INFORMS NEWS: Innovative Applications in Analytics Award

Innovative Applications in Analytics Award Committee members and officers of the Analytics Section of INFORMS congratulate the finalists, led by members of the winning Mayo Clinic team.

Innovative Applications in Analytics Award Committee members and officers of the Analytics Section of INFORMS congratulate the finalists, led by members of the winning Mayo Clinic team.

The winner of the 2015 Innovative Applications in Analytics Award is “Intelligent Surgical Scheduling” by Narges Hosseini, Kalyan Pasupathy, Thomas Rohleder, Jeanne Huddleston and Paul Huddleston of the Mayo Clinic and Yariv Marmor of ORT Braude College. The team is comprised of an ideal mix of operations researchers/systems engineers, a spine surgeon and a physician-engineer, as well as an IT team, working together to implement an analytics-driven scheduling system to impact spine surgery practice.

Presented by the Analytics Section of INFORMS at the INFORMS Conference on Business Anakytics and Operations Research, the award recognizes creative and unique application of analytical techniques. As stated on the award website, the prize “promotes the awareness and value of the creative combination of analytics techniques in unusual applications to provide insights and business value.” To win the award, implementations must integrate theoretical advances and innovative applications in order to create value.

The Mayo Clinic Department of Orthopedic Surgery was facing low utilization of their operating rooms for spine surgical procedures, combined with fluctuating empty days and days with overtime to complete scheduled surgeries. Extremely long days ended up being unsafe days with increased provider fatigue and higher likelihood of errors. Investigation revealed the cause to be inaccurate estimation of surgical and non-surgical duration and scheduling of surgeries rather than limited surgery demand.

Existing scheduling optimization research in the literature was inadequate, as it provided a single “optimal” solution. Often, the single optimal solution was not satisfactory to the patients and the providers. The team conducted descriptive research using historical data to identify clinical and operational factors; developed and implemented predictive models for the duration of surgical and nonsurgical times in the operation room based on these factors; and developed and implemented a prescriptive scheduling search algorithm that suggests multiple slots for a given surgery, thereby providing flexibility while ensuring high probability of completion of surgical day without much overtime.

The project will be presented by Drs. Narges Hosseini, Kal Pasupathy and Jeanne Huddleston at the 2015 INFORMS Annual Conference in Philadelphia in November.

Implementations that span applications of descriptive, predictive or prescriptive analytics, as well as data creation, collection and dissemination which support or enable novel analytical methods, can be submitted for the 2016 Innovative Applications in Analytics Award.

Applicants must submit a 500- to 1,000-word summary by Sept. 4, 2015.