Johns Hopkins Bloomberg School of Public Health.
Department of Health Policy and Management, Johns Hopkins Center for Health Disparities Solutions.
Med Care. 2018 Nov;56(11):934-943. doi: 10.1097/MLR.0000000000000988.
The Hospital Readmission Reduction Program (HRRP) disproportionately penalizes hospitals serving minority communities. The National Academy of Science, Engineering, and Medicine has recommended that the Centers for Medicare and Medicaid Services (CMS) consider adjusting for social risk factors in their risk adjustment methodology. This study examines the association between the racial and ethnic composition of a hospital market and the impact of other social risk factors on the probability of a hospital being penalized under the HRRP.
This study analyzes data from CMS, the American Hospital Association, and the American Community Survey for 3168 hospitals from 2013 to 2017. We used logistic regression models to estimate the association between the penalty status under HRRP and the racial and ethnic composition of a hospital market, and explored whether this association was moderated by other social risk factors.
Our results indicate that the probability of being penalized increases with the percentage of black and Asian residents in the hospital service area (HSA) and decreased with the percentage of Hispanic residents in the HSA. This association was reduced and became statistically insignificant when we controlled for other social risk factors. The strongest predictors of penalty status were the hospital's share of Medicaid patients and the percent of persons without a high school diploma in the HSA.
By incorporating relevant social risk factors in the reimbursement methodology, CMS could mitigate the negative effects of HRRP on hospitals serving minority communities.
医院再入院率降低计划(HRRP)不成比例地惩罚服务少数族裔社区的医院。美国国家科学院、工程院和医学院建议医疗保险和医疗补助服务中心(CMS)在其风险调整方法中考虑社会风险因素。本研究考察了医院市场的种族和民族构成与其他社会风险因素对医院在 HRRP 下被处罚的可能性之间的关联。
本研究分析了来自 CMS、美国医院协会和 2013 年至 2017 年美国社区调查的 3168 家医院的数据。我们使用逻辑回归模型来估计 HRRP 下的处罚状况与医院市场的种族和民族构成之间的关联,并探讨了这种关联是否受到其他社会风险因素的调节。
我们的结果表明,在医院服务区(HSA)中,黑人居民和亚洲居民的比例越高,被处罚的概率就越高,而 HSA 中西班牙裔居民的比例越低,被处罚的概率就越低。当我们控制了其他社会风险因素时,这种关联会减少,并且变得不具有统计学意义。处罚状况的最强预测因素是医院 Medicaid 患者的比例和 HSA 中没有高中文凭的人的比例。
通过在报销方法中纳入相关社会风险因素,CMS 可以减轻 HRRP 对服务少数族裔社区的医院的负面影响。