Causes and Consequences of Healthcare Efficiency

描述（由申请人提供）：在过去10年中，本PPG专注于记录美国医疗保健中持续存在的低效率。然而，我们仍然对低效率的根源有不完全的理解。我们的方法和措施，亦不足以研究公营或私营机构的政策改变会如何影响成本和质素。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外后果。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、高成本患者的医疗保健效率。我们使用医疗保险，医疗补助和疗养院的数据来研究医生-医院网络中高需求和高成本患者的护理成本和质量。我们将研究这些高需求的患者如何随着医疗保健系统的发展而受到影响-系统是否会改善高需求昂贵患者的护理连续性，或者转而寻求摆脱他们？ 医疗保险人群处方药使用效率。医生-医院网络用于衡量患者在使用有效和无效药物方面的差异，以及对结果和下游成本的影响。我们关注髋部骨折和AMI患者队列，以及65岁以下的残疾医疗保险参保者，非洲裔美国人和最年长的老人。 了解和改善基于发作的医院护理。使用密歇根州医院手术的独特数据集，我们试图了解手术安全性/质量以及首次入院和出院后医疗费用的变化。一个关键问题是医疗保险捆绑支付改革将如何影响65岁以上人群的质量，以及是否会对65岁以下人群产生溢出效应。 医疗保健效率的衡量和决定因素。我们在静态模型（医疗保险，医疗补助和私人保险数据，如果可用），美国和加拿大之间，以及动态措施（查看AMI治疗随时间的变化）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。我们还在美国的三个地点（达特茅斯，宾夕法尼亚州和凯泽科罗拉多）试点患者报告和基于生物标志物的健康措施，并进一步研究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衡量核心提供支持。

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.