Sterilization network design

Abstract

With the increasing costs of health care, service providers are looking for innovative ways to cut cost without sacrificing high service quality. Resource pooling is a promising trend in different health care areas, and sterilization is no exception. Specialized medical sterilization centers (SCs) that offer reusable medical device (RMD) sterilization services for hospitals have the potential to cut cost and improve efficiency through better utilization of resources, risk-pooling and economies of scale. However, it is unclear whether the resulting cost savings can offset the additional transportation costs and the operational complications associated with a centralized system. We compare three schemes to organize RMD sterilization in a group of hospitals: fully distributed, centralized processing, and centralized processing and stock keeping. The sterilization network design problem is formulated as a mixed-integer concave minimization program (MISOCP) that considers economies of scale, service level requirements and variable demand, with the objective of minimizing capacity, transportation, and inventory holding costs. The mathematical model is reformulated as a mixed-integer second-order cone program with a piecewise-linear cost function so it can be solved efficiently. We also consider the case when the first two moments of the RMD demand distributions are not known with certainty but are rather estimated based on sample data. We show that, with proper selection of the uncertainty structure, the robust nonlinear optimization problem can be tractably reformulated as a MISOCP as well. Testing on a realistic case study under different scenarios reveals that significant cost savings can be achieved by consolidating sterilization services. Compared to the distributed scheme, we found that cost saving in the second scheme is attributed primarily to improved resource utilization and economies of scale. Risk-pooling in the last scheme results in an additional small cost saving that has to be weighed against other operational and legal considerations.