Optimization Online


Proactive-Reactive Surgery Scheduling under Disruptions and the "To-Follow" Policy

Miao Bai(mib411***at***lehigh.edu)
R.H. Storer(rhs2***at***lehigh.edu)
G.L. Tonkay(glt0***at***lehigh.edu)
T.E. Theman(tet212***at***lehigh.edu)

Abstract: Surgery schedules are subject to disruptions due to duration uncertainty, patient punctuality, surgery cancellation, surgical emergencies and recovery resource availability. Such disruptions may result in inefficient utilization of medical resources, suboptimal patient care and patient and staff dissatisfaction. To alleviate these issues, we propose a proactive-reactive surgery scheduling method for a surgical suite with multiple operating rooms (ORs) and a shared post-anesthesia care unit (PACU). A surgical schedule considering possible disruptions is constructed prior to the day of surgery, and then adjusted dynamically in response to disruptions on the day of surgery. The proposed method is based on stochastic optimization and a sample-gradient descent algorithm. In addition, the "to-follow" scheduling policy, which is widely used in practice, is considered in this study. This differs from previous surgical scheduling studies which assume no surgery can start before its scheduled start time. Our objective is to minimize the expected penalty incurred from patient waiting time, surgeon idle time, OR blocking time, OR overtime and PACU overtime. The proposed method fi nds near-optimal solutions and outperforms the scheduling method commonly used in practice. Managerial insights are provided on the "to-follow" policy and on the arrival time of patients.

Keywords: Health care, surgery scheduling, stochastic optimization, reactive scheduling

Category 1: Applications -- OR and Management Sciences

Category 2: Stochastic Programming

Category 3: Applications -- OR and Management Sciences (Scheduling )


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Entry Submitted: 04/20/2017
Entry Accepted: 04/20/2017
Entry Last Modified: 04/20/2017

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