This paper develops a two-stage planning procedure for master planning of elective and emergency patients while allocating at best the available hospital resources. Four types of resources are considered: operating theatre, beds in the medium and in the intensive care units, and nursing hours in the intensive care unit. A tactical plan is obtained by minimizing the deviations of the resources consumption to the target levels of resources utilization, following a goal programming approach. The MIP formulation to get this tactical plan is specifically designed to account for emergency care since it allows for the reservation of some capacity for emergency patients and possible capacity excess. To deal with the deviation between actually arriving elective patients and the average number of patients on which the tactical plan is based, we consider the possibility of planning a higher number of patients than the average to create operating slots in the tactical plan (slack planning). These operating slots are then filled in the operational plan following several flexibility rules. We consider three options for slack planning that lead to three different tactical plans on which we apply three flexibility rules to get finally nine alternative weekly schedules of elective patients. We then develop an algorithm to modify this schedule on a daily basis so as to account for emergency patients' arrivals. Scheduled elective patients may be cancelled and emergency patients may be sent to other hospitals. Cancellation rules for both types of patients rely on the possibility to exceed the available capacities. Several performance indicators are defined to assess patient service and hospital efficiency. Simulation results show a trade-off between hospital efficiency and patient service.

, , , , ,,
ERIM Top-Core Articles
European Journal of Operational Research
Erasmus School of Economics

Adan, I., Bekkers, J., Dellaert, N., Jeunet, J., & Vissers, J. (2011). Improving operational effectiveness of tactical master plans for emergency and elective patients under stochastic demand and capacitated resources. European Journal of Operational Research, 213(1), 290–308. doi:10.1016/j.ejor.2011.02.025