Scheduling surgery groups considering multiple downstream resources

A.J. Thomas Schneider*, J. Theresia van Essen, Mijke Carlier, Erwin W. Hans

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

37 Citations (Scopus)
141 Downloads (Pure)

Abstract

Surgery groups are clustered surgery procedure types that share comparable characteristics (e.g. expected duration). Scheduling OR blocks leaves many options for operational surgery scheduling and this increases the variation in usage of both the OR and downstream beds. Therefore, we schedule surgery groups to reduce the options for operational scheduling, ultimately bridging the gap between tactical and operational scheduling. We propose a single step mixed integer linear programming (MILP) approach that approximates the bed and OR usage and a simulated annealing approach. Both approaches are compared on a real-life data set and results show that the MILP performs best in terms of solution quality and computation time. Furthermore, the results show that our model may improve the OR utilization from 71% to 85% and decrease the bed usage variation from 53 beds to 11 beds compared to historical data. To show the potential and robustness of our model, we discuss several variants of the model requiring minor modifications. The use of surgery groups makes it easier to implementation our model in practice and, for operational planners, it is instantly clear where to schedule different types of surgery.

Original languageEnglish
Pages (from-to)741-752
Number of pages12
JournalEuropean journal of operational research
Volume282
Issue number2
Early online date24 Sept 2019
DOIs
Publication statusPublished - 16 Apr 2020

Keywords

  • Master surgery scheduling
  • OR in health services
  • Resource allocation
  • Surgery type clustering
  • Ward and ICU occupancy
  • UT-Hybrid-D
  • 22/2 OA procedure

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