore, were not tabulated. C. INFLOW The inflow of patient-days to the G.V.R.H.D. was reduced by 10% as explained i n Chapter VI and the results were compared to the Standard Forecast. Table XXV shows t h i s comparison with the Standard Forecast as the base. D. TRANSFER MATRIX The Transfer Matrix, designed to r e f l e c t the ultimate patient-transfer p o l i c y described i n Chapter VI, was used i n the computer fore-casting program to produce Pol i c y Forecast D. Table XXVI compares t h i s forecast to the Standard Forecast, which i s used as the base. 76. E. OCCUPANCY PERCENTAGE The Poisson method of estimating the forecast Requirement f o r Hospital Beds above the forecast Average Daily Census to accommodate fluctuations i n the demand f o r hos p i t a l admissions, described i n Chapter VI, was applied to the forecast Average Daily Census of i n d i v i d u a l hospitals. The hospi t a l s ' forecast bed-compliments were summed by d i s t r i c t t o form P o l i c y Forecast E. Table XXVII compares Policy Forecast E to the Standard Forecast, which i s used as the base. 77. TABLE XXIV COMPARISON BETWEEN THE STANDARD FORECAST AND POLICY FORECAST A (POPULATION) D i s t r i c t s Surrey Ladner Richmond Vancouver New West. Burnaby Coquitlam North Shore Forecast Hospital Bed Requirements (Standard) 475 0 172 3,099 663 306 0 468 Forecast Hospital Bed Requirements (Policy A) 522 0 188 3,407 729 336 0 516 Increase Increase 47 16 308 66 30 48 10.0 9.3 9.9 10.0 9.8 10.3 TOTAL 5,183 5,698 515 9.9 78. TABLE XXV COMPARISON BETWEEN THE STANDARD FORECAST AND POLICY FORECAST C (INFLOW) D i s t r i c t s Surrey Ladner Richmond Vancouver New Westminster Burnaby Coquitlam North Shore Forecast Hospital Bed Requirements (Standard) 475 0 172 3,099 663 306 0 468 Forecast Hospital Bed Requirements (Policy C) 471 0 172 3,043 656 306 0 461 Decrease 0 56 7 0 TOTAL 5,183 5,109 74 7 9 . TABLE XXVI COMPARISON BETWEEN THE STANDARD FORECAST AND POLICY FORECAST D (TRANSFER MATRIX) Forecast Forecast Hospital Hospital Bed Bed D i s t r i c t s Requirements Requirements % (Standard) (Policy D) Difference Difference Surrey 475 571 + 96 + 20.2 Ladner 0 80 + 80 00 Richmond 172 217 + 45 + 26.2 Vancouver 3,099 2,798 - 301 - 9.7 New West. 663 400 - 263 - 40.0 Burnaby 306 435 + 129 + 42.2 Coquitlam 0 230 + 230 CO North Shore 468 458 - 10 - 2.1 TOTAL 5,183 5,189 + 6 * + 0.6 *This s l i g h t difference from Standard results from the exclusion of OUTFLOW from the P o l i c y Forecast f o r convenience i n programming the Transfer Matrix. 80. TABLE XXVII COMPARISON BETWEEN THE STANDARD FORECAST AND POLICY FORECAST E (OCCUPANCY PERCENTAGE) Forecast Forecast Hospital Hospital Bed Bed D i s t r i c t s Requirements Requirements % (Standard) (Policy E) Difference Differei Surrey 475 504 + 29 + 6.1 Ladner 0 0 0 -Richmond 172 188 + 16 + 9.3 Vancouver 3,099 3,203 + 104 + 3.4 New West. 663 689 + 26 + 3.9 Burnaby 306 320 + 14 + 4.6 Coquitlam 0 0 0 -North Shore 468 479 + 11 + 2.4 TOTAL 5,183 5,383 + 200 + 3.9 81. CHAPTER VIII DISCUSSION THE STANDARD FORECAST The B.C.H.P. planning proposal was based on t h e i r forecast of the Gross Demand ( i n patient days) expected by the G.V.R.H.D.'s d i s t r i c t s . The connection between that forecast and the B.C.H.P. hospital-bed proposal was never established. However, I suspect that a r b i t r a r y decisions were made when the forecast Gross Demands of an i n d i v i d u a l d i s t r i c t were compared to the number of hospital beds currently i n operation i n that d i s t r i c t . The B.C.H.P. proposal, then, i s not s t r i c t l y a forecast, whereas the computer forecasting program's rebuttal to i t i s a forecast, based on specified assumptions. Nevertheless, the two "forecasts" were compared here to reveal the differences created by the use of di f f e r e n t approaches to translate Gross to Net Demand for h o s p i t a l services i n each d i s t r i c t . Table XXVIII transforms the balance (difference) data i n Tables XVI to XIX into percentages of the computer program's Standard Forecast of Hospital-Bed Requirements. Before analysing t h i s data, a complicating factor must be explained. Since patients can only transfer t o d i s t r i c t s that have h o s p i t a l s , the d i s t r i c t s of Coquitlam, Ladner and North Delta, with no hospitals of t h e i r own, export 100% of t h e i r patients and are shown on the G.V.R.H.D. forecast with no forecast Net Demand, and thus, no requirement f o r h o s p i t a l beds. Obviously, t h i s i s not s t r i c t l y true. There was considerable debate i n 1976 as to whether Coquitlam and Ladner had s u f f i c i e n t Gross Demand and access to inflow patient-days from 82. TABLE XXVIII VARIATION BETWEEN B.C.H.P. AND G.V.R.H.D. HOSPITAL BED FORECASTS EXPRESSED AS % G.V.R.H.D. FORECAST AREA PAEDIATRIC MATERNITY ADULT TOTAL SURREY 2.3 22.0 17.6 12.4 LADNER - - co oo RICHMOND 85.7 20.0 30.1 33.1 VANCOUVER 21.3 14.3 3.4 5.3 NEW WEST. 7.8 13.0 1.2 0.8 BURNABY 27.6 3.8 43.4 38.0 COQUITLAM - _ oo co NORTH SHORE 7.7 5.9 0.2 2.6 TOTAL 7.4 4.8 3.1 1.8 83. neighbouring d i s t r i c t s , to j u s t i f y the establishment of t h e i r own hospitals. B.C.H.P. said "yes" and proposed a new hospital i n each of the two d i s t r i c t s ; the G.V.R.H.D. said "no" and did not so propose. For t h i s reason, an i n f i n i t e percentage difference exists between the B.C.H.P. and the Standard forecasts of the Hospital-Bed Requirements of Coquitlam and Ladner. Table XXVIII shows that there i s considerable v a r i a t i o n between the two forecasts. Although the o v e r a l l B.C.H.P. t o t a l d i f f e r s by only 1.8% from the G.V.R.H.D. forecast, i n d i v i d u a l age-sex group forecasts f o r in d i v i d u a l d i s t r i c t s have some substantial variations. For example, the 85.7% v a r i a t i o n i n Richmond's paediatric forecast r e f l e c t s an absolute v a r i a t i o n of 12 beds. While t h i s i s not a large v a r i a t i o n , i t could considerably a f f e c t the planning of a paediatric unit within an i n d i v i d u a l hospital. The 43.4% v a r i a t i o n i n Burnaby's adult bed forecast i s a lower percent than that of the previous example, but the absolute v a r i a t i o n i s 109 beds - a large and c r i t i c a l v a riation. In summary, t h i s analysis reveals that, although the B.C.H.P. and G.V.R.H.D. forecasting p o l i c i e s and methods are not s t r i c t l y comparable, the two forecasts do not vary s i g n i f i c a n t l y o v e r a l l , as i s to be expected considering t h e i r common data. However, the allo c a t i o n s of the o v e r a l l Net Demand to age-sex groups by d i s t r i c t do vary s i g n i f i c a n t l y . This i s also expected considering the two diff e r e n t a l l o c a t i o n methods: B.C.H.P.'s i n t u i t i o n and the computer forecasting program's 1975 Transfer Matrix. THE SENSITIVITY ANALYSIS A. SENSITIVITY TO POPULATION CHANGES Without an opportunity to study the data, an outside observer might propose that f o r the d i s t r i c t s with high proportions of e l d e r l y people i n 84. t h e i r t o t a l adult populations, the s e n s i t i v i t i e s of t h e i r Net Demands for hospital services to changes i n the g e r i a t r i c population would be high. Since the g e r i a t r i c incidence rate i s approximately four times that of other adults, t h i s proposal i s reasonable. Table XX i n Chapter VII shows that t h i s i s not necessarily the case. As described i n Chapter VI, the g e r i a t r i c populations of the G.V.R.H.D. d i s t r i c t s were increased by approximately 64% above the standard g e r i a t r i c / t o t a l adult r a t i o s . The r e s u l t i n g percentages of g e r i a t r i c population i n 1981 vary from 5.18% i n Richmond to 11.80% i n New Westminster. The i n t r a -Regional patient transfer redistributed the increase i n patient days with the r e s u l t that some areas, notably Burnaby, received "more than t h e i r share" when t h e i r percent increase i n net demand i s compared with t h e i r percent increase i n g e r i a t r i c population. For example, the general 64% increase i n absolute numbers of elde r l y people raised Burnaby's percentage of g e r i a t r i c population to t o t a l adult population from 6.33% t o 10.40% - an increase of 4.07%. However, Table XX shows that the same general increase raised the forecast of the total-adult-Net Demand f o r h o s p i t a l services by 19.67%. Thus, f o r every 1% increase i n the g e r i a t r i c population, the net demand was increased by 4.84%; a s e n s i t i v i t y of 4.84. By comparison, New Westminster's s e n s i t i v i t y to a 1% increase i n the g e r i a t r i c population was 1.65 even though t h e i r g e r i a t r i c population i s 11.80% of t h e i r t o t a l adult population while that of Burnaby i s only 6.33%. This can be explained by the f a c t that Burnaby has the highest g e r i a t r i c inflow proportion of t o t a l adult Inflow of the G.V.R.H.D.'s d i s t r i c t s as shown i n Table XXIX. This table shows that Burnaby i s forecast to import 36,787 adult patient-days or 45% of the 82,346 adult patient-days that i t i s forecast to accommodate, and of those imported patient-days, 33% are g e r i a t r i c . 