A stochastic model for scheduling elective surgeries in a cyclic Master Surgical Schedule

• Published in: Computers & industrial engineering 2019-03, Vol.129, p.156-168
• Main Authors: M'Hallah, Rym, Visintin, Filippo
• Format: Article
• Language: English
• Subjects: Length of stay; Operating room; Post-surgery beds; Sample average approximation; Stochastic integer programming
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2019.01.030

•Addresses the Master Surgical Scheduling problem at the tactical level.•Proposes a stochastic model that is solved via a sample average approximation.•Considers the stochasticity of both surgery times and length of stays.•Assumes that each operating session is pre-assigned to a surgical specialty.•Finds the number and type of cases to schedule in a two-week planning horizon. In this study we propose a stochastic model that determines the number and type of surgeries to schedule in a two-week planning horizon where each operating session is assigned to a surgical specialty according to a fixed grid (Master Surgical Schedule). Our model considers surgery times, intensive care unit times and post-surgery lengths of stays stochastic and accounts for the availability of both intensive care unit beds and post-surgery beds. It aims to maximise the expected operating theatre’s throughput. The assignment problem, modelled as a stochastic problem, is solved via a sample average approximation. It gets an estimate of the optimum expected throughput for each specialty and of the operating theatre. We illustrate the application of the model on a real case study with real data from a leading European Children’s Hospital, study the sensitivity of obtained results to the two-week planned grid, and highlight the importance of considering the stochastic nature of the problem.