Surgical scheduling to smooth demand for resources

Abstract

With the growing demand for healthcare resources, pressure on efficient usage of available bed capacity is increasing. Peaks in bed demand corresponds to overcrowding in upstream units such as emergency department or operating rooms. With a balanced schedule in elective surgeries integrated into the master surgical schedule, peak traffic can be leveled across the week without changing resource capacity. Hence, overcrowding is reduced without turning away any patients or increasing bed capacity.

This study formulates the integration of master surgical and elective surgery scheduling problems as an Integer Programming model to minimize the fluctuation in the required ward beds for elective inpatients admitted for surgery to the hospital, by changing the day of surgery. This demonstrates the opportunities for smoothing the expected patient demand for beds by adjusting the operating room schedule. This decision is made at the tactical level. The model has been examined using data on the elective patient demand for beds in the hospital during typical weeks driven from Hamilton Health Sciences in Ontario, Canada. The integer programming model has been solved using GAMS/CoinCBC MIP Solver. The model enhances bed management by not only smoothing but also reducing the peak demand. The optimal schedule reduces the peak patient demand for bed by about 3–19% for the test samples. The model can be extended to cover the demand for other resources such as ICU beds.