Stochastic Modeling and Optimization of Longitudinal Health Care Coordination

纵向医疗保健协调的随机建模和优化

• 批准号: 1233095
• 负责人: MARK VAN OYEN
• 金额: $ 42万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1233095&HistoricalAwards=false
• 关键词: Stochastic; Modeling; Optimization; Longitudinal; Health

This research targets lupus, a prototypic complex disease, and supports care delivery in other contexts. To achieve care based on best practices, lupus requires sophisticated operational planning and scheduling capabilities and sometimes requires infusion-based treatments. A key innovation is to model capacity and provide planning decision support so as to effectively integrate clinical research activities into the clinical care delivery site. Lacking effective planning and appointment scheduling, the inconsistent capture of key disease activity tools degrades the ability to manage a disease like lupus and results in unnecessarily frequent visits to already scarce physicians. Novel operations decision support methodology will be developed to (1) improve access to care (reduced waiting), (2) reduce costly overtime and staff turnover while better utilizing physicians and staff, (3) better support evidence-based medicine, and (4) provide useful decision support for the administration of clinical research studies with clinical care.If successful, key fundamental science and technology innovations will provide longitudinally coordinated health care and better health services research. For lupus, targeted operational systems improvements are known to improve patient health outcomes. The methodology will integrate delivery site planning and appointment scheduling. The former includes decision support for setting the mix of clinical care and clinical research services to be provided and setting the staff size (and composition) and number of rooms. Stochastic process models with integrated optimization algorithms will be created. The research will generate freely available teaching resources for engineers, physicians, researchers, and administrative delivery personnel. The dissemination will also facilitate commercialization. Conduct of the research will support the education and research development of graduate and undergraduate students with attention to underrepresented students.

这项研究的目标是狼疮，一种典型的复杂疾病，并支持在其他情况下的护理提供。为了实现基于最佳实践的护理，狼疮需要复杂的操作计划和调度能力，有时还需要基于输液的治疗。一个关键的创新是建立能力模型并提供规划决策支持，以便有效地将临床研究活动整合到临床护理提供地点。缺乏有效的规划和预约安排，对关键疾病活动工具的不一致捕获降低了管理狼疮等疾病的能力，并导致不必要地频繁拜访本已稀缺的医生。将开发新的运营决策支持方法，以(1)改善获得护理的机会(减少等待)，(2)减少昂贵的加班和员工流动，同时更好地利用医生和员工，(3)更好地支持循证医学，以及(4)为临床研究和临床护理的管理提供有用的决策支持。如果成功，关键的基础科学和技术创新将提供纵向协调的卫生保健和更好的卫生服务研究。对于狼疮来说，众所周知，有针对性的操作系统改进可以改善患者的健康结果。该方法将整合交付地点规划和预约安排。前者包括为确定要提供的临床护理和临床研究服务的组合以及确定工作人员规模(和组成)和房间数量提供决策支持。将创建具有集成优化算法的随机过程模型。这项研究将为工程师、医生、研究人员和行政交付人员提供免费的教学资源。传播还将促进商业化。开展这项研究将支持研究生和本科生的教育和研究发展，并关注代表性不足的学生。