85. TABLE XXIX PROPORTION OF GERIATRIC INFLOW TRANSFERS TO TOTAL ADULT INFLOW TRANSFERS* AREA ADULT NET DEMAND ADULT INFLOW GERIATRIC INFLOW GERIATRIC PROPORTION SURREY 128,364 26,612 3,406 .138 RICHMOND 43,573 9,062 2,109 .233 VANCOUVER 888,610 322,524 46,768 .145 NEW WEST. 185,981 143,457 31,641 .221 BURNABY 82,346 36,787 12,199 .332 NORTH SHORE 134,302 19,581 2,611 .133 '•Calculated from the Standard Forecast using the Transfer Matrix. 86. Thus, Burnaby's adult Net Demand i s highly susceptible to changes i n the g e r i a t r i c population of the G.V.R.H.D. Without the patient transfers among the d i s t r i c t s , the c a l c u l a t i o n of the Net Demand would be a l i n e a r process and thus, the s e n s i t i v i t y of the output to changes i n the input would be equal f o r a l l d i s t r i c t s . B. SENSITIVITY TO INCIDENCE RATE CHANGES 1. S 2. In t h i s analysis of s e n s i t i v i t y , the g e r i a t r i c Incidence Rates were lowered by 10% and then were raised by 10% while the adult Rates were held constant at standard values. The summary of the s e n s i t i v i t y by d i s t r i c t to the 10% decrease i n the g e r i a t r i c Incidence Rates, Table XXI i n Chapter V I I , again shows that the s e n s i t i v i t i e s of the d i s t r i c t s ' Net Demand vary among the d i s t r i c t s . Somewhat as before, Burnaby's Net Demand decreased by 4.97% following the 10% drop i n the g e r i a t r i c Incidence Rates, a s e n s i t i v i t y of 0.50, while that of New Westmin-st e r , with a much higher percentage of eld e r l y persons, decreased by only 3.71%, a s e n s i t i v i t y of 0.37. Burnaby's higher s e n s i t i v i t y can be explained by that d i s t r i c t ' s high percentage of g e r i a t r i c Inflow, as noted i n the previous section. Because the intra-Regional transfer patterns are constant f o r a l l the s e n s i t i v i t y analyses, the Net Demand of each d i s t r i c t i s equally sensitive to an i d e n t i c a l increase or decrease i n the standard Incidence Rates. 3. S 4. In t h i s analysis of s e n s i t i v i t y , the adult Incidence Rates were lowered by 10% and then were raised by 10% while the g e r i a t r i c Rates were held constant. The summary of the s e n s i t i v i t y by d i s t r i c t to the 10% decrease i n the adult Incidence Rates, Table XXII i n Chapter V I I , shows that, as expected, the s e n s i t i v i t i e s of the Net Demand by d i s t r i c t vary 87. among the d i s t r i c t s . In addition, these s e n s i t i v i t i e s have a r e l a t i o n s h i p to the s e n s i t i v i t i e s shown on Table XXI. Burnaby, f o r example, has the lowest s e n s i t i v i t y to a 10% decrease i n the adult Incidence Rates, whereas i t has the highest s e n s i t i v i t y to a 10% decrease i n the g e r i a t r i c Incidence Rates. This opposite order of d i s t r i c t s e n s i t i v i t i e s was expected because a d i s t r i c t with a high g e r i a t r i c inflow proportion has a correspondingly low adult inflow proportion. Thus, t h i s d i s t r i c t ' s Net Demand i s more sensitive to changes i n the g e r i a t r i c Incidence Rates than are the Net Demands of other d i s t r i c t s , and correspondingly t h i s d i s t r i c t ' s Net Demand i s less sensitive to changes i n the adult Incidence Rates than are the Net Demands of other d i s t r i c t s . 5. S 6. In t h i s analysis of s e n s i t i v i t y , both the g e r i a t r i c and the adult Incidence Rates were f i r s t decreased by 10% and then were increased by 10%. . With the values of the other forecast variables held at Standard values, the Net Demand by d i s t r i c t was expected to have a s e n s i t i v i t y of 1.0 to an equal percentage change i n both the g e r i a t r i c and the adult Incidence Rates. This i s because the v a r i a t i o n by d i s t r i c t i n the g e r i a t r i c -adult inflow proportions w i l l not a f f e c t the conversion of Gross to Net Demand. Table XXIII, Chapter VII, shows that the s e n s i t i v i t i e s are 1.0 which indicates that the computer forecasting program produces r e s u l t s consistent with those expected. In summary, these exaircLnations of the s e n s i t i v i t y of the computer forecasting program's output forecast to changes made to the values of the input variables have shown that the user of the program cannot assume a common output-response to changes i n Populations and Incidence Rates. 88. An exanuination of the patient transfer patterns w i l l reveal p e c u l i a r i t i e s of a p a r t i c u l a r d i s t r i c t ' s h o s p i t a l service patterns. I f the combined pattern of a l l the d i s t r i c t s i s judged to be undesirable by the policy-makers, then the effects of revised patterns (TRANSFER MATRICES) can be analysed through the use of the computer forecasting program. THE POLICY ANALYSIS A. POPULATION I f an equal percentage increase i s applied to a l l the population groups of the d i s t r i c t s , the computer forecasting program should produce a forecast of Hospital-Bed Requirements that w i l l be increased by the same percentage. This should occur because the equal percentage change i n a l l the values of the population variable w i l l be transmitted through the fore-cast process to the forecast of Hospital-Bed Requirements. Table XXIV i n Chapter VII shows that a 10.0% increase i n a l l population groups of a l l d i s t r i c t s produced an average increase of 9.9% i n the Forecast Hospital-Bed Requirements. This s l i g h t difference i s attributable to"rounding"in the conversion of Net Demand i n patient-days to equivalent hospital-beds. The computer forecasting program does not greatly a s s i s t i n t h i s analysis as the effects of a general population increase can be calculated manually with less complication. B. INCIDENCE RATES An equal percentage increase i n a l l Incidence Rates of H o s p i t a l i z -a t i o n should produce an equivalent increase i n the forecast of Hospital-Bed Requirements f o r the same reason stated i n the previous section. The analysis, described i n Chapter VII , of the effects of a 10% increase i n 89, the Incidence Rates revealed that these effects were i d e n t i c a l to the effects of the 10% population increase. As i n the population analysis, the computer forecasting program does not greatly a s s i s t i n the analysis of the effects of general Incidence Rate changes. However, the program can a s s i s t i n the analysis of d i f f e r -e n t i a l changes i n Population and Incidence Rates as discussed under the S e n s i t i v i t y Analysis. C. INFLOW Table XXV i n Chapter VII shows the eff e c t s of a 10% decrease i n the Inflow patient-days to the G.V.R.H.D. Since the Inflow Transfer Vector (Standard) di s t r i b u t e s 75% of the G.V.R.H.D.'s Inflow to Vancouver's specialized h o s p i t a l services, i t was expected that 75% of the reduction i n Inflow would occur i n Vancouver. In f a c t , Vancouver's Forecast Hospital-Bed Requirements were reduced by 56 beds or 75% of the t o t a l 74 bed reduction that resulted from the 10% decrease i n Inflow. Although the effects of changes i n Inflow are completely predict-able i n t h i s forecasting method, the computer forecasting program does produce an alternate forecast quickly and, "thus, can a s s i s t the p o l i c y -analyst. D. TRANSFER MATRIX I f the