Health Care Management Science

, Volume 10, Issue 1, pp 13–24

Optimization of surgery sequencing and scheduling decisions under uncertainty

Authors

    • Mayo Clinic College of Medicine
  • James Viapiano
    • Fletcher Allen Health Care
  • Andrea Vogl
    • Fletcher Allen Health Care
Article

DOI: 10.1007/s10729-006-9005-4

Cite this article as:
Denton, B., Viapiano, J. & Vogl, A. Health Care Manage Sci (2007) 10: 13. doi:10.1007/s10729-006-9005-4

Abstract

Operating rooms (ORs) are simultaneously the largest cost center and greatest source of revenues for most hospitals. Due to significant uncertainty in surgery durations, scheduling of ORs can be very challenging. Longer than average surgery durations result in late starts not only for the next surgery in the schedule, but potentially for the rest of the surgeries in the day as well. Late starts also result in direct costs associated with overtime staffing when the last surgery of the day finishes later than the scheduled shift end time. In this article we describe a stochastic optimization model and some practical heuristics for computing OR schedules that hedge against the uncertainty in surgery durations. We focus on the simultaneous effects of sequencing surgeries and scheduling start times. We show that a simple sequencing rule based on surgery duration variance can be used to generate substantial reductions in total surgeon and OR team waiting, OR idling, and overtime costs. We illustrate this with results of a case study that uses real data to compare actual schedules at a particular hospital to those recommended by our model.

Keywords

SurgerySchedulingSequencingStochasticOptimizationLinear programmingSimulation

Copyright information

© Springer Science+Business Media, LLC 2006