Causes and Consequences of Healthcare Efficiency

描述（由申请人提供）：在过去的10年里，本PPG专注于记录美国医疗保健中持续的低效率。然而，我们对低效率的根源仍然知之甚少。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，我们担心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。这个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、高成本患者的医疗保健效率。我们使用医疗保险、医疗补助和养老院的数据来研究医医院网络中高需求和高成本患者的护理成本和质量。我们将研究随着医疗保健系统的发展，这些高需求患者是如何受到影响的——系统是会改善高需求、高成本患者的护理连续性，还是会寻求摆脱他们？医疗保险人群处方药使用效率研究。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。我们关注髋部骨折和急性心肌梗死的患者队列，以及65岁以下的残疾医疗保险参保者、非裔美国人和老年人。了解并改善基于事件的医院护理。使用密歇根医院手术的独特数据集，我们试图了解手术安全/质量以及初次入院和出院后医疗保健支出的变化。一个关键问题是，医疗保险捆绑支付改革将如何影响65岁以上人群的医疗质量，以及65岁以下人群是否会受到溢出效应的影响。医疗保健效率的测量和决定因素。我们在美国和加拿大之间的静态模型（医疗保险、医疗补助和私人保险数据可用时）和动态测量（观察AMI治疗的随时间变化）中估计提供者效率模型。提出风险调整和绩效考核措施。为了改善风险调整，我们从健康与退休研究（HRS）和医疗保险中制定了新的健康措施。我们还在美国的三个地点（宾夕法尼亚州达特茅斯和科罗拉多州凯撒）试点了患者报告和基于生物标志物的健康测量，并进一步研究了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度量核心支持。

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.