G.V.R.H.D. were to establ i s h a p o l i c y that 80% of a d i s t r i c t ' s Gross Demand should be serviced i n l o c a l community hospitals (see Chapter I I I f o r Ontario's p o l i c y ) , then a t h e o r e t i c a l Transfer Matrix could be used to forecast the effects of t h i s p o l i c y . The Transfer Matrix described i n Chapter VII was developed to r e f l e c t such a p o l i c y and was used to produce the po l i c y forecast l i s t e d i n Table XXVI i n Chapter VII. 90. This p o l i c y would dramatically s h i f t the d i s t r i b u t i o n of h o s p i t a l f a c i l i t i e s from Vancouver and New Westminster to the surrounding d i s t r i c t s . Once provided with t h i s information, the p o l i c y maker must then weigh the s o c i a l benefits of the p o l i c y against the costs. For example, New Westminster's revised Forecast Hospital-Bed Requirement i s 40% below the Standard Forecast and also 40% below B.C.H.P.'s proposal f o r t h i s d i s t r i c t . The s o c i a l benefits would have to be high to balance the high cost of the abandoned or underutilized c a p i t a l f a c i l i t i e s that would follow the implementation of t h i s p o l i c y . The computer forecasting program could be a valuable t o o l i n t h i s type of analysis because i t quickly completes the necessary calculations to produce forecasts that can be used to analyse the e f f e c t s of alternate patient d i s t r i b u t i o n s . E. OCCUPANCY PERCENTAGE As an a l t e r n a t i v e to the B.C.H.P. "desired" occupancy percentages, the Poisson method of accommodating demand fluctuations was applied to the Forecast Average Daily Census of each G.V.R.H.D. h o s p i t a l . The r e s u l t s , shown i n Table XXVII i n Chapter VII , indicate that such a p o l i c y would increase the Forecast Hospital-Bed Requirements by an average of 3.9%, or 200 h o s p i t a l beds. The Poisson method, described i n Chapter VI, accounts f o r 99.7% of the demand fl u c t u a t i o n . The cost of providing such a high l e v e l of service a v a i l a b l i t y must be weighed against the health costs to the patient of not having s u f f i c i e n t bed-capacity available a t some peak demand occasions. Also, such an analysis could i n i t i a t e the investigation of alternate services to accommodate peak demand. 91. In summary, Table XXX displays the forecasts of Hospital Bed Requirements that resulted from the alternate p o l i c i e s discussed i n Chapter VI. These p o l i c i e s were selected as examples of possible applications of the computer forecasting program. The program i s best suited to the analysis of p o l i c i e s which incorporate d i f f e r e n t i a l changes i n the values of input variables by age-sex group and by d i s t r i c t . The program can quickly provide the p o l i c y analyst with a forecast of the net e f f e c t of these p o l i c i e s . TABLE XXX COMPARISON AMONG THE B.C.H.P. PROPOSAL, THE STANDARD FORECAST, AND THE POLICY FORECASTS OF HOSPITAL-BED REQUIREMENTS DISTRICT B.C.H.P. PROPOSAL STANDARD FORECAST POLICY A POPULATION POLICY B INCIDENCE RATES POLICY C INFLOW POLICY D TRANSFER MATRIX POLICY E OCCUPANCY PERCENTAGE SURREY 416 475 522 522 471 571 504 LADNER 75 0 0 0 0 80 0 RICHMOND 229 172 188 188 172 217 188 VANCOUVER 2,936 3,099 3,407 3,407 3,043 2,798 3,203 NEW WEST. 668 663 729 729 656 400 689 BURNABY 422 306 336 336 306 435 320 COQUITLAM 75 0 0 0 0 230 0 NORTH SHORE 456 468 516 516 461 458 479 TOTAL 5,277 5,183 5,698 5,698 5,109 5,189 5,383 93. CHAPTER IX SUMMARY AND CONCLUSIONS This thesis has studied the history and present a v a i l a b i l i t y of techniques f o r forecasting the demand f o r acute-care-hospital beds. A computerized forecasting program was developed, based on the current hospital planning method used i n B r i t i s h Columbia, but with some improve-ments. 1. The current method of forecasting acute-care-bed demand i n B r i t i s h Columbia does not use many of the refinements that have been developed and published. These refinements include the following: a) The separation of incidence rate into both the admission rate per 1,000 persons and the length of h o s p i t a l s t a y ? f o r d i f f e r e n t diagnostic categories. b) The d i v i s i o n of d i s t r i c t s into homogeneous population groups where possible. c) The recognition of intra-Regional patient transfers. d) The recognition of the d i s t r i b u t i o n of inflow among d i s t r i c t hospitals within the region. e) The use of occupancy c r i t e r i a that take account of the size of the i n d i v i d u a l h o s p i t a l rather than applying a set occupancy rate to a l l hospitals. f ) The use of alternate forecasts to r e f l e c t most l i k e l y and l e a s t l i k e l y estimates of the p r i n c i p a l variables. 2. The current B r i t i s h Columbia technique has been r e f i n e d by including three of the above aspects: (b), ( c ) , and (d). The other improvements noted i n #1 were not incorporated i n t o the forecasting program, i n order to conform with my e x p l i c i t decision 94. to match the B.C.H.P. method as much as possible to focus discussion on the more important issue of a Transfer Matrix to accommodate intra-Regional patient transfers. 3. The computerization of the forecasting process was e f f e c t i v e i n that the B.C.H.P. re s u l t s were reproduced when a neutral Transfer Matrix was used. This v a l i d a t i o n confirmed that the Transfer Matrix component was successfully integrated into the c a l c u l a t i o n sequence without d i s t o r t i n g the forecast t o t a l Net Demand f o r h o s p i t a l services. 4. The standard forecast produced by the computer program was compared with the B.C.H.P. forecast revealing that B.C.H.P.'s best estimated h o s p i t a l bed a l l o c a t i o n varied considerably from forecast requirements based on current patient flow patterns. My use of 1975 patient transfer data i s subject to the c r i t i c i s m that i t provides an entrenchment of the status quo, but, since the Standard Forecast was produced to show what might happen i f present trends continue, and since the computer program was s p e c i f i c a l l y designed to use alternate data, I do not believe that such c r i t i c i s m i s v a l i d . 5. The s e n s i t i v i t y of the technique to changes i n the values of input variables was analysed by comparing the canges i n output (Net Demand f o r h o s p i t a l services) to the changes made to Population and Incidence Rates. This analysis revealed that the i n d i v i d u a l d i s t r i c t s have d i f f e r e n t s e n s i t i v i t i e s to input data changes and that the output of each d i s t r i c t does not vary i n proportion to the v a r i a t i o n made to the input data. This f a c t makes the computer forecasting program a valuable t o o l f o r the analysis of the possible effects caused by inaccurate population or incidence rate forecasts. 6. Once the computer forecasting program was tested and validated, 95. i t was available to serve i n the role f o r which i t was designed: as a policy-analysis t o o l . Since h o s p i t a l planning has been plagued by the questionable usefulness of input data, the process of forecasting the future demand f o r f a c i l i t i e s has been f r u s t r a t i n g f o r both researchers and p o l i c y analysts. The computer forecasting program cannot be used to improve the data fed i n t o i t , but i t can be used to explore the range of data options, from most l i k e l y to least l i k e l y , to give the p o l i c y analyst a range of the possible results to be expected i f an estimate, or p o l i c y decision, proves to be incorrect. Several alternate p o l i c y positions regarding the values of the program's variables were analysed, with the conclusion that the program i s w e l l suited f o r the analysis of d i f f e r e n t i a l changes made to the values of input variables by age-sex group and by d i s t r i c t . 7. In conclusion, the computer forecasting program should now be improved by incorporating the remainder of the items previously noted under #1. 