Data-Driven Surgical Tray Optimization to Improve Operating Room Efficiency
Submitted to Operations Research manuscript OPRE-2021-06-370
Vinayak Deshpande, PhD
Nishanth Mundru, PhD
Sandeep Rath, PhD
Martyn Knowles, MD, MBA, FACS
Benjamin C. Wood, MD, MBA, FACS
ABSTRACT
Surgical procedures account for over 60% of the operating cost of a hospital. About 15% of these costs are those related to surgical instruments and supplies. Hospitals spend several million dollars a year on instrument sterilization, instrument tray assembly, and instrument repurchase costs. However, less than 20-30% of reusable instruments supplied to a surgery are used on average.
Prior implementations of surgical tray rationalizations have typically been expert-driven. This is a labor-intensive effort typically focused on a small set of trays. On the other hand, past mathematical programming model-based studies have typically tested models with simulated data because of the difficulty in obtaining actual instrument-level usage data.
We obtained actual surgical instrument usage at a large multi-specialty hospital in partnership with OpFlow, a healthcare software company. We formulate a data-driven mathematical optimization model for surgical tray configuration and assignment with the goal of reducing costs of unused instruments, such as sterilization, instrument purchase, and tray assembly costs. We develop a solution methodology that scales to thousands of surgeries, thousands of instruments, and hundreds of surgical trays.
We perform extensive out-of-sample testing of our solution. Our model-based approach identifies improvements in tray configuration and assignment, which would lead to a 54% reduction in unused instruments per surgery compared to current tray configuration used at this hospital. We also validated our model with an expert- recommended solution for a subset of trays.
We find that our model-based solution leads to 20% lower overage and 21% lower underage than the expert-recommended solution. We estimate projected annual cost savings of 35% in instrument sterilization, tray assembly costs and instrument repurchase costs from using the recommendations of our model. Our analysis has quantified the value of collecting point-of-usage data to be at least $1.39 million per year from using the model-recommended solution at the hospital.
Key words : data-driven optimization; healthcare operations; surgical tray rationalization