Responses to readmissions penalties: What can we learn about hospital behavior?

项目摘要 美国每年大约有4000万人重新入院， 超过400亿美元。从2013年开始，医院再入院减少计划（HRRP） 有三种情况的医疗保险再入院过多的医院：急性心肌梗死，充血性心脏病， 失败和肺炎。选择性髋关节/膝关节置换术和慢性阻塞性肺疾病， 2015年增加，2016年增加冠状动脉旁路移植术。CMS计算医院的风险调整 再入院率使用三年平均值，如果医院的比率超过全国平均水平， 医院在下一年的医疗保险报销率会有所降低。政策的影响范围 近80%的医院每年都受到HRRP的处罚。 在这项研究中，我们将首先确定不同再入院率的医院如何应对 HRRP的财政激励措施。使用2009-2018年HRRP合格条件的数据，我们将研究 未来再入院率变化时，给定年份的医院距离HRRP性能阈值 rates.此外，我们包括几年的前HRRP数据，以控制潜在的均值回归， 再入院率接下来，我们将评估医院或他们所服务的社区的特点 潜在的中度医院反应HRRP。我们将对分析进行分层，以确定 这些以及其他机构和地理特征，缓和了医院对 HRRP。我们假设营利性医院，规模较大，医疗保险份额较高 支付，或具有较低的患者急性将表现出更大的响应HRRP的激励。最后我们 将评估HRRP下观察到的再入院减少是否与以下因素相关： 住院死亡率随之增加。作为一个子目标，我们还将确定医院的 参与以价值为基础的护理方案（例如，负责任的护理组织，捆绑支付） 缓和了再入院和死亡率之间的这种潜在替代。我们假设医院 更多的参与可能会降低再入院率，而不会增加死亡率，但匡威 参与度较低的医院。 这项研究的结果可能对AHRQ的几个优先人群有重要的影响， 老年人、低收入者、城市居民和慢性病患者受到的影响尤其严重 再次入院。首先，我们的方法使我们能够检查医院对不同方面的反应， HRRP的财政激励措施，这可能会建议修改HRRP的计划设计，以进一步 减少再入院。其次，我们将检查潜在的意外后果，如死亡率， 这可能表明某些医院在HRRP下的护理质量下降。

Project Abstract There are approximately 40 million readmissions in the United States per annum, with a price tag of more than $40 billion. Starting in 2013, the Hospital Readmission Reduction Program (HRRP) penalizes hospitals with excess Medicare readmissions for three conditions: acute myocardial infarction, congestive heart failure, and pneumonia. Elective hip/knee replacements and chronic obstructive pulmonary disease were added in 2015, and coronary artery bypass grafts were added in 2016. CMS calculates hospitals’ risk-adjusted readmission rates using a three-year average, and if a hospital’s rate exceeds the national average the hospital receives a reduction in Medicare reimbursement rates in the following year. The reach of the policy has been profound; nearly 80% of hospitals receive penalties under the HRRP each year. In this study, we will first determine how hospitals with varying readmission rates responded to the HRRP’s financial incentives. Using data from 2009-2018 for HRRP-eligible conditions, we will study the effects of hospital distance from the HRRP performance threshold in a given year on future changes in readmission rates. Further, we include several years of pre-HRRP data to control for potential mean reversion in readmissions rates. Next, we will evaluate whether characteristics of hospitals or the communities they serve potentially moderate hospital responsiveness to the HRRP. We will stratify our analyses to determine whether these, as well as other institutional and geographic characteristics, moderate hospitals’ responses to the HRRP. We hypothesize that hospitals which are for-profit, larger in size, have a higher Medicare share of total payments, or have lower patient acuity will demonstrate a larger response to the HRRP’s incentives. Lastly, we will assess whether the observed reductions in hospital readmissions under the HRRP were associated with concomitant increases in hospital mortality rates. As a sub-aim, we will also determine whether hospitals’ participation in value-based care programs (e.g. accountable care organizations, bundled payments) moderates this potential substitution between readmissions and mortality. We hypothesize that hospitals with greater participation may lower readmissions without increasing mortality, but the converse will be true for hospitals with lower participation. The study’s findings may have important implications for several AHRQ priority populations such as the elderly, low-income, urban residents, and those with chronic condition who are disproportionately affected by hospital readmissions. First, our approach allows us to examine hospitals’ responses to different aspects of the HRRP’s financial incentives, which may suggest modifications to the HRRP’s program design to further reduce readmissions. Second, we will check for potential unintended consequences in terms of mortality, which may suggest that quality of care declined under the HRRP for certain hospitals.