An Improved Stochastic Model for Occupancy-Related Random Variables in General-Acute Hospitals

This paper presents an improved stochastic model for the behavior of the daily census and associated waiting variables in general-acute hospitals. The development and form of the distributions derived follow the general approach of a previous paper by Shonick [J. Amer. Statist. Assoc. 65, 1474–1500 (1970)], but greater flexibility is provided for the health-services planner by increasing the number of decision choices available for achieving given outcomes. This increased flexibility is attained via a generalization of the queuing discipline, permitting admissions of elective patients to be suspended when the number of occupied beds reaches a predetermined level (which may be less than the total bed complement). For any emergency-elective mix of the demand for hospitalization, this model permits the computation of many measures of operating efficiency, including expected overfill rate, percentage occupancy, waiting-list length, and loss of emergency patients. A variant of the model permits computation of the expected number of patient days that will be served in “nonapproved” facilities when emergencies arriving during “full” periods are accommodated therein, rather than turned away.