MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Articles in Advance, pp. 1–19 ISSN 1523-4614 (print)  ISSN 1526-5498 (online) http://dx.doi.org/10.1287/msom.2015.0564 © 2015 INFORMS Optimization and Simulation of Orthopedic Spine Surgery Practice at Mayo Clinic Asli Ozen University of Massachusetts Amherst, Amherst, Massachusetts 01003, aslozen@gmail.com Yariv Marmor ORT Braude College, 2161002 Karmiel, Israel; and Mayo Clinic, Rochester, Minnesota 55905, myariv@braude.ac.il Thomas Rohleder 3185 Rosemary Lane NE, Rochester, Minnesota 55906, trohleder@charter.net Hari Balasubramanian University of Massachusetts Amherst, Amherst, Massachusetts 01003, hbalasubraman@ecs.umass.edu Jeanne Huddleston, Paul Huddleston Mayo Clinic, Rochester, Minnesota 55905 {huddleston.jeanne@mayo.edu, huddleston.mayo@mayo.edu} S pine surgeries tend to be lengthy (mean time of 4 hours) and highly variable (with some surgeries last- ing 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 iden- tify 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 optimiza- tion 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 per- formance, 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 History : Received: February 28, 2014; accepted: August 24, 2015. Published online in Articles in Advance. 1. Introduction For spine surgeries, large medical centers like Mayo Clinic generally face more patient demand than avail- able capacity. One reason is the relatively long surgi- cal times for spine patients. Data from Mayo Clinic shows that 50% of spine surgeries are over four hours in length. Thus, on most days a spine surgeon is able to do only one or at most two surgeries (within regu- lar working hours). The length and variability of spine surgeries ad- versely impact patient access, effective operations, and financial performance (Dexter et al. 2010). At Mayo Clinic, 38% of surgical days went past the desired end time of 5 p.m. At the same time, operat- ing room (OR) utilization during normal hours was less than desired, limiting patient access and reducing potential financial performance. Overtime is a con- cern at Mayo Clinic due to the importance of qual- ity of life for the surgeons and the surgical teams. In addition, as noted in Espin et al. (2006), safety for both the patient and surgical staff may be an issue if surgical days run long. Emergency cases, short-term cancellations, teaching requirements for surgeons on specific weekdays, and complex cases that require more than one surgery per patient further complicate scheduling and OR management. In this paper, we describe a data-driven hierarchi- cal modeling approach for scheduling spine surgeries that tackles multiple aspects such as surgery vari- ability (by better classification), OR utilization, over- time, payer mix, and financial performance. We use a seven-year data set consisting of 2,500 spine surgeries to parameterize our models. We also quantify how this scheduling approach performed in a pilot imple- mentation. Many of the concepts and approaches dis- cussed in this research are relevant to other surgical practices and particularly those in spine surgery. Nonetheless, the orthopedic spine surgery practice at 1