96. FIGURE 1. FLOW DIAGRAM OF THE COMPUTER FORECASTING PROGRAM HOSPITAL ADMISSION RATES Annual by Age-Sex £ D i s t r i c t POPULATION By Age-Sex £ D i s t r i c t > 2. Multiply A INCIDENCE RATES OF HOSPITALIZATION Annual by Age-Sex £ D i s t r i c t GROSS DEMAND i n Patient-Days Annual by Age-Sex £ D i s t r i c t I _ 1 _ \ Multiply • / Multiply fc- -AVERAGE LENGTH _0F STAY In Days per Admission INFLOW As % of Total Gross Demand for Age-Sex TRANSFER MATRIX OCCUPANCY PERCENTAGE By Age-Sex INFLOW In Patient ^Days by ' Age-Sex £ Year Multiply DISTRIBUTED GROSS DEMAND !  ^  In Patient-Days '  Annual by Age-Sex £ D i s t r i c t ±-Multiply TRANSFER VECTOR Sum T~ DISTRIBUTED INFLOW By Age-Sex £ D i s t r i c t NET DEMAND In Patient-Days by Age-Sex £ D i s t r i c t . -a 4 Divide 365 Days AVERAGE DAILY CENSUS In Patient- _ Days by Age-Sex £ D i s t r i c t ^ Divide L>, B.C.H.P.' Proposal FORECAST HOSPITAL BED REQUIRE-MENTS-, By Age-Sex £ D i s t r i c t Compare BALANCE OF BEDS REQUIRED 97. GLOSSARY Average Daily Census : Average Length of Stay : Gross Total Demand f o r : Hospital!zation Hospital Admissions Rate : Incidence Rate of : Hosp i t a l i z a t i o n Inflow Net Total Demand f o r : Ho s p i t a l i zation Occupancy Percentage : Outflow : Patient Day : Relevance Index : The average d a i l y number of beds that are expected to be used i n a h o s p i t a l or group of hospitals. The average length of time i n days that patients reside i n a h o s p i t a l per admission. The t o t a l number of patient days consumed by a population group or serviced by a geographical area exclusive of inflow and outflow. The number of persons from a population group who are admitted to a h o s p i t a l expressed as the number of admissions per 1000 persons per year. The number of patient-days consumed by a population group, usually 1000 persons, per year. The number of patient-days provided by hospitals i n a d i s t r i c t f o r patients whose residence i s not i n that d i s t r i c t . The t o t a l number of patient days serviced by a geographic area i n c l u s i v e of inflow and outflow. The percentage of a hospital's t o t a l beds that are being used by patients at a point i n time. The number of patient-days provided f o r the residents of a d i s t r i c t by hospitals not i n that d i s t r i c t . The use of one h o s p i t a l bed by one patient f o r one day. The proportion of a population group's t o t a l number of patient days that are serviced at a s p e c i f i c h o s p i t a l or i n a s p e c i f i c geographic area. A district-of-patient-residence by dis1n?ict-of-patient-treatment matrix composed of Relevance Indices. 99. BIBLIOGRAPHY Literature Cited Abel-Smith, Brian. Hospitals (May, 1962) Anderson, D.O. "Paediatric Bed Requirements" An unpublished paper produced f o r the B r i t i s h Columbia Medical Centre, A p r i l 1974. Anderson, O.W. Health Care: Can There Be Equity? New York: John Wiley and Sons, 1972. Bailey, Norman T.J. and Mark Thompson, eds. Systems Aspects of Health Planning. Oxford: North Holland Publishing Company Amsterdam, 1975. Bergwall, D.F., P.N. Reeves and N.B. Woodside. Introduction to Health  Planning. Washington: Information Resources Press, 1974. Blumberg, M.S. "'DPF Concept' Helps Predict Bed Needs." Modern Hospital 97 (6) December 1961. Brown, R.E. i n Medicare and the Hospitals, H.M. and A.R. Somers. Washington: The Brookings I n s t i t u t e , 1967. Commission on Hospital Care. Hospital Care i n the United States. New York: Commonwealth Fund, 1947. Economic Council of Canada. Seventh Annual Review Patterns of Growth. Ottawa: Queen's Pr i n t e r f o r Canada, 1970. Ensminger, Barry. The Eight B i l l i o n Dollar Hospital Bed Overrun. Washington! Public Citizens' Health Research Group, 1975. Godber, S i r George. "Health Planning i n Great B r i t a i n . " i n Regional  Hospital Planning, Malcolm Tottie and Bengt Janzen, eds. Stockholm: National Board of Health, 1967, Gottlieb, S.R. "A B r i e f History of Health Planning i n the United States." i n Regulating Health F a c i l i t i e s Construction, CC. Havighurst, ed. Washington: American Enterprise I n s t i t u t e f o r Public Po l i c y Research, 1974. G r i f f i t h , John R. Quantitative Techniques f o r Hospital Planning and Control. Lexington, Mass.: Lexington Books, 1972. Grigg, Naomi I. and Glori a E. Whelen. A Study of the Bed Requirements f o r  Acute Care i n Lower Fraser Valley Hospital Region. V i c t o r i a : B.C. Dept. of Health and Welfare, 1954. Hamilton, James A. and Assoc. A Hospital Plan and a Professional Educational  Programme f o r the Province of B r i t i s h Columbia, Canada. Minneapolis, 1949. H i l l , D.R. "Planning Model Found Faulty." Hospitals (December 16, 1971) 100. Hoge, V.M. "Hospital Bed Needs." Canadian Journal of Public Health 49 (1) 1-8. (January, 1958T! Hudenburg, Roy. Planning the Community Hospital. New York: McGraw-Hill, 1967. Johnstone, D.K. "The Concept and D e f i n i t i o n of An Individual Hospital Geographic Service Area." Major Report Submitted to Faculty of Department of Health Care Administration of the School of Govern-ment and Business Administration. George Washington University, 1971. Martin, Joseph R. Comprehensive Health Planning: Analytic Concepts. Blue Cross Association, 1975. May, J. J o e l . Health Planning: I t s Past and P o t e n t i a l . Chicago: University of Chicago, 1967. " W i l l Third Generation Planning Succeed?" Hospital Progress March 1976, p. 60. Melum, Mara M. Assessing the Need for Hospital Beds. Minneapolis: InterStudy, 1975. National Health Service. The Hospital Building Program. London: Her Majesty's Stationery O f f i c e , 1966. Newhouse, J.P. "A l l o c a t i o n of Public Sector Resources i n Medical Care: An Economist Looks at Health Planning." Economic and Business  B u l l e t i n 23 (2) 8-12. Paine, D.W. and L.L. Wilson. "The Determination of Acute Care Bed Requirements for P r o v i n c i a l Acute Care Hospital Regions." A paper presented to a conference of the International I n s t i t u t e f o r Applied Systems Analysis held at Baden, Aus t r i a , August 22-30, 1974. Roemer, M.I., MD and M. Shain. Hospital U t i l i z a t i o n Under Insurance. American Hospital Association: Monograph No. 6, 1959. Royal Commission on Health Services, Volume I . Ottawa, Queen's P r i n t e r , 1964. Somers, Anne R. Hospital Regulation: The Dilemma of Public P o l i c y . Princeton: Princeton University, 1969. The Task Force Reports on the Cost of Health Services i n Canada, Volume I. Ottawa, Queen's P r i n t e r , 1970. Thompson, Robert. Bed Needs i n the Scarborough Area. Toronto: Metropolitan Toronto Hospital Planning Council, 1971. Tot t i e , Malcolm and Bengt Janzon, eds. Regional Hospital Planning. Stockholm: National Board of Health, 1967. 101. United States Public Health Service. Areawide Planning f o r Hospitals and  Related Health F a c i l i t i e s . Washington, 1961. . The Nation's Health F a c i l i t i e s . (Publication No. 616) Washington, 1958. 102. APPENDIX A COMPUTER FORECASTING PROGRAM 10 ! 20 ! 30 ! 40 ! 50 ! 60 70 ! 80 90 1 100 110 120 130 140 150 160 170 180 190 200 T I ( 210 220 230 240 250 260 270 280 290 300 310 320 330 340 350 360 370 380 390 400 410 420 430 440 450 460 470 480 490 500 510 520 530 540 550 560 570 580 590 600 610 620 630 ******************************************************************** *** A PROGRAM TO FORECAST ACUTE CARE HOSPITAL BEDS IN THE GVRHD *** *************************************** K I L L 'BEDS' KI L L 'SUM' C1% = 0 OPEN 'BEDS' AS FILE 1% OPEN 'SUM' FOR OUTPUT AS FILE 9% MAT READ A$,B$,Al$ ! CLEAR PREVIOUS RUN'S PRINT OUTPUT FILE ! CLEAR PREVIOUS RUN'S SUMMARY FILE . ! INITIALIZE THE RUN COUNTER. ! OPEN OUTPUT FILE (DISK) FOR PRINTING. L SUM INDIVIDUAL RUNS ON DISK F I L E . ! READ AREA TITLES. i i i 9) i *** DIMENSION THE VIRTUAL ARRAYS ON DISK *** DIM # 9 , U 0 ( 9 ) , U 3 % ( 9 ) , U 4 % ( 9 ) , U 5 % ( 9 ) , V 0 ( 9 ) , V 1 ( 9 ) , V 1 % ( 9 ) , V 2 % ( 9 ) , V 3 % ( 9 ) , ,T2(9) ,T5%(9) ,T7(9) ,T9(9) ,X(9,9) ,Y(9 ,9) IF K%=5 GO TO 600 * * * INITIALIZE THE VIRTUAL ARRAYS *** MAT T1=ZER ! SUM OF POPULATION BY AREA. MAT T2=ZER i SUM OF PATIENT DAYS BY AREA. MAT T5%=ZER ! SUM OF INCIDENCE RATE BY AREA. MAT T7=ZER ! SUM OF NET PATIENT DAYS BY AREA. MAT T9=ZER ! SUM OF INFLOW PATIENT DAYS BY AREA. MAT U0=ZER I SUM OF INFLOW RATE AS A % BY AREA. MAT U3%=ZER I SUM OF BED NEED BY AREA. MAT U4%=ZER ! SUM OF BEDS.NEEDED BY AREA. MAT U5%=ZER i SUM OF BED BALANCE BY AREA. MAT V0=ZER . SUM OF OUTFLOW DAYS BY AREA. MAT V1=ZER . SUM OF OUTFLOW AS A % BY AREA. MAT V1%=ZER . SUM OF PLANNED BEDS BY REGROUPED AREA. MAT V2%=ZER . SUM OF NEEDED BEDS BY REGROUPED AREA. MAT V3%=ZER . SUM OF BED BALANCE BY REGROUPED AREA. MAT X=ZER . SUM OF PATIENT DAYS IN AREA TO AREA MATRI MAT Y=ZER SUM OF PATIENT DAY % DISTRIBUTION MATRIX. IF K%=5 GO TO 600 PRINT ! MESSAGE FOR USER ON TERMINAL, PRINT 'ANOTHER FORECAST SEQUENCE HAS STARTED. 