Predicting operating room case load: An aid to resource allocation

Abstract

Hospital patient bed utilization can reach 100% with an impact on elective surgery schedules. Analysis of the demand for beds created by elective surgical operations is desirable to manage overall resources under these conditions. For planning and allocating operating rooms, staff, beds and equipment on any given day, hospital administrators would benefit from an accurate prediction of the number of surgical cases that will be completed. Current scheduling techniques do not predict, for a given day in the future, the number of cases that will actually be performed. A study was performed at a 247 bed hospital with 10 operating rooms. The operating rooms were available for reservation more than two weeks in advance. Both block scheduling and open time were available. Using reservation data with a simple Black Box model allows the prediction of the total number of cases to be performed up to two weeks in advance with 90% accuracy. The resultant predictive demand should allow for better resource planning for the Operating Suite as well as required post-op hospital patient beds.