Abstract
Operating room (OR) scheduling is important. Because of increasing demand for surgical services, hospitals must provide high quality care more efficiently with limited resources. When constructing the OR schedule, it is necessary to consider the availability of downstream resources, such as intensive care unit (ICU) and post anaesthesia care unit (PACU). The unavailability of downstream resources causes blockings between every two consecutive stages. In this paper we address the master surgical schedule (MSS) problem in order to minimize blockings between two consecutive stages. First, we present a blocking minimization (BM) model for the MSS by using integer programming, based on deterministic data. The BM model determines the OR block schedule for the next day by considering the current stage occupancy (number of patients) in order to minimize the number of blockings between intraop and postop stages. Second, we test the effectiveness of our model under variations in case times and patient arrivals, by using simulation. The simulation results show that our BM model can significantly reduce the number of blockings by 94% improvement over the base model. Scheduling patient flow across the 3-stage periop process can be applied to work flow scheduling for the s-stage flow shop shop production in manufacutirng, and also Smoothing patient flow in periop process can be applied to no-wait flow shop production.
Document Type
Article
Publication Date
7-7-2017
Digital Object Identifier (DOI)
https://doi.org/10.1016/j.promfg.2017.07.022
Funding Information
This project was supported by grant number R03HS024633 from the Agency for Healthcare Research and Quality.
Repository Citation
Abedini, Amin; Li, Wei; and Ye, Honghan, "An Optimization Model for Operating Room Scheduling to Reduce Blocking Across the Perioperative Process" (2017). Mechanical Engineering Faculty Publications. 33.
https://uknowledge.uky.edu/me_facpub/33
Included in
Business Administration, Management, and Operations Commons, Manufacturing Commons, Operational Research Commons
Notes/Citation Information
Published in Procedia Manufacturing, v. 10, p. 60-70.
© 2017 The Author(s). Published by Elsevier B.V.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).