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.
Original language | English |
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Pages (from-to) | 60-70 |
Number of pages | 11 |
Journal | Procedia Manufacturing |
Volume | 10 |
DOIs | |
State | Published - 2017 |
Event | 45th SME North American Manufacturing Research Conference, NAMRC 2017 - Los Angeles, United States Duration: Jun 4 2017 → Jun 8 2017 |
Bibliographical note
Publisher Copyright:© 2017
Keywords
- operating room
- optimization
- scheduling
- simulation
- statistical process control
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Artificial Intelligence