Scheduling of surgeries subject to stochastic surgery and length of stay with respect to limited capacities in hospitals

• Applicant: Dr. Svenja Schoonover
• Subject Area: Accounting and Finance ; Public Health, Healthcare Research, Social and Occupational Medicine
• Term: from 2016 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 328158686

Surgeries are measures to improve the quality of life. In some cases, the procedures are even life-saving. Surgeries require many resources, including surgeons, anesthesiologists, nurses, tools and devices, an operating room and a bed in a care unit directly following the surgery. If one resource is not available, the surgery must be postponed, reducing the health care service level. Therefore, a surgery scheduling approach should take limited resources and stochasticity into account. This leads to shorter waiting times for surgeries (by higher utilization of operating rooms) and to a better nurse-patient ratio in the care units (by more leveled utilization of the care units). Current research considers fixed, repeating surgery schedules, but not individual plans for varying demand of surgeries. Therefore, the objective of this research project is to develop a mathematical decision model for surgery scheduling subject to stochastic surgery and bed occupancy times, limited operating rooms and care units, and staff capacities. The goal of this model is to maximize the utilization of operating rooms, to level the utilization in the care units, and the economic, and therefore sustainable, use of the hospital resources. In the course of the project, the distribution of surgery times and the length of stay subject to the procedures is determined, and the correlation between the duration of the surgery and the length of stay in the wards is investigated. The mathematical decision model is developed using the insights from this data analysis (that is, the expected value and the standard deviation per procedure and, if applicable, the correlation between surgery time and length of stay). The result of the model is a surgery and bed occupancy plan for a given demand of procedures subject to the limited resources. Furthermore, we will analyze buffer times in the surgery schedule and its positive effects on robustness of the plan and its negative effects on the idle time. The model will utilize real hospital data. The provided data are surgery times and lengths of stay for the complete years 2014-2016 for three different disciplines at the Hanover Medical School in Germany. The variability of surgery times differs for the selected disciplines: eye surgery has very low variability, heart surgery has a medium variability, and accident surgery is highly variable. In addition, we have bypass surgery data from the Vanderbilt Medical Center for 2015-2017.This research project extends the assumptions of prevailing methods by the consideration of the stochasticity of durations and limited bed capacities with varying surgery demands. That way, it will contribute to the improvement of the health care service level.

• DFG Programme: Research Fellowships
• International Connection: USA
• Participating Institution: Gottfried Wilhelm Leibniz Universität Hannover ; Wirtschaftswissenschaftliche Fakultät ; Institut für Produktionswirtschaft
• Host: Professor Michael Pinedo, Ph.D.