1 PRINT ' ': PRINT ' ' * * * INSTRUCTIONS FROM TERMINAL * * * INPUT 'IF THIS IS A MATERNITY FORECAST, TYPE IN THE WORD YES',M$ IF M$='YES' GO TO 600 : PRINT ' ' INPUT 'IF THIS IS AN ADULT FORECAST, TYPE IN THE WORD YES',A$ PRINT ' 1 INPUT 'WHAT IS THE TITLE OF THIS FORECAST INPUT 'DATE PREPARED ' ,C$ 1 ,L$ \J -> v/ m r u i * v n x * ~ u r u r u u f i n u i i r w i M j ^ n o j . u o & L J ' 660 INPUT 1 WHICH TRANSFER MATRIX USED 1 ,F$ 670 INPUT 'WHICH PLANNED BED TOTALS USED ',G$ 680 INPUT 1 ANY COMMENTS TO ADD ',H$ 690 INPUT 1 ANY MORE COMMENTS TO ADD ' f K $ 700 INPUT 'LAST CHANCE FOR COMMENTS ',J$ •710! 715 IF K%=5 GO TO 5360 720 PRINT ' 1 730 ! 740 , INPUT 1 NAME OF INCIDENCE RATE DATA FILE TO BE USED ';R$ 750 INPUT 1 NAME OF POPULATION DATA FILE TO BE USED ';P$ 760 INPUT 1 NAME OF PLANNED BEDS DATA FILE TO BE USED ';B1$ 770 INPUT 1 NAME OF OUTFLOW RATE DATA FILE TO BE USED * ;0$ 780 INPUT 1 NAME OF TRANSFER MATRIX DATA FILE TO BE USED ' ;T$ 790 INPUT 1 NAME OF INFLOW DISTRIBUTION FILE TO BE USED ' ;I$ 800 INPUT 'INFLOW RATE AS A % GVRHD RESIDENT VOLUME ' ,L 810 PRINT ' ' 820 PRINT 'STANDARD OCCUPANCY RATES: PAEDS = .85 MAT = .80 ADULT = .90' 830 PRINT ' ' 840 INPUT 'WHICH OCCUPANCY RATE TO BE USED ',01 850 PRINT ' ' 860 ! 870 OPEN R$ FOR INPUT AS FILE 2% ! DESIGNATE DISK DATA FILE FOR INPUT. 880 OPEN P$ FOR INPUT A3 FILE 3% 890 OPEN B l $ FOR INPUT AS FILE 4% 900 OPEN 0$ FOR INPUT AS FILE 5% 910 OPEN T$ FOR INPUT AS FILE 6% 920 OPEN 1$ FOR INPUT AS FILE 8% 930 ! 9401 950! *** DIMENSION THE ARRAYS *** 960! 970 ! 980 DIM #2%, R(9) ! INCIDENCE RATES PER 1000 POPULATION. 990 DIM #3%, P ( 9 ) ! POPULATION IN THOUSANDS. 1000 DIM #4%, B(9) ! PLANNED BEDS BY AREA. 1010 DIM #5%, C(9) ! OUTFLOW BY AREA AS % AREA TOTAL VOLUME. 1020 DIM #6%, T(9,9) ! INTERNAL GVRHD TRANSFERS AS % AREA VOLUME. 1030 DIM #8%, F(9) ! INFLOW DISTRIBUTION AS % TOTAL INFLOW. 1040 ! 1050 DIM D(9) ! PATIENT DAYS. 1060 DIM D l ( 9 ) ! NET PATIENT DAYS. 1070 DIM G l % ( 4 ) ! REGROUPING OF PLANNED BEDS. 1080 DIM G2%(4) ! REGROUPING OF NEEDED BEDS. 1090 DIM B%(9) ! NET BED REQUIREMENT. 1100 DIM X%(9) ! NEEDED BEDS BY AREA. 1110 DIM B$(4) ! NAMES OF AREA GROUPS. 1120 DIM A l $ ( 9 ) ! ABBREVIATION OF AREA NAMES. 1130 DIM A$(9) ! NAMES OF AREAS. 1140 DIM P9(9) ! CORRECTION FOR MATERNITY POPULATION COUNT. 1150 DIM X9(9) ! SUM OF MATRIX PERCENTAGES BY AREA. 1160 DIM X8(9) ! SUM OF ACCUMULATED MATRIX PERCENTAGES BY AREA. 1170 ! 1190 ! 1200 ! 1210! 1220! *** CALCULATION OF PATIENT DAYS *** 1230! 1240 ! 1250 RESTORE ! RECYCLE DATA FOR THE NEXT READ STATEMENT. 1260 ! 1270 FOR 1=1 TO 9 1280 D ( I ) = R ( I ) * P ( I ) ! PATIENT DAYS=INCIDENCE RATE X POPULATION. 1290 31=S1+D(I) ! TOTAL OF PATIENT DAYS. 1310 ! 1320 1330 1340 1350 1360 1370 1380 ! 1390 1400 ! 1410 1420 ! 1430 1440 1450 1460 1470 ! 1480 1490 ! 1500 1510 1520 1530 1540 ! 1550 1560 1570 ! 1580 ! 1590 ! 1600 ! 1610 ! 1620 1630 1640 1650 1660 1 1670 1680 1690 i 1700 1710 ! 1720 1730 1740 1750 1760 1770 ! 1780 1790 ! 1800 1810 ! 1820 1830 1840 ! 1850 ! 1860 ! 1870 ! 1880 ! 1890 1900 1910 ! 1920 1930 1940 1950 ! T I ( I ) = T 1 ( I ) + P ( I ) T2 (I)=T2(I)+D(I) T3 =T3+D(I) T4 =T4+P(I) T 5 % ( I ) = T 2 ( I ) / T 1 ( I ) NEXT I R%=R%+S1/P2 IF M$ <> 1 YES 1 GO TO 1480 FOR J = l TO 9 P9 ( J ) = P ( J ) P9=P9+P(J) NEXT J IF P 9 O 0 AND A$='YES' GO TO 1510 GO TO 1560 FOR 1=1 TO 9 T l ( I ) = T 1 ( I ) - P 9 ( I ) NEXT I T4=T4-P9 T6%=T3/T4 * * * INTERNAL GVRHD TRANSFERS * * * FOR 1=1 TO 9 : FOR J = l TO 9 DI(J)=D1 ( J ) + T ( I , J ) * D ( I ) X ( I , J ) = X ( I , J ) + ( T ( I , J ) * D ( I ) ) Y ( I , J ) = X ( I , J ) / T 2 ( I ) X 9 ( I ) = X 9 ( I ) + T ( I , J ) X 8 ( I ) = X 8 ( I ) + Y ( I , J ) NEXT J V 0 ( I ) = V 0 ( I ) + ( C ( I ) * D ( I ) ) VI (I) =V0 (I) /T2 (I) X7=X7+(C(I)*D(I)) X 9 ( I ) = X 9 ( I ) + C ( I ) X 8 ( I ) = X 8 ( I ) + V 1 ( I ) NEXT I X6=X6+X7 DI(3)=D1(3)+D1(2) DI (2)=0 . *** CALCULATION FOR INFLOW *** T2=S1*L T=T+T2 FOR 1=1 TO 9 D1(I)=D1(I)+T2*F(I) D2=D2+D1(I) SUM FOR TOTAL POPULATION BY AREA. SUM FOR TOTAL PATIENT DAYS BY AREA. SUM FOR TOTAL PATIENT DAYS GVRHD. SUM FOR TOTAL GVRHD POPULATION. CUMULATIVE INCIDENCE RATE BY AREA. ! AVERAGE INCIDENCE RATE FOR THIS AGE GROUP, ! AVOID DOUBLE MATERNITY COUNT IN SUMMARY. ! SUBTRACT MATERNITY DOUBLE COUNT. ! SUMMARY INCIDENCE RATE ! AN AREA'S PATIENT DAYS = TRANSFERS TO IT. ! CUMULATIVE PATIENT DAYS IN TRANSFER MATRIX, ! CUMULATIVE TRANSFER MATRIX IN PERCENTAGES. ! SUM OF MATRIX PERCENTAGES. f SUM OF ACCUMULATED MATRIX PERCENTAGES. ACCUMULATED OUTFLOW DAYS BY AREA. ACCUMULATED OUTFLOW AS A % BY AREA. SUM OF OUTFLOW PATIENT DAYS. SUM OF MATRIX PERCENTAGES + OUTFLOW. SUM OF ACCUMULATED MATRIX PERCENTAGES + OUTFLOW, i ACCUMULATED TOTAL OUTFLOW PATIENT DAYS, ! DELTA ADJUSTMENT WHEN NEUTRAL MATRIX USED, ! NORTH DELTA CAN'T RECEIVE PATIENTS. ! INFLOW PATIENT DAYS FROM THIS AGE GROUP, I CUMULATIVE SUM OF INFLOW PATIENT DAYS. 1 ADD INFLOW FROM OUTSIDE THE GVRHD. ! SUM OF TOTAL PATIENT DAYS. ± V I u 1980 1990 2000 ! 2010 2020 ! 2030 2040 2050 2060 ! 2070 ! 2080 ! 2090 ! 3000 ! 3020 ! 3030 3040 3050 3060 3070 3080 3090 ! 3450 ! 4000 4010 4020 4030 4040 4050 4060 ! 4070 4075 ! 4080 4090 ! 5000 ! 5010 ! 5020 ! 5030 5040 5050 5060 5070 ! 5080 5090 5100 5110 5120 ! 5130 5140 5150 5160 ! 5170 5180 5190 5200 5210 5220 5230 5240 5250 ! 5260 5270 ! 5280 5290 5300 I O - I O t U l \ 1 J T9 (I)=T9 (I) + (T2*F(I) ) U 0 ( I ) = T 9 ( I ) / T NEXT I B%=T2/ (365*01) U1=U1+B% U2=T/T3 *** BED NEED CALCULATIONS *** FOR J = l TO 9 X%(J)=D1(J)/(365*01)+0 , B % ( J ) = B ( J ) - X % ( J ) A%=A%+B(J) C%=C%+X%(J) D%=D%+B%(J) U3% (J)=U3 % ( J ) + X % ( J ) U4%(J)=U4%(J)+B(J) U5% (J) =U5% (J) +B% (J) U6%=U6%+B(J) U7%=U7%+X%(J) U3%=U3%+8%(J) NEXT J GO TO 5360 *** REGROUP THE GEOGRAPHIC AREAS autn ur i u x a b f f l i x c N i uftia U N i n n U V M U , CUMULATIVE INFLOW BY AREA. PERCENT TOTAL INFLOW TO EACH AREA. *** =3(9) = B(5)+B(7) =B(3)+B(4) = B(1)+B(2)+B(6)+B(8) = X%(9) =X% (5)+X% (7) = X% (3) +X% (4) = X% (1) +X% (2) +X% (6) +X% (8) G l % (1) G l % (2) G l % (3) G l % (4) G2% (1) G2% (2) G2%(3) G2% (4) A% = 0. C% = 0 . D% = 0 . FOR J = l TO 4 B% (J)=G1%(J)-G2%(J) A%=A%+G1%(J) C%=C%+G2%(J) D%=D%+B%(J) V l % (J) =V1% (J) +G1% (J) V2%(J)=V2%(J)+G2%(J) V3%(J)=V3 % ( J ) + B % ( J ) NEXT J V4%=V4%+A% V5%=V5%+C% V6%=V6%+D% INFLOW AS BEDS. TOTAL INFLOW AS BEDS. OVERALL INFLOW RATE AS GVRHD DAYS. BED NEED = DAYS/OCCUPANCY RATE. BALANCE = PLANNED BEDS - NEEDED BEDS SUM OF PLANNED BEDS. SUM OF NEEDED BEDS. ! NET BED BALANCE, ! ACCUMULATION OF BED NEED BY AREA. ! ACCUMULATION OF PLANNED BEDS BY AREA. ! ACCUMULATION OF BED BALANCES BY AREA. ! ACCUMULATION OF TOTAL BEDS. ! ACCUMULATION OF NEEDED BEDS. ! ACCUMULATION OF BED BALANCE. ! NORTH = NORTH SHORE. ! CENTRAL - VANCOUVER + BURNABY ! SOUTH = LADNER + RICHMOND. ! EAST = SURREY + WHITE ROCK + ! REGROUP NEEDED BEDS. N DELTA + NEW WEST + COQUITLAM, ! RESET TOTALS TO ZERO. ! BED BALANCE. ! TOTAL PLANNED BEDS. ! TOTAL NEEDED BEDS. ! NET BED BALANCE. ! ACCUMULATE PLANNED BEDS, ! ACCUMULATE NEEDED BEDS. ! ACCUMULATE BED BALANCE. ! ACCUMULATE TOTAL PLANNED BEDS, ! ACCUMULATE TOTAL NEEDED 3EDS. ! ACCUMULATE TOTAL BED BALANCE. - ) -> J . J V j ' v J l 'U / ± u u 5320 ! 5330 ! *** PRINT SEQUENCE *** 5340 ! 5350 ! 5360 FOR 1 = 1 TO 14 5370 PRINT #1, 5380 NEXT I 5390 ! 5400 PRINT #1, ' * * * * * * * * * * * * * * * * * * * * * * * * i 5410 PRINT #1, 5420 PRINT #1, ' FORECAST OF GVRHD' 5430 PRINT #1, ' ACUTE CARE HOSPITAL BEDS' 5440 PRINT #1, 5450 PRINT #1, ' • , c $ 5460 PRINT #1, ' * * * * * * * * * * * * * * * * * * * * * * * * i 5470 PRINT #1, 5480 PRINT #1, ' DATA USED:' 5490 PRINT #1, 5500 PRINT #1, ' INCIDENCE RATE :',D$ 5510 PRINT #1, 5520 PRINT #1, ' POPULATION :',E$ 5530 PRINT #1, 5540 PRINT #1, ' TRANSFER MATRIX:',F$ 5550 PRINT #1, 5560 PRINT #1,' PLANNED BEDS :',G$ 5570 PRINT #1, 5580 PRINT #1, ' ************************** 5590 PRINT #1, 5600 PRINT #1, 5610 PRINT # 1 / REMARKS :' 5620 PRINT #1, 5630 PRINT #1, ' i ,H$ 5640 PRINT #1, 5650 PRINT #1, ' i ,K$ 5660 PRINT #1, 5670 PRINT #1, ' i ,J$ 5680 ! 