Optimal trauma care network redesign with government subsidy: A bilevel integer programming approach

Shaonan Liu, Nan Kong, Pratik Parikh and Mingzheng Wang

Omega, 2023, vol. 119, issue C

Abstract: Trauma presents a prominent health problem worldwide. However, trauma centers are often clustered in urban areas and sparsely located in rural areas. The geographic maldistribution of trauma centers leads to system-related mistriage errors. While some local governments offer subsidy to incentivize the affiliated hospital group to redesign the trauma care network, the approach is ad hoc. To address this issue, we propose a bilevel integer programming model to investigate the subsidized trauma care network redesign problem, which considers the government as the leader and the hospital group as the follower. To solve the resultant problem efficiently, we propose a branching idea to exclude additional infeasible solutions and suboptimal solutions, in turn speeding up the branch-and-bound algorithm. In a case study, we redesign a trauma care network in the midwestern area of the U.S. based on closed-form approximate functions of system-related mistriage errors. The results show that the optimal network redesign redistributes the network by slightly reducing the number of trauma centers to relieve the crowded trauma care resource, and achieves an overall improvement of about 11% over the original network.

Keywords: Emergency care; Network design; Facility location optimization; Bilevel integer programming; Government subsidy (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.omega.2023.102885

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