Collaborative Research: Optimizing Trauma Care Network Design

该奖项通过支持将改善创伤护理网络设计的研究来促进国民健康。创伤是年轻人死亡的主要原因。创伤护理网络包括创伤中心，配备人员和设备全天候治疗最严重的受伤病例，社区医院，配备稳定病人并将其运送到适当的创伤中心，以及空中/地面运输服务。创伤护理网络应确保严重受伤患者在适当的时间内得到适当的护理，但创伤护理设施的不合理分布可能导致严重受伤患者治疗不足，以及对较轻受伤患者的昂贵过度治疗。该项目将促进国家机构和医院网络之间的协调网络设计，这是创伤护理系统中的两个关键利益相关者。它将使创伤政策制定者能够在分诊错误和成本方面对区域和国家的创伤护理进行定量基准测试。研究小组将与州政府官员、医院和急救服务提供者合作，验证网络优化方法。该奖项将支持研究生的研究，并为本科生和研究生提供与医疗政策和管理相关的运筹学的体验式学习机会。研究成果将广泛分发给学术界和实践界。本项目提出了创新的优化方法来协调创伤中心选址的双层决策过程。该研究将创伤网络设计问题框架为一个双层双目标优化问题，以捕捉上层（地区当局）决策之间的层次互动，上层（地区当局）决策涉及补贴分配，以改善社会福利和最小化公共支出，下层（医院网络）决策涉及升级或降级，以最大化收入。交叉分解约束组合低层问题和自适应标量化逼近非线性非凸多目标双层规划的整个Pareto集的新技术将使问题的求解更加有效。鲁棒性将根据现场决策的空间变化、预计创伤需求和运输资源可用性的时间偏差进行评估。新的基于代理模型的算法将有助于解决由此产生的最大参数子空间识别问题。来自两个州的数据将用于验证该方法。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award advances the national health by supporting research that will improve trauma care network design. Trauma is a leading cause of death in younger populations. Trauma care networks include trauma centers, staffed and equipped round the clock to treat the most severely injured cases, community hospitals, equipped to stabilize and transport patients to appropriate trauma centers, and air/ground transport services. The trauma care network should ensure that severely injured patients receive the right care in the right amount of time, but maldistribution of trauma care facilities can result in undertreatment of severely injured patients as well as expensive overtreatment of less-severely injured patients. This project will facilitate coordinated network design between state agencies and hospital networks, two key stakeholders in the trauma care system. It will enable trauma policy makers to quantitatively benchmark trauma care regionally and nationally in terms of triage errors and costs. The research team will collaborate with state officials, hospitals, and emergency care providers to validate the network optimization methods. The award will support graduate student research and provide experiential learning opportunities for undergraduate and graduate students in operations research related to healthcare policy and management. Research findings will be widely distributed to both the academic and practitioner communities. Innovative optimization methods to coordinate the bilevel decision making process for trauma center location are developed in this project. The research frames the trauma network design problem as a bilevel biobjective optimization problem to capture the hierarchical interaction between the upper level (regional authority) decisions involving subsidy allocation to improve social wellbeing and minimize public spending, and lower level (hospital networks) decisions involving upgrade or downgrade to maximize revenue. Novel techniques for cross-decomposition to bound the combinatorial lower level problem and adaptive scalarization to approximate the entire Pareto set of nonlinear nonconvex multiobjective bilevel programs will enable efficient problem solution. Robustness will be evaluated in response to spatial variations in on-scene decisions, and temporal deviations in projected trauma demand and transport resource availability. New surrogate modeling-based algorithms will help solve the resultant maximal parameter subspace identification problem. Data from two states will be used to validate the approach.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.