Objectives: 1) To assess temporal patterns in historical patient arrival rates in an   emergency department (ED) to determine the appropriate number of shift   schedules in an acute care area and a fast-track clinic and 2) to determine   whether physician scheduling can be improved by aligning physician   productivity with patient arrivals using an optimization planning model.   

Methods: Historical data were statistically analyzed to determine whether the   number of patients arriving at the ED varied by weekday, weekend, or holiday   weekend. Poisson-based generalized additive models were used to develop   models of patient arrival rate throughout the day. A mathematical programming   model was used to produce an optimal ED shift schedule for the estimated   patient arrival rates. We compared the current physician schedule to three   other scheduling scenarios: 1) a revised schedule produced by the planning   model, 2) the revised schedule with an additional acute care physician, and   3) the revised schedule with an additional fast-track clinic physician.   

Results: Statistical modelling found that patient arrival rates were   different for acute care versus fast-track clinics; the patterns in arrivals   followed essentially the same daily pattern in the acute care area; and arrival   patterns differed on weekdays versus weekends in the fast-track clinic. The   planning model reduced the unmet patient demand (i.e., the average number of   patients arriving at the ED beyond the average physician productivity) by   19%, 39%, and 69% for the three scenarios examined. 

Conclusions: The planning   model improved the shift schedules by aligning physician productivity with   patient arrivals at the ED.

Authors: David W. Savage, Douglas G. Woolford, Bruce Weaver, David Wood