5690 FOR 1 = 1 TO 13 5700 PRINT #1, 5710 NEXT I 5720 ! 5730 PRINT #1, ' DATE PREPARED :',L$ 5740 PRINT #1, ' *************' 5750 ! 5760 PRINT #1, CHR$(12%) ! SKIP TO A NEW 5770! 5790 ! 5800 PRINT #1, 5810 PRINT | ]_, 1 *************************************** 5820 PRINT #1,' * * * ASSUMPTIONS USED IN THE FORECAST OF AC 5830 PRINT #1, 1 ******************************************* 5840 PRINT #1, : PRINT #1,: PRINT #1, 5850 PRINT #1,' AREA , * INCIDENCE* , ' POPULATION' , 1 OWN DAYS' , ' 5860 PRINT #1,' * ** * i * * * * * * * * * i 1 * * * * * * * * * * 1 1 * * * * * * * * 1 i 5865 ! 5866 IF K%=5 GO TO 7960 5870 PRINT #1, 5880 FOR 1 = 1 TO 9 5890 PRINT #1 ,USING *\ V ,A$ (I) ; 5900 PRINT #1 ,USING #### ',R(I) ; 5910 PRINT #1 ,USING ' ####### ' ,P(I)*1000 . ; 5920 PRINT #1,USING '######£ ' ,D(I) ; 5930 PRINT #1,USING '######* ' ,D1 (I) 5940 PRINT #1, 5970 PRINT #1, : PRINT #1, 5980 PRINT #l,'TOTALS 5990 PRINT #1 ,USING ' #### ' ,R%; 6000 PRINT #1,USING ' ###&### ',P2*1000.; 6010 PRINT #1,USING '######* ' ,S1; 6020 PRINT #1,USING '####### ' ,D2 6030 PRINT #1,: PRINT #1,: PRINT #1, 6040 ! 6050 PRINT #1, 1 *********************** 1 6060 PRINT #1,'TRANSFER MATRIX ASSUMED' 6070 PRINT #1 '***********************' 6080 PRINT #1,' 6090 PRINT #1,'PATIENT AREA OF HOSPITAL TREATMENT1 6100 PRINT #1,"ORIGIN' 6110 PRINT #1, 1 ******* **************************' 6120 PRINT #1, 6130 PRINT #1,* ' ; 6140 FOR K=l TO 9 6150 PRINT #1,USING ' \\ ',A1$(K); 6160 NEXT K 6170 PRINT #1,' OUT TOTAL' 6180 PRINT #1, 6190 ! 6200 FOR 1=1 TO 9 6210 PRINT #1,USING '\ \ ' , A $ ( I ) ; 6220 FOR J = l TO 9 6230 PRINT #1,USING '.### ' , T ( I , J ) ; 6240 NEXT J 6250 PRINT #1,USING '.###', C ( I ) ; 6260 PRINT #1,USING ' #.###',X9(I) 6270 PRINT #1, 6280 NEXT I 6290 ! 6300 FOR K=l TO 8 6310 PRINT #1, 6320 NEXT K 6330 ! 6340 PRINT #1,'INFLOW ASSUMED 6350 PRINT #1, USING ' ##.#',L*100 . ; 6360 PRINT #1,' % OR AS BEDS: B% 63 70 PRINT #1,' **************' 6380 PRINT #1, 6390 PRINT #1,'OUTFLOW ASSUMED '; 6400 PRINT #1, USING ' ## .#' ,X7/S1*100.; 6410 PRINT #1,' % OR AS BEDS: 6420 PRINT #1, USING ' ### ' ,X7/(365.*01) 6430 I 6435 PRINT #1 •***************' 6440! 6450 FOR K=l TO 5 6460 PRINT #1, 6470 NEXT K 6480 ! 6490 PRINT #1DISTRIBUTION OF INFLOW 16500 PRINT #1,'BY AREA (PERCENTAGE) 1 6510 PRINT ft\r ***********************' 6520 PRINT #1, 6530! 6540 IF K%=5 GO TO 8550 6550 FOR 1=1 TO 9 6560 F1%=F1%+(F(I)*1000.) 6570 PRINT #1, USING '\ \ ' , A $ ( I ) ; 6580 PRINT #1, USING 1 ###.#',F(I)*100 6590 NEXT I O U i U 6620 6630 6640 ! 6650 6680 ! 6690 6700 6710 6720 6730 ! 6740 6750 ! 6760 67 70 6780 6790 ! 6800 6810! 6820 6825 6828 6830 6840 6850 6855! 68 56 6857 ! 6860 6870 6380 6890 6900 6910 6920 6930 ! 6940 6950 6960 6970 ! 6980 6990 ! 7000 7010 7020 7030 7040 7050 70 60 7070 ! 7080 7090 7095! 7100 7200 7210 7220 7230 ! 7240 7250 7260 7270 7280 7290 7300 f K 1 N X ff X , PRINT #1,'TOTAL '; PRINT #1, USING '###.#',F1%/10 FOR J = l TO 6 : PRINT #1, : NEXT J PRINT #1, 1 OCCUPANCY RATE ASSUMED 1PRINT #1, '**********************' PRINT #1, PRINT #1, 1 PAEDIATRICS - 85% : MATERNITY - 80% : ADULT - 90%' IF K%=5 GO TO 3660 PRINT #1, PRINT #1,'THE OCCUPANCY RATE FOR THIS FORECAST IS ' ; PRINT #1,01*100;'%' PRINT #1, CHR$(12%) PRINT #1 , 1 ***************************************** ' PRINT #1,'***** GVRHD BED NEED FORECAST BY AREA *****' PRINT #1 , 1 *********************************************' PRINT #1, PRINT #1,'AREA','PLANNED BEDS','NEEDED BEDS','BALANCE' PRINT #1, '****' f '*************' <***********• >*******< IF K%=5 GO TO 8860 PRINT #1, PRINT #1, A $ ( 1 ) , B ( 1 ) , X % ( 1 ) , B % ( 1 ) PRINT #1, FOR 1=3 TO 9 PRINT #1, A$ (I) ,B(I) ,X%(I) ,B%(I) PRINT #1, NEXT I ! PRINT SURREY'S NEEDS. ! PRINT OTHER AREAS' NEEDS PRINT t l , '************' •*****' •*******' <*******• PRINT #1, PRINT #1,'TOTALS',A%,C%,D% FOR J = l TO 6 : PRINT #1, : NEXT J PRINT #1, ' ********************************************************' PRINT #1,'***** GVRHD BED NEED FORECAST BY REGROUPED AREAS *****' PRINT #1 , ' ********************************************************' PRINT #1, PRINT #1,'AREA','PLANNED BEDS','NEEDED BEDS','BALANCE' PRINT #1, '****' , '*************' ^ '***********• f <*******> PRINT #1, IF K%=5 GO TO 8990 GO TO 5030 FOR K=l TO 4 PRINT #1, B$(K) ,G1%(K) ,G2%(K) ,B% (K) PRINT #1, NEXT K PRINT #1 , ' * * * * * * * * * * * * 1 / ' * * * * * ' r 1 * * * * * * * < i * * * * * * * 1 PRINT #1, PRINT #1, 1 TOTALS 1 ,A%,C%,D% PRINT #1, : PRINT #1, PRINT #1,'EXPLANATION OF AREAS' PRINT #1 '********************' PRINT #l) 7330 7340 7350 7360 7370 7380 7390 ! 7400 7410 ! 7420 ! 7430 ! 7440 7450 7460 7470 7480 7490 7500 7510 ! 7520 7530 7540 7550 7560 7570 7580 7590 7600 7610 7620 7630 ! 7640 7650 ! 7660! 7670 ! 7680 7690 7710 7720 7730 7740 7750 ! 7760 7770 ! 7780 7790 7800! 7810 7820 7830 7840 ! 7850 7860 ! 7870 7880 ! 7890 7900 7910 ! 7920 ! 7930 ! 7940 ! 7950 ! 7960 7970 PRINT ffi, PRINT #1,'2. CENTRAL = VANCOUVER AND BURNABY.1 PRINT #1, PRINT #1,'3. SOUTH = RICHMOND AND LADNER.' PRINT #1, PRINT #1,'4. EAST = COQUITLAM, NEW WESTMINSTER, NORTH DELTA,' PRINT #1,' SURREY AND WHITE ROCK.' IF K%=5 GO TO 9410 ***** RESET TOTALS FOR ANOTHER FORECAST RUN ***** MAT D Z ER MAT D l = ZER MAT G l % = ZER MAT G2 % = ZER MAT B% = ZER MAT X9 = ZER MAT X% = ZER A% = 0 C% = 0 D% = 0 R% = 0 S = 0 . SI = 0 . F l % = 0 T2 = 0 . P2 0 . D2 = 0 . X7 = 0 . C l % = Cl%+1 ***** INSTRUCTIONS TO THE USER ! INCREMENT THE COUNTER. ***** PRINT ' ' PRINT 1 RUN #';C1%;, IS COMPLETE.' IF K%=6 GO TO 9410 PRINT ' ' INPUT 'IF YOU WANT TO SUMMARIZE THESE FORECASTS, TYPE IN THE # 5 ',K% PRINT ' ' IF K%<>5 GO TO 7850 CLOSE 9% OPEN 'SUM' FOR INPUT AS FILE 9% ! CLOSE THE SUMMARY FILE FOR OUTPUT. ! OPEN THE SUMMARY FILE FOR INPUT. PRINT 'GIVE THE FOLLOWING INFORMATION FOR THE SUMMARY RUN:' PRINT ' ' GO TO 200 INPUT 'IF YOU WANT TO STOP NOW, TYPE IN THE # 6 ',K1% MAT X8 = ZER ! IF ANOTHER RUN HAS STARTED, RESET ACCUMULATED P%, IF Kl%=6 GO TO 9410 GO TO 49 0 ****************************************************** ***** PRINT SEQUENCE FOR THE SUMMARY FORECAST ***** ****************************************************** FOR K=l TO 9 PRINT #1, USING V ,A$ (K) ? IWK) f K 1 W T ffi, U O l l N S j • fffffffff-ffff • , T 1 ( K ) " 1 U U U . ; 8000 PRINT #1, USING '####### ',T2(K); 8010 PRINT #1, USING '####### ' ,T7(K) 8020 PRINT #1, 8030 NEXT K 8040! 8050 PRINT #1, : PRINT #1, : PRINT #1, 80 60 PRINT #1, 'TOTALS '; 8070 PRINT #1, USING ' #### ',T6%; 8080 PRINT #1, USING ' ####### ',T4*1Q00.; 8090 PRINT #1, USING '####### 1 ,T3; 8100 PRINT #1, USING '####### ' ,T8 8110 FOR K=l TO 3 : PRINT #1, : NEXT K 8120 PRINT #1, 'TRANSFER MATRIX ASSUMED1 8130 PRINT #1 '***********************' 8140 PRINT # l ' 8150 PRINT #1, 'PATIENT AREA OF HOSPITAL TREATMENT1 8160 PRINT #1, 'ORIGIN' 8170 PRINT #1 '******* * * * * * * * * * * * * * * * * * * * * * * * * * * i 8180 PRINT %l\ 8190 ! 8200 PRINT #1, ' 8210 FOR 1=1 TO 9 8220 PRINT #1, USING ' \\ * , A l $ ( I ) ; 82 30 NEXT I 8240 ! 82 50 PRINT #1, ' OUT TOTAL' 8260 PRINT #1, 8270 ! 8280 FOR 1=1 TO 9 8290 PRINT #1, USING '\ \ ' , A $ ( I ) ; 8300 FOR J = l TO 9 8310 PRINT #1, USING '.### ' , Y ( I , J ) ; 8320 NEXT J 8330 PRINT #1, USING '.###',VI(I); 8340 PRINT #1, USING * #.###',X8(I) 8350 PRINT #1, 8360 NEXT I 8370 ! 8380 FOR K=l TO 8 8390 PRINT #1, 8400 NEXT K 8410 ! 84 20 PRINT #1, 'INFLOW ASSUMED '; 8430 PRINT #1, USING '##.#',U2*100 . ; 8440 PRINT #1, ' % OR AS BEDS: ';U1 8450 PRINT #1, '**************' 8460 PRINT #1, 8470 PRINT #1, 'OUTFLOW ASSUMED '; 8480 PRINT #1, USING ' ## . # ' ,X6/T3*100.; 8490 PRINT #1, ' % OR AS BEDS: '; 8500 PRINT #1, USING ' ### 1 ,X6/(T3/U7%) 8 510 PRINT #1 "***************' 8520! 8530 GO TO 6450 8540! 8550 FOR K=l TO 9 8560 F2%=F2%+(U0 (K)*10000 . + .5) ! SUM INFLOW PERCENTAGES. 8570 PRINT #1, USING '\ \ ' , A $ ( K ) ; 8580 PRINT #1, USING '###.#' ,U0(K)*100. + .0005 8590 NEXT K 8600 ! 8610 PRINT #1, 8620 PRINT #1,'TOTAL '; 8630 PRINT #1, USING '###.#',F2%/l00 PRINT #1, PRINT #1, 'THE AVERAGE OCCUPANCY RATE FOR THIS FORECAST I S : PRINT #1, USING '##.#',(T8/(U7%*365.))