Causes and Consequences of Healthcare Efficiency

描述(由申请人提供)：在过去的10年里，这份PPG专注于记录美国医疗保健领域持续的低效。然而，我们对低效的根源仍有不完全的理解。我们的方法和措施也不足以研究公共或私营部门的政策变化将如何影响成本和质量。最后，我们对政策变化对弱势患者产生不利影响的潜在意想不到的后果表示关切。此PPG应用程序通过5个不同的子项目解决了这些差距：高需求、高成本患者的医疗效率。我们使用Medicare、Medicaid和疗养院数据来研究医生-医院网络中高需求且往往高成本的患者的护理成本和质量。我们将研究随着医疗系统的发展，这些高需求患者是如何受到影响的--该系统是会改善对高需求昂贵患者的连续性护理，还是会寻求摆脱他们？医疗保险人群中处方药的使用效率。医生-医院网络被用来衡量患者在使用高效和低效药物方面的差异，以及对结果和下游成本的影响。我们专注于髋部骨折和急性心肌梗死患者队列，以及65岁以下残疾医疗保险参与者、非裔美国人和年龄最大的老年人。理解和改进以情节为基础的医院护理。使用密歇根医院独特的手术数据集，我们试图了解在最初入院和出院后手术安全/质量和医疗费用的变化。一个关键问题是，联邦医疗保险捆绑支付改革将如何影响65岁以上人群的质量，以及是否会对65岁以下人群产生溢出效应。医疗效率的测量和决定因素。我们在静态模型(使用Medicare、Medicaid和私人保险数据(如果可用))、美国和加拿大之间以及动态指标(查看急性心肌梗死治疗过程中的变化)中估计提供者效率的模型。推进风险调整和绩效评估措施。为了改善风险调整，我们从健康和退休研究(HRS)和医疗保险中开发了新的健康措施。我们还在美国三个地点(达特茅斯、宾夕法尼亚州和科罗拉多州凯撒)试验了患者报告的和基于生物标记物的健康衡量标准，并进一步研究了对临床医生的反馈如何影响护理质量。所有5个子项目都由一个管理核心、一个数据核心和一个测量核心提供支持。

DESCRIPTION (provided by applicant): During the past 10 years, this PPG has focused on documenting persistent inefficiency in U.S. healthcare. Yet we still have an incomplete understanding of the sources of Inefficiency. Nor are our methods and measures adequate to study how policy changes arising in the public or private sector will affects costs and quality. Finally, we are concerned about potential unintended consequences of policy changes adversely affecting vulnerable patients. This PPG application addresses these gaps with 5 distinct subprojects: Healthcare Efficiency among High Need, High Cost Patients. We use Medicare, Medicaid, and nursing home data to study the cost and quality of care for high-need and often high-cost patients within physician-hospital networks. We will study how these high-need patients are affected as healthcare systems evolve - will systems improve the continuity of care for high-need costly patients, or instead seek to shed them? Efficiency of Prescription Drug Use in the Medicare Population. Physician-hospital networks are used to measure differences across patients in their use of efficient and inefficient pharmaceutical use, and the implications for outcomes and downstream costs. We focus on patient cohorts with hip fractures and AMI, as well as under-age-65 disabled Medicare enrollees, African-Americans, and the oldest-old. Understanding and Improving Episode-based Hospital Care. Using a unique dataset on surgery in Michigan hospitals, we seek to understand variations in surgical safety/quality and in healthcare expenditures during the Initial admission and post-discharge. A key question is how Medicare bundled payment reform will affect quality for the over-65, and whether there are spillover effects to the under-65. Measurement and Determinants of Healthcare Efficiency. We estimate models of provider efficiency in static models (with Medicare, Medicaid, and private insurance data when available), between the U.S. and Canada, and with dynamic measures (looking at changes overtime in AMI treatments). Advancing Measures for Risk Adjustment and Performance Assessment. To improve risk adjustment, we develop new health measures from the Health and Retirement Study (HRS) and Medicare. We also pilot patient-reported and biomarker-based measures of health in three sites across the U.S. (Dartmouth, Pennsylvania, and Kaiser Colorado), and further study how feedback to clinicians affects care quality. All 5 subprojects are supported by an Administrative Core, a Data Core, and a Measurement Core.