Date on Master's Thesis/Doctoral Dissertation

8-2025

Document Type

Doctoral Dissertation

Degree Name

Ph. D.

Department

Industrial Engineering

Degree Program

Industrial Engineering, PhD

Committee Chair

Parikh, Pratik

Committee Member

Bai, Lihui

Committee Member

Saleem, Jason

Committee Member

Kong, Nan

Author's Keywords

Subsidy; trauma centers; network; policy; insurance

Abstract

Trauma, as the leading cause of mortality and morbidity for those under the age of 45 in the US, incurs trillions in annual economic costs. The time-sensitive nature of trauma treatment necessitates an effective, coordinated regional trauma system to optimize patient safety. However, the financial burden associated with trauma care, especially due to low-insured population, presents a significant challenge to the financial health of trauma centers (TCs). To address critical challenges in this domain and provide much-needed insights to trauma decision-makers regarding their trauma system cost, network design, and subsidy policy, this dissertation proposes 3 contributions. First, we introduce an economic theory-based model that enables estimating the cost of a given trauma network with patient volume. This model also allows trading off cost and care; i.e., it addresses questions such as ‘would opening additional TCs in the network improve care or significantly increase cost?’ Second, we propose a Subsidized Trauma Network Design Problem (STNDP) to determine the optimal number and location of TCs. We employ a lexicographic approach to model the problem where maximizing equity in patient care across regions in a trauma service area (TSA) is the primary objective and minimizing the total subsidy is the secondary objective. We develop a decomposition-based approach to efficiently solve the problem. Third, we introduce a generalized subsidy distribution formula that incorporates key elements from various state subsidy policies, such as trauma volume, number of severely injured patients, and uncompensated care. We then propose a TC Financial Evaluation Model (TC-FEM), which employs Monte Carlo simulation to assess the impact of different subsidy policies on the financial health of TCs within a given network using the generalized formula. Based on our proposed evaluation metrics and realistic data from multiple US states and national insurance statistics, our findings suggest that the financial performance of TCs could be affected by the total subsidy amount, the Uninsured level within the Trauma Service Area (TSA), and the specific subsidy distribution policy employed. This tool will enable trauma decision makers to evaluate, compare, and design subsidy policies tailored to their unique demographic and economic contexts, potentially leading to a more standardized approach to mitigate existing policy disparities across states. In summary, our research delivers critical insights into the financial and patient safety challenges faced by trauma systems and offers policy recommendations for their sustainability. It equips state trauma decision-makers with robust models to optimize resource allocation and improve the efficiency of trauma networks.

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