An Inventory Optimization Model To Support Operating Room Schedules
(2011) Supply Chain Forum — Vol. 12, n° 1, p. 56-69 (2011)
Files
No attached file found for this publication.
Details
- Authors
- Abstract
- Health care costs continue to rise at unprecedented rates in the United States. While past research has addressed optimal patient scheduling to improve the utilization of operating theater resources (physicians, specialized equipment, and operating rooms), little research has attempted to optimize material requirements and safety stocks to support these optimized schedules. Although classical inventory models can and should be used, additional considerations in hospital environments remain unaddressed. Based on our empirical observations, significant opportunities exist to reduce waste by improving the planning and coordination of materials and information in hospital operating theaters. To quantify these opportunities, we develop an analytic optimization framework for planning and executing material quantity preparation and placement decisions to support hospital operating theaters. Our model considers the non-stationary stochastic demand associated with block scheduling of surgical departments and a stochastic bill of materials, common in surgical treatments. Our approach is novel in that we formulate the stochastic decision problem exactly as a linear program by leveraging the convexity of the expected cost functions. The model is computationally efficient and flexible, allowing fast solutions and unique considerations for individual hospitals while considering uncertainty explicitly. We conduct a numerical study and sensitivity analysis to pinpoint the leverage points in the system for reducing inventory carrying and materials management costs. Surprisingly, reducing the uncertainty in the physician-determined bill of materials through standardization exhibited the greatest potential for savings
- Affiliations
Citations
Riane, F., Rappold, J., Van Roo, B., & Di Martinelly, C. (2011). An Inventory Optimization Model To Support Operating Room Schedules. Supply Chain Forum, 12(1), 56-69. https://hdl.handle.net/2078.5/189841 (Original work published 2011)