*100.; PRINT #1, '%' FOR K=l TO 8 : PRINT #1, : NEXT K PRINT #1, 'PATIENT DAY FLOW STATISTICS' PRINT #1, '***************************' PRINT #1, PRINT #1, 'RESIDENT ACUTE PATIENT DAYS: PRINT #1, PRINT #1, PRINT #1, PRINT #1, PRINT #1, LESS OUTFLOW: PLUS INFLOW : PRINT #1, PRINT #1, 'NET GVRHD PATIENT DAYS : PRINT #1, PRINT #1, 'ACUTE CARE BED REQUIREMENTS: GO TO 6800 PRINT #1, A§(1) ,U4% (1) ,U3% (1) ,U5%(1) PRINT #1, FOR J=3 TO 9 PRINT #1, A$ (J) ,U4% (J) ,U3%(J) ,U5%(J) PRINT #1, NEXT J * * * * * * * i tfb^U I 8660 8670 8680 8690 8700 1 8710 8720 ! 8730 87 40 8750 8760 8765 8770 8775 8780 8790 8800 8810 8820 8830 i 8840 8850 ! 8860 8870 8880 ! 8890 8900 8910 8920 8930! 8940 8950 8960 8970 8980 ! 8990 9000 9010 9020 9030 9040 9050 9060 ,9070 ! 9080 ! 9090 ! 9100 DATA 'SURREY','NORTH DELTA','LADNER','RICHMOND','VANCOUVER', 1 NEW WEST', 'BURNABY' ,'COQUITLAM' ,'NORTH SHORE' 9 2 00 DATA 'NORTH','CENTRAL','SOUTH','EAST' 93 00 DATA ' S','ND',' L',' R',' V'^NW',' B',' C','NS' 9400 ! 9410 9420 9430 9440 ! 9450 9460 9470 9480 9490 9500 9510 9520 9530 ! PRINT #l,USING'######r,T3 PRINT #1,USING'#####«' ,X6 PRINT #1,USING'#######',T PRINT #1,USING'HJI#####' ,T3-X6+T PRINT #1,USING'#######',(T3-X6+T)/(T8/U7%)+.5 PRINT #1, '************' '***•*" !*****•*> PRINT #1, PRINT #1, 'TOTALS' ,U6%,U7%,U8% GO TO 6980 FOR K=l TO 4 PRINT #1,B$(K),V1%(K),V2%(K),V3%(K) PRINT #1, NEXT K PRINT #1, '************' >*****' <*******< •*******> PRINT #1, PRINT #1, 'TOTALS',V4%,V5%,V6% GO TO 9410 *** HEADINGS *** PRINT 'THIS FORECAST IS COMPLETE.' : PRINT ' ' PRINT 'TO PRINT THE RESULTS, RUN $QUE , QLP0:=BED3 PRINT #1, : PRINT #1, CLOSE 1% CLOSE 6% CLOSE 5% CLOSE 4% CLOSE 3% CLOSE 2% CLOSE 8% CLOSE 9% 103. APPENDIX B STANDARD FORECAST ******************* GVRHD FORECAST ACUTE HOSPITAL BEDS TITLE : PAEDIATRIC (0-14) 1981 ********************************************* DATA USED: INCIDENCE RATES: R001 POPULATION P001 TRANSFERS MO 21 PLANNED BEDS B001 ********************************************* REMARKS: THIS IS THE STANDARD FORECAST. DATE PREPARED: ** * * * * * * * * * * * 1 OCTOBER ************************************* *** ASSUMPTIONS USED IN FORECAST OF 1981 HOSPITAL BEDS *** ********************************************************** AREA * * * * SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE INCIDENCE ********* 425 350 350 340 375 475 375 330 286 POPULATION ********** 36100 12400 13400 24400 72000 6500 29400 32150 33550 OWN DAYS ******** 15343 4340 4690 8296 27000 3088 11025 10610 9595 TOTAL DAYS ********** 13385 0 0 4221 78788 15722 8877 0 8023 TOTALS 361 259900 93986 129016 *********************** TRANSFER MATRIX ASSUMED *********************** PATIENT ORIGIN ******* S ND SURREY .550 .000 NORTH DELTA .350 .000 LADNER .350 .000 RICHMOND .000 .000 VANCOUVER .000 .0 00 NEW WEST .000 .000 BURNABY .000 .000 COQUITLAM .000 .000 NORTH SHORE .000 .000 AREA OF HOSPITAL TREATMENT ************************** L .000 .000 .000 .000 .000 .000 .000 .000 .000 R ,000 ,100 ,100 ,400 000 000 000 000 000 V ,250 400 400 ,550 900 200 450 300 350 NW .150 .100 .100 .000 .000 .700 ,200 ,600 , 000 B ,050 , 050 ,050 ,050 ,100 ,050 ,350 050 000 C , 000 ,000 ,000 .000 000 000 ,000 ,000 000 NS .000 . 000 .000 .000 .000 . 000 .000 .000 .650 OUT TOTAL 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 050 1.000 000 1.000 050 1.000 000 1.0.00 INFLOW ASSUMED ************** 38.0 % OR AS BEDS: 115 OUTFLOW ASSUMED 0.7 % OR AS BEDS: 2 *************** DISTRIBUTION OF INFLOW BY AREA (PERCENTAGE) ********************** SURREY 5.0 NORTH DELTA 0.0 LADNER 0.0 RICHMOND 0.0 VANCOUVER 8 5.0 NEW WEST 5.0 BURNABY 0.0 COQUITLAM 0.0 NORTH SHORE 5.0 TOTAL 10 0.0 OCCUPANCY RATE ASSUMED ********************** PAEDIATRICS - 85% : MATERNITY - 80% : ADULT - 90% THE OCCUPANCY RATE FOR THIS FORECAST IS 85 % **************************************** ***** GVRHD BED NEED FORECAST FOR 1981 ***** ************************************************* AREA PLANNED BEDS NEEDED BEDS BALANCE **** ************* *********** ******* SURREY 44 43 1 LADNER 0 0 0 RICHMOND 26 14 12 VANCOUVER 200 254 -54 NEW WEST 55 51 4 BURNABY 3 7 29 8 COQUITLAM 0 0 0 NORTH SHORE 2 4 2 6 -2 ************ ***** ******* ******* TOTALS 386 417 -31 ************************************************* *** GVRHD BED NEED FORECAST FOR 1981 BY AREA '*** **************************************** *'* ******* AREA PLANNED BEDS NEEDED BEDS BALANCE **** ************* *********** ******* NORTH 24 2 6 -2 CENTRAL 237 283 -46 SOUTH 26 14 12 EAST 9 9 94 5 ************ ***** ******* ******* TOTALS 386 417 -31 EXPLANATION OF AREAS ******************** 1. NORTH INCLUDES THE NORTH SHORE 2. CENTRAL INCLUDES VANCOUVER AND BURNABY 3. SOUTH INCLUDES RICHMOND AND SOUTH DELTA 4. EAST INCLUDES COQUITLAM, NEW WESTMINSTER, NORTH DELTA, SURREY, AND WHITE ROCK ******************* GVRHD FORECAST ACUTE HOSPITAL BEDS TITLE : MATERNITY (15-45 FEMALE) ********************************************* DATA USED: INCIDENCE RATES: R002 POPULATION POO2 TRANSFERS M022 PLANNED BEDS B002 ********************************************* REMARKS: THIS IS THE STANDARD FORECAST. DATE PREPARED: ************* 1 OCTOBER 1981 ************************************ *** ASSUMPTIONS USED IN FORECAST OF 1981 HOSPITAL BEDS *** ********************************************************** AREA * * * * SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE INCIDENCE ********* 400 400 400 350 300 300 300 325 296 POPULATION ********** 33350 8450 9100 21250 88800 8050 32750 24400 32500 OWN DAYS ******** 13340 3380 3640 7438 26640 2415 9825 7930 9620 TOTAL DAYS ********** 11923 0 0 7 2 36 40740 .13378 7651 0 10039 TOTALS 325 258650 84228 90966 *********************** TRANSFER MATRIX ASSUMED *********************** PATIENT ORIGIN ******* S ND SURREY .650 .000 NORTH DELTA .350 .000 LADNER .350 .000 RICHMOND .000 .000 VANCOUVER .000 .000 NEW WEST .050 .000 BURNABY .000 .000 COQUITLAM .000 .000 NORTH SHORE .000 .000 AREA OF HOSPITAL TREATMENT ************************** L 000 .000 000 000 000 000 000 000 000 R .050 .300 .300 .600 .000 .000 .000 .000 .000 V 100 ,200 ,200 ,400 900 100 400 200 200 NW .150 .100 .100 .000 .000 .750 .200 .700 ,000 B 050 ,050 ,050 ,000 050 100 400 100 000 C ,000 ,000 ,000 000 000 000 000 000 000 NS . 000 .000 .000 .000 .050 .000 .000 .000 .800 OUT TOTAL 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 INFLOW ASSUMED 8.0 % OR AS BEDS: 23 ************** OUTFLOW ASSUMED 0.0 % OR AS BEDS: 0 *************** DISTRIBUTION OF INFLOW BY AREA (PERCENTAGE) ********************** SURREY 10 .0 NORTH DELTA 0 .0 LADNER 0 .0 RICHMOND 0 .0 VANCOUVER 50 0 NEW WEST 20 .0 BURNABY 5 0 COQUITLAM 0 0 NORTH SHORE 15 0 TOTAL 100. 0 OCCUPANCY RATE ASSUMED ********************** PAEDIATRICS - 85% : MATERNITY - 80% : ADULT - 90% THE OCCUPANCY RATE FOR THIS FORECAST IS 80 % **************************************** ***** GVRHD BED NEED FORECAST FOR 1981 ***** ************************************************* AREA * * * * SURREY LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE PLANNED BEDS NEEDED BEDS BALANCE ************* *********** ******* 50 0 30 120 40 25 0 32 ************ ***** TOTALS 297 41 0 25 140 46 26 0 34 ******* 312 9 0 5 -20 -6 -1 0 -2 ******* -15 ************************************************* *** GVRHD BED NEED FORECAST FOR 1981 BY AREA *** ************************************************* AREA PLANNED BEDS NEEDED BEDS BALANCE **** ************* *********** ******* NORTH 32 34 -2 CENTRAL 145 166 -21 SOUTH 30 2 5 5 EAST 90 87 3 ************ ***** ******* ******* TOTALS 297 312 -15 EXPLANATION OF AREAS ******************** 1. NORTH INCLUDES THE NORTH SHORE 2. CENTRAL INCLUDES VANCOUVER AND BURNABY 3. SOUTH INCLUDES RICHMOND AND SOUTH DELTA 4. EAST INCLUDES COQUITLAM, NEW WESTMINSTER, NORTH DELTA, SURREY, AND WHITE ROCK ******************* GVRHD FORECAST ACUTE HOSPITAL BEDS TITLE : ADULT (15-69) 1981 ********************************************* DATA USED: INCIDENCE RATES: R003 POPULATION POO3 TRANSFERS M023 PLANNED BEDS B003 ********************************************* REMARKS: THIS IS THE STANDARD FORECAST. DATE PREPARED: ************* 1 OCTOBER ********************************** *** ASSUMPTIONS USED IN FORECAST OF 1981 HOSPITAL BEDS *** ********************************************************** AREA * * * * SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE INCIDENCE ********* 1100 830 830 950 1350 1250 900 900 987 POPULATION ********** 100200 22700 24650 62200 293600 26900 103600 67450 104650 OWN DAYS ******** 110220 18841 20460 59090 396360 33625 93240 60705 103290 TOTAL DAYS ********** 87375 0 0 33509 652297 138734 52507 0 99652 TOTALS 1111 805950 895830 1064073 *********************** TRANSFER MATRIX ASSUMED *********************** PATIENT ORIGIN ******* S ND SURREY ,.600 .000 NORTH DELTA .350 .000 LADNER .300 .000 RICHMOND .000 .000 VANCOUVER .000 .000 NEW WEST .000 .000 BURNABY .000 .000 COQUITLAM .000 .000 NORTH SHORE .000 .000 AREA OF HOSPITAL TREATMENT ************************** L 000 ,000 000 000 000 000 000 000 000 R .000 .150 .200 .450 .000 .000 .000 .000 .000 V 200 350 350 550 950 150 450 200 200 NW .200 .100 .100 .000 .000 . 