Measuring health disparities using a continuous social risk factor.
Measuring health disparities using a continuous social risk factor.
复制标题
使用连续的社会风险因素衡量健康差异。
DOI：
10.1111/1475-6773.14048
复制
发表时间：
2023
影响因子：
3.4
通讯作者：
Bernheim,Susannah
中科院分区：
文献类型：
--
作者：
Herrin,Jeph;Barthel,Andrea;Goutos,Demetri;Du,Chengan;Zhou,Sheng;Peltz,Alon;Poyer,James;Lin,Zhenqiu;Bernheim,Susannah
目的根据连续的多社会风险因素对这些结果的影响，提出并评估一种衡量医院水平差异的新方法。研究背景我们的队列由 65 岁及以上的 Medicare 按服务付费 (FFS) 患者组成，他们因六种常见病症或手术之一入住急症护理医院。使用了六项医院再入院措施的医疗保险行政索赔数据，包括 2015 年 7 月至 2018 年 6 月的住院治疗。 研究设计我们采用了现有的方法，这些方法是使用二分社会风险因素 (SRF) 报告医院级别的差异。现有方法报告了医院内部和医院之间的差异；我们使用医疗保健研究机构和质量社会经济状况指数开发并测试了这两种方法的修改方法。我们将调整后的方法应用于医疗保险和医疗补助服务中心医院再入院减少计划措施中包含的六项为期 30 天的再入院措施。我们将每个医院内部和跨医院的结果与使用原始方法获得的结果进行比较，并将 AHRQ SES 指数分为“低”和“高”分数。数据收集我们使用与美国人口普查数据相关的 Medicare FFS 行政索赔数据。主要发现对于所有六种再入院指标，我们发现，与现有方法相比，连续 SRF 的方法为更多机构提供了差异结果，尽管值范围较窄。基于这种方法的差异度量与基于相同风险因素的二分版本的差异度量具有中度至高度相关性，同时反映了更全面的风险范围。这种方法为检测提供者层面的结果提供了机会，这些结果与潜在的社会风险更紧密地一致。结论我们已经证明了使用连续的多社会风险因素估计医院护理差异的可行性和实用性。这种方法扩大了报告医院层面差异的潜力，同时更好地考虑了社会风险对医院结果的多因素性质。
ObjectiveTo propose and evaluate a novel approach for measuring hospital‐level disparities according to the effect of a continuous, polysocial risk factor on those outcomes.Study SettingOur cohort consisted of Medicare Fee‐for‐Service (FFS) patients 65 years and older admitted to acute care hospitals for one of six common conditions or procedures. Medicare administrative claims data for six hospital readmission measures including hospitalizations from July 2015 to June 2018 were used.Study DesignWe adapted existing methodologies that were developed to report hospital‐level disparities using dichotomous social risk factors (SRFs). The existing methods report disparities within and across hospitals; we developed and tested modified approaches for both methods using the Agency for Healthcare Research and Quality Socioeconomic Status Index. We applied the adapted methodologies to six 30‐day hospital readmission measures included in the Centers for Medicare & Medicaid Services Hospital Readmissions Reduction Program measures. We compared the within‐ and across‐hospital results for each to those obtained from using the original methods and dichotomizing the AHRQ SES Index into “low” and “high” scores.Data CollectionWe used Medicare FFS administrative claims data linked to U.S. Census data.Principal FindingsFor all six readmission measures we find that, when compared with the existing methods, the methods for continuous SRFs provide disparity results for more facilities though across a narrower range of values. Measures of disparity based on this approach are moderately to highly correlated with those based on a dichotomous version of the same risk factor, while reflecting a fuller spectrum of risk. This approach represents an opportunity for detection of provider‐level results that more closely align with underlying social risk.ConclusionWe have demonstrated the feasibility and utility of estimating hospital disparities of care using a continuous, polysocial risk factor. This approach expands the potential for reporting hospital‐level disparities while better accounting for the multifactorial nature of social risk on hospital outcomes.