Surgery scheduling with recovery resources. (3rd October 2017)

• Record Type: Journal Article
• Authors: Bam, Maya; Denton, Brian T.; Van Oyen, Mark P.; Cowen, Mark E.
• Is Part Of: IISE transactions. Volume 49:Number 10(2017)
• Page Start: 942
• Page End: 955
• Publication Date: 2017-10-03
• Subjects: Surgery scheduling -- post-anesthesia care unit -- fast heuristics -- simulation; Industrial engineering -- Periodicals; Systems engineering -- Periodicals; Industrial engineering; Systems engineering; Electronic journals; Periodicals; 670.285
• DOI: 10.1080/24725854.2017.1325027
• Languages: English
• ISSNs: 2472-5854

Abstract

ABSTRACT: Surgical services are large revenue sources that account for a large portion of hospital expenses. Thus, efficient resource allocation is crucial in this system; however, this is a challenging problem, in part due to the interaction of the different stages of the surgery delivery system and the uncertainty of surgery and recovery durations. This article focuses on single-day in-patient elective surgery scheduling considering surgeons, operating rooms (ORs), and the post-anesthesia care unit (recovery). We propose a mixed-integer programming formulation of this problem and then present a fast two-phase heuristic: phase 1 is used for determining the number of ORs to open for the day and surgeon-to-OR assignments, and phase 2 is used for surgical case sequencing. Both phases have provable worst-case performance guarantees and excellent average case performance. We evaluate schedules under uncertainty using a discrete-event simulation model based on data provided by a mid-sized hospital. We show that the fast and easy-to-implement two-phase heuristic performs extremely well, in both deterministic and stochastic settings. The new methods developed reduce the computational barriers to implementation and demonstrate that hospitals can realize substantial benefits without resorting to sophisticated optimization software implementations.