Collaborative Operating Room Planning and Scheduling

Vahid Roshanaei (), Curtiss Luong (), Dionne M. Aleman () and David R. Urbach ()
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Vahid Roshanaei: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada
Curtiss Luong: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada
Dionne M. Aleman: Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario M5S 3E3, Canada; and Techna Institute at University Health Network, Toronto, Ontario M5G 1P5, Canada
David R. Urbach: Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario M5S 3E3, Canada; and Techna Institute at University Health Network, Toronto, Ontario M5G 1P5, Canada

INFORMS Journal on Computing, 2017, vol. 29, issue 3, 558-580

Abstract: Operating rooms (ORs) play a substantial role in hospital profitability, and their optimal utilization is conducive to containing the cost of surgical service delivery, shortening surgical patient wait times, and increasing patient admissions. We extend the OR planning and scheduling problem from a single independent hospital to a coalition of multiple hospitals in a strategic network, where a pool of patients, surgeons, and ORs are collaboratively planned. To solve the resulting mixed-integer dual resource constrained model, we develop a novel logic-based Benders’ decomposition approach that employs an allocation master problem, sequencing sub-problems for each hospital-day, and novel multistrategy Benders’ feasibility and optimality cuts. We investigate various patient-to-surgeon allocation flexibilities, as well as the impact of surgeon schedule tightness. Using real data obtained from the General Surgery Departments of the University Health Network (UHN) hospitals, consisting of Toronto General Hospital, Toronto Western Hospital, and Princess Margret Cancer Centre in Toronto, Ontario, Canada (who already engage in some collaborative resource sharing), we find that on average, collaborative OR scheduling with traditional patient-to-surgeon allocation flexibility results in 6% cost-savings, while flexible patient-to-surgeon allocation flexibility increases cost-savings to 40%, and surgeon schedule tightness can impact costs by 15%. The collective impact of our collaboration and patient flexibility results in between 45% and 63% savings per surgery. We also use a game theoretic approach to fairly redistribute the payoff acquired from a coalition of hospitals and to empirically show coalitional stability among hospitals.

Keywords: healthcare; operating room; open scheduling strategy; mixed-integer linear programming; logic-based Benders’ decomposition; coalition; patient-to-surgeon allocation flexibility; surgeon schedule tightness; game theory; convex games; Shapley value (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:29:y:2017:i:3:p:558-580

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