Effective management of demand for patient services begins with making conscientious staffing and scheduling decisions.  This is a very complex problem which requires assessment of multiple, competing objectives such as maximizing throughput, balancing staff workload, and satisfying preferences.

We use mathematical programming techniques to help determine and assign schedules that accommodate variations in demand. We developed a mixed-integer programming model (MIP) to guide Patient and Guest Services in weekly staffing and zoning decisions, which are invaluable considering we transport patients and medical equipment throughout the health system around a quarter of a million times in any given year.