Optimization and Simulation of Orthopedic Spine Surgery Cases at Mayo Clinic

Asli Ozen (), Yariv Marmor (), Thomas Rohleder (), Hari Balasubramanian (), Jeanne Huddleston () and Paul Huddleston ()
Additional contact information
Asli Ozen: University of Massachusetts Amherst, Amherst, Massachusetts 01003
Yariv Marmor: ORT Braude College, 2161002 Karmiel, Israel; and Mayo Clinic, Rochester, Minnesota 55905
Thomas Rohleder: 3185 Rosemary Lane NE, Rochester, Minnesota 55906
Hari Balasubramanian: University of Massachusetts Amherst, Amherst, Massachusetts 01003
Jeanne Huddleston: Mayo Clinic, Rochester, Minnesota 55905
Paul Huddleston: Mayo Clinic, Rochester, Minnesota 55905

Manufacturing & Service Operations Management, 2016, vol. 18, issue 1, 157-175

Abstract: Spine surgeries tend to be lengthy (mean time of 4 hours) and highly variable (with some surgeries lasting 18 hours or more). This variability along with patient preferences driving scheduling decisions resulted in both low operating room (OR) utilization and significant overtime for surgical teams at Mayo Clinic. In this paper we discuss the development of an improved scheduling approach for spine surgeries over a rolling planning horizon. First, data mining and statistical analysis was performed using a large data set to identify categories of surgeries that could be grouped together based on surgical time distributions and could be categorized at the time of case scheduling. These surgical categories are then used in a hierarchical optimization approach with the objective of maximizing a weighted combination of OR utilization and net profit. The optimization model is explored to consider trade-offs and relationships among utilization levels, financial performance, overtime allowance, and case mix. The new scheduling approach was implemented via a custom Web-based application that allowed the surgeons and schedulers to interactively identify best surgical days with patients. A pilot implementation resulted in a utilization increase of 19% and a reduction in overtime by 10%.

Keywords: operating room scheduling; surgery scheduling; mixed-integer program (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormsom:v:18:y:2016:i:1:p:157-175

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