800 .250 .750 .000 B 000 000 000 000 050 050 300 050 000 C 000 000 000 000 000 000 000 000 000 NS .000 .000 .000 .000 .000 .000 .000 .000 .800 OUT TOTAL 000 1.000 050 1.000 050 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 INFLOW ASSUMED 19.0 % OR AS BEDS: 518 ************** OUTFLOW ASSUMED 0.2 % OR AS BEDS: 6 *************** DISTRIBUTION OF INFLOW BY AREA (PERCENTAGE) ********************** SURREY 5 .0 NORTH DELTA 0 .0 LADNER 0 .0 RICHMOND 0 0 VANCOUVER 75 0 NEW WEST 10 0 BURNABY 0 0 COQUITLAM 0 0 NORTH SHORE 10 0 TOTAL 100. 0 OCCUPANCY RATE ASSUMED ********************** PAEDIATRICS - 85% : MATERNITY - 80% : ADULT - 90% THE OCCUPANCY RATE FOR THIS FORECAST IS 90 % ******************************************** ***** GVRHD BED NEED FORECAST FOR 1981 ***** ************************************************* AREA * * * * PLANNED BEDS NEEDED BEDS ************* *********** SURREY 322 LADNER 75 RICHMOND 173 VANCOUVER 2616 NEW WEST 573 BURNABY 360 COQUITLAM 75 NORTH SHORE 40 0 ************ ***** TOTALS 4 59 4 266 0 102 1986 422 160 0 303 ******* 3239 BALANCE ******* 56 75 71 630 151 200 75 97 ******* 1355 ************************************************* *** GVRHD BED NEED FORECAST FOR 1981 BY AREA *** ************************************************* AREA ** ** NORTH CENTRAL SOUTH EAST PLANNED BEDS NEEDED BEDS BALANCE ************* *********** ******* 400 2976 248 970 ************ ***** TOTALS 4594 303 2146 102 688 ******* 3239 97 830 146 282 ******* 1355 EXPLANATION OF AREAS ******************** 1. NORTH INCLUDES THE NORTH SHORE 2. CENTRAL INCLUDES VANCOUVER AND BURNABY 3. SOUTH INCLUDES RICHMOND AND SOUTH DELTA 4. EAST INCLUDES COQUITLAM, NEW WESTMINSTER, NORTH DELTA, SURREY, AND WHITE ROCK ******************* GVRHD FORECAST ACUTE HOSPITAL BEDS TITLE : GERIATRIC (70+) 1981 ********************************************* DATA USED: INCIDENCE RATES: R004 POPULATION POO4 TRANSFERS M024 PLANNED BEDS B004 ********************************************* REMARKS: THIS IS THE STANDARD FORECAST. DATE PREPARED: ************* 1 OCTOBER ******************************************** *** ASSUMPTIONS USED IN FORECAST OF 1981 HOSPITAL BEDS *** ********************************************************** AREA * * * * SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE INCIDENCE ********* 5400 3500 3500 3900 5800 5100 5600 4000 5235 POPULATION ********** 8700 900 950 3400 34400 3600 7000 3400 6800 OWN DAYS ******** 46980 3150 3325 13260 199520 18360 39200 13600 35598 TOTAL DAYS ********** 40990 0 0 10065 236312 47247 29839 0 34649 TOTALS 5393 69150 372993 399103 *********************** TRANSFER MATRIX ASSUMED *********************** PATIENT ORIGIN ******* S ND SURREY .800 .000 NORTH DELTA .350 .000 LADNER .300 .000 RICHMOND .000 .000 VANCOUVER .000 .000 NEW WEST .00 0 .000 BURNABY .000 .000 COQUITLAM .000 .000 NORTH SHORE .000 .000 AREA OF HOSPITAL TREATMENT ************************** L ,000 ,000 ,000 ,000 ,000 000 000 000 000 R ,000 ,300 ,350 ,600 000 000 000 000 000 V .100 .300 .300 .350 ,950 ,100 , 300 ,100 ,10 0 NW .100 ,050 ,050 ,050 ,000 ,850 ,250 ,900 000 B . 000 .000 .000 .000 .050 .0 50 .450 .000 .000 ,000 ,000 000 ,000 000 000 000 000 000 NS .000 .000 .000 .000 .000 .000 .000 .000 .900 OUT TOTAL 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 000 1.000 INFLOW ASSUMED 7.0 % OR AS BEDS: 79 ************** OUTFLOW ASSUMED 0.0 % OR AS BEDS: 0 *************** DISTRIBUTION OF INFLOW BY AREA (PERCENTAGE) ********************** SURREY 5 .0 NORTH DELTA 0 .0 LADNER 0 .0 RICHMOND 0 .0 VANCOUVER 65 .0 NEW WEST 15 0 BURNABY 5 0 COQUITLAM 0 0 NORTH SHORE 10 0 TOTAL 100. 0 OCCUPANCY RATE ASSUMED ********************** PAEDIATRICS - 85% : MATERNITY - 80% : ADULT - 90% THE OCCUPANCY RATE FOR THIS FORECAST IS 90 % ******************************************** ***** GVRHD BED NEED FORECAST FOR 1981 ***** ************************************************* AREA PLANNED BEDS NEEDED BEDS BALANCE **** ************* *********** ******* SURREY 0 125 -125 LADNER 0 0 0 RICHMOND 0 31 -31 VANCOUVER 0 719 -719 NEW WEST 0 144 -144 BURNABY 0 91 -91 COQUITLAM 0 0 0 NORTH SHORE 0 10 5 -10 5 ************ ***** ******* ******* TOTALS 0 1215 -1215 ************************************************* *** GVRHD BED NEED FORECAST FOR 1981 BY AREA *** ************************************************* AREA PLANNED BEDS NEEDED BEDS BALANCE **** ************* *********** ******* NORTH 0 105 -105 CENTRAL 0 810 -810 SOUTH 0 31 -31 EAST 0 269 -269 ************ ***** ******* ******* TOTALS 0 1215 -1215 EXPLANATION OF AREAS ******************** 1. NORTH INCLUDES THE NORTH SHORE 2. CENTRAL INCLUDES VANCOUVER AND BURNABY 3. SOUTH INCLUDES RICHMOND AND SOUTH DELTA 4. EAST INCLUDES COQUITLAM, NEW WESTMINSTER, NORTH DELTA, SURREY, AND WHITE ROCK ******************* GVRHD FORECAST ACUTE HOSPITAL BEDS TITLE : SUMMARY OF ALL AGE-SEX GROUPS, ********************************************* DATA USED: INCIDENCE RATES: ROOX POPULATION POOX TRANSFERS M02X PLANNED BEDS BOOX ********************************************* REMARKS: THIS IS THE STANDARD FORECAST. DATE PREPARED: 1 OCTOBER ************* ******************************************** *** ASSUMPTIONS USED IN FORECAST OF 1981 HOSPITAL BEDS *** ********************************************************** AREA * * * * SURREY NORTH DELTA LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE INCIDENCE ********* 1281 825 823 978 1623 1553 1094 901 1090 POPULATION ********** 145000 36000 39000 90000 400000 37000 140000 103000 145000 OWN DAYS ******** 185883 29711 32115 88084 649520 57488 153290 92845 158103 TOTAL DAYS ********** 153671 0 0 55030 1008137 215081 98874 0 152363 TOTALS 1274 1135000 1447036 1683158 TRANSFER MATRIX ASSUMED *********************** PATIENT ORIGIN ******* 3 ND SURREY .650 .000 NORTH DELTA .350 .000 LADNER .313 .000 RICHMOND .000 .000 VANCOUVER .000 .000 NEW WEST .00 2 .0 00 BURNABY .000 .000 COQUITLAM .00 0 .000 NORTH SHORE .000 .000 AREA OF HOSPITAL TREATMENT ************************** L ,000 ,000 ,000 ,000 000 000 000 000 000 R ,004 ,176 ,212 ,481 000 000 000 000 000 V ,172 ,335 ,335 , 507 ,946 135 ,408 197 187 NW ,167 ,095 ,095 ,008 000 808 243 751 000 B ,008 ,013 ,013 ,005 052 052 348 047 000 C ,000 ,000 ,000 ,000 ,000 000 000 000 000 NS .00 0 .000 .000 .000 .002 .000 .000 .000 .813 OUT TOTAL 000 1.000 032 1.000 032 1.000 000 1.000 000 1.000 003 1.000 000 1.000 006 1.000 000 1.000 INFLOW ASSUMED 16.5 % OR AS BEDS: 735 ************** OUTFLOW ASSUMED 0.2 % OR AS BEDS: 8 *************** DISTRIBUTION OF INFLOW BY AREA (PERCENTAGE) ********************** SURREY 5 .1 NORTH DELTA 0 0 LADNER 0 .0 RICHMOND 0 0 VANCOUVER 74 .7 NEW WEST 10 1 BURNABY 0 7 COQUITLAM 0 0 NORTH SHORE 9 4 TOTAL 100. 0 OCCUPANCY RATE ASSUMED ********************** PAEDIATRICS - 85% : MATERNITY - 80% : ADULT THE AVERAGE OCCUPANCY RATE FOR THIS FORECAST IS PATIENT DAY FLOW STATISTICS *************************** RESIDENT ACUTE PATIENT DAYS: 1447036 LESS OUTFLOW: 2650 PLUS INFLOW : 238770 NET GVRHD PATIENT DAYS : 1683156 ACUTE CARE BED REQUIREMENTS: 5183 89 . ******************************************** ***** GVRHD BED NEED FORECAST FOR 1981 ***** ************************************************* AREA * * * * SURREY LADNER RICHMOND VANCOUVER NEW WEST BURNABY COQUITLAM NORTH SHORE PLANNED BEDS NEEDED BEDS ************* *********** 416 75 229 2936 668 422 75 456 ************ ***** TOTALS 5277 475 0 172 3099 663 306 0 468 ******* 5183 BALANCE ******* -59 75 57 -163 5 116 75 -12 ******* 94 ************************************************* *** GVRHD BED NEED FORECAST FOR 1981 BY AREA *** ************************************************* AREA * * * * NORTH CENTRAL SOUTH EAST PLANNED BEDS NEEDED BEDS BALANCE ************* *********** ******* 456 3358 304 1159 ************ ***** 468 3405 172 1138 ******* -12 -47 132 21 ******* TOTALS 5277 5183 94 

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