Hospital bed planning in Canada: a survey analysis.
The need to plan health and especially hospital care delivery systems is becoming more critical in this period of severe financial constraints and even cutbacks of services. This article reports on a survey of hospital planning norms and bed requirements methodologies in Canada conducted in 1977 and 1980. The comparison and assessment of approaches to bed need determination in the Canadian provinces, together with some recommendations, are preceded by a review of basic hospital planning methods and their use in a number of selected countries. The literature review and the analysis conducted reveal that the "formula method" (beds per 1000 population) is the most common approach used to define and to allocate the "optimum" number of beds in the countries reviewed and in Canada. Despite its shortcomings, this method appears to have many advantages (e.g., simplicity, equity, flexibility). In general, provincial authorities use similar factors in the calculation of the number of beds to be provided, the most important ones being the size of the projected geographic population or population served by age groups. The acute care bed guidelines in Canada range from 3.5 per 1000 population in southern Ontario to 5.0 in Saskatchewan and Alberta. Extended care bed guidelines are much more spread between provinces. The analysis underlines the difficulties faced by the planner and the researcher in comparing bed guidelines due to significant definition and content differences between provinces. It finally leads to the observation that hospital planning remains arbitrary and appears to be more designed to ration the supply of services and to contain overall expenditures than to really try to meet the "need" of the population for hospital services.
D001509:Bed Occupancy; D002170:Canada; D005060:Europe; D006287:Health Planning Guidelines; D006301:Health Services Needs and Demand; D006742:Hospital Bed Capacity; D006752:Hospital Planning; D008433:Mathematics; D010934:Planning Techniques; D012044:Regression Analysis; D013269:Stochastic Processes; D014481:United States