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Trauma injuries continue to be the leading cause of mortality and morbidity among US citizens aged 44 years and under. Government agencies are often in charge of designing an effective trauma network in their region to provide prompt and definitive care to their citizens. This process is, however, largely manual, experience-based and often leads to a suboptimal network in terms of patient safety. To support effective decision making, we propose a Nested Trauma Network Design Problem (NTNDP), which can be characterized as a nested multi-level, multi-customer, multi-transportation, multi-criteria, capacitated model with the bi-objective of maximizing the weighted sum of equity and effectiveness in patient safety. We use mistriages (system-related under- and over-triages) as surrogates for patient safety. To add realism, we include intermediate trauma centers that are set up in many states in the US to serve as feeder centers to major trauma centers to improve patient safety and three criteria to mimic EMS’s on-scene decisions. We propose a ‘3-phase’ solution approach that first solves a relaxed version of the model, then solves a Constraint Satisfaction Problem, and then a modified version of the original optimization problem (if needed), all using a commercial solver. Our findings suggest that solutions are sensitive to (i) the proportion of assignments attributed to various destination determination criteria, (ii) distribution of trauma patients, and (iii) relative emphasis on equity vs. effectiveness. We also illustrate the use of our approach using real data from a midwestern US state; results show over 30% performance improvement in the objective value.
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Optimal trauma care network redesign with government subsidy: A bilevel integer programming approach
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 oer 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.
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- Award ID(s):
- 1761022
- PAR ID:
- 10526690
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Omega
- Volume:
- 119
- Issue:
- C
- ISSN:
- 0305-0483
- Page Range / eLocation ID:
- 102885
- Subject(s) / Keyword(s):
- emergency care, network design, facility location optimization, bilevel integer programming, government subsidy
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.omega.2023.102885
