Collaborative Research: An Allocation Model with Dynamic Updates for Balanced Workload Distribution on Patient Centered Medical Homes

这项通过系统建模研究推进健康服务的合作项目的目标是为新的业务规则和运营科学奠定科学基础，这些规则和操作科学有助于以患者为中心的医疗家庭模式(PCMH)。PCMH模式是一种新兴的基于团队的初级保健方法，旨在改善患者健康的及时性、护理的连续性、护理成本和全面性。这个为期三年的项目有以下任务：1)制定全面的医疗信息技术数据准备策略，以提供医疗需求和供应组合数据；2)开发基于离散聚类的自适应统计估计模型，该模型可以根据关键患者属性(如诊断和治疗特征)预测医疗工作量；3)创建随机优化模型，以帮助管理所有PCMH团队的患者小组和人员水平。这样的模型将为随机迁移的医疗机构中的患者和人员分配提供动态更新规则；并将提供一个实时预约调度系统，通过在随机患者服务需求下的最优患者分配和人员配置来改善日常运营。随着医疗工作量组合估计模型、患者分配模型和动态调度策略的发展，本研究将通过将患者分配给提供者团队成员来直接支持PCMH实践，从而使提供者？时间可以得到充分利用，患者可以得到及时、充足和经济的医疗保健。该项目将与美国最大的医疗保健系统--退伍军人健康管理局合作。我们预计这项研究的结果将在数百家医疗机构采用和实施。这项研究将被带入课堂，以激励和吸引本科生和研究生，特别是代表不足的群体。这项研究将有助于和提高我们的研究生水平的课程和研讨会。此外，还将在校园和各种会议上举办讲习班。

The goal of this collaborative Advancing Health Services through System Modeling Research project is to lay a scientific foundation for new business rules and operation sciences useful for the patient centered medical home model (PCMH). The PCMH model is an emerging team-based approach for primary care aimed at improving timely access to care, continuity of care, care cost and comprehensiveness for patient wellness. This three-year project has the following tasks: 1) to develop a comprehensive health information technology data preparation strategy to provide healthcare demand and supply portfolio data 2) to develop an adaptive discrete-cluster-based statistical estimation model that can predict healthcare workload based on key patient attributes, such as diagnosis and treatment characteristics, and 3) to create stochastic optimization models to aid in managing patient panels and staffing levels for all PCMH teams. Such models would provide dynamic updating rules for patient and staffing allocation with a stochastically migrating patient population in medical facilities; and would provide a real time appointment scheduling system to improve daily operations through optimal patient allocation and staffing under stochastic patient demand for service. With the development of a healthcare workload portfolio estimation model, patient allocation model and dynamic scheduling strategy, this research will directly support PCMH practices by assigning patients to provider team members so that that providers? time can be fully utilized and patients receive prompt, adequate and economical healthcare. The project will be in collaboration with the largest healthcare system in U.S., the Veterans Health Administration. We expect the results of this research to be adopted and implemented in hundreds of medical facilities. The research will be brought into classrooms to inspire and engage undergraduate and graduate students, especially underrepresented groups. This research will contribute to and enhance our graduate level courses and seminars. In addition workshops will be developed on campus and in various conferences.