PDF(Pubmed)
Abstract：
OBJECTIVE: The objective of this study is to assess the effects of social determinants of health (SDOH) and race-ethnicity on readmission and to investigate the potential for geospatial clustering of patients with a greater burden of SDOH that could lead to a higher risk of readmission.
METHODS: A retrospective study of inpatients at five hospitals within Henry Ford Health (HFH) in Detroit, Michigan from November 2015 to December 2018 was conducted.
METHODS: This study used an adult inpatient registry created based on HFH electronic health record data as the data source. A subset of the data elements in the registry was collected for data analyses that included readmission index, race-ethnicity, six SDOH variables and demographics and clinical-related variables.
METHODS: The cohort was composed of 248 810 admission patient encounters with 156 353 unique adult patients between the study time period. Encounters were excluded if they did not qualify as an index admission for all payors based on the Centers for Medicare and Medicaid Service definition.
METHODS: The primary outcome was 30-day all-cause readmission. This binary index was identified based on HFH internal data supplemented by external validated readmission data from the Michigan Health Information Network.
RESULTS: Race-ethnicity and all SDOH were significantly associated with readmission. The effect of depression on readmission was dependent on race-ethnicity, with Hispanic patients having the strongest effect in comparison to either African Americans or non-Hispanic whites. Spatial analysis identified ZIP codes in the City of Detroit, Michigan, as over-represented for individuals with multiple SDOH.
CONCLUSIONS: There is a complex relationship between SDOH and race-ethnicity that must be taken into consideration when providing healthcare services. Insights from this study, which pinpoint the most vulnerable patients, could be leveraged to further improve existing models to predict risk of 30-day readmission for individuals in future work.
METHODS: A retrospective study of inpatients at five hospitals within Henry Ford Health (HFH) in Detroit, Michigan from November 2015 to December 2018 was conducted.
METHODS: This study used an adult inpatient registry created based on HFH electronic health record data as the data source. A subset of the data elements in the registry was collected for data analyses that included readmission index, race-ethnicity, six SDOH variables and demographics and clinical-related variables.
METHODS: The cohort was composed of 248 810 admission patient encounters with 156 353 unique adult patients between the study time period. Encounters were excluded if they did not qualify as an index admission for all payors based on the Centers for Medicare and Medicaid Service definition.
METHODS: The primary outcome was 30-day all-cause readmission. This binary index was identified based on HFH internal data supplemented by external validated readmission data from the Michigan Health Information Network.
RESULTS: Race-ethnicity and all SDOH were significantly associated with readmission. The effect of depression on readmission was dependent on race-ethnicity, with Hispanic patients having the strongest effect in comparison to either African Americans or non-Hispanic whites. Spatial analysis identified ZIP codes in the City of Detroit, Michigan, as over-represented for individuals with multiple SDOH.
CONCLUSIONS: There is a complex relationship between SDOH and race-ethnicity that must be taken into consideration when providing healthcare services. Insights from this study, which pinpoint the most vulnerable patients, could be leveraged to further improve existing models to predict risk of 30-day readmission for individuals in future work.
摘要：
目的：本研究的目的是评估健康的社会决定因素（SDOH）和种族-种族对再入院的影响，并调查具有更高的SDOH负担的患者的地理空间聚集的可能性，这可能导致更高的再入院风险。
方法：对底特律亨利·福特健康（HFH）五家医院的住院患者进行的回顾性研究，密歇根州于2015年11月至2018年12月进行。
方法：本研究使用基于HFH电子健康记录数据创建的成人住院登记处作为数据源。收集了登记册中数据元素的子集，用于数据分析，其中包括再接纳索引，种族-种族,六个SDOH变量和人口统计学和临床相关变量。
方法：该队列由248810名入院患者和156353名独特的成年患者组成。如果根据医疗保险和医疗补助服务中心的定义，他们没有资格成为所有付款人的指数入场券，则将其排除在外。
方法：主要结局是30天全因再入院。该二进制索引是根据HFH内部数据以及来自密歇根州健康信息网络的外部验证的再入院数据确定的。
结果：种族和所有SDOH均与再入院显着相关。抑郁症对再入院的影响取决于种族，与非洲裔美国人或非西班牙裔白人相比，西班牙裔患者的影响最强。空间分析确定了底特律市的邮政编码，密歇根州,对于具有多个SDOH的个人来说，代表过多。
结论：在提供医疗保健服务时，必须考虑SDOH与种族种族之间的复杂关系。从这项研究的见解，找出最脆弱的病人，可以利用进一步改进现有模型来预测未来工作中个人30天再入院的风险。
方法：对底特律亨利·福特健康（HFH）五家医院的住院患者进行的回顾性研究，密歇根州于2015年11月至2018年12月进行。
方法：本研究使用基于HFH电子健康记录数据创建的成人住院登记处作为数据源。收集了登记册中数据元素的子集，用于数据分析，其中包括再接纳索引，种族-种族,六个SDOH变量和人口统计学和临床相关变量。
方法：该队列由248810名入院患者和156353名独特的成年患者组成。如果根据医疗保险和医疗补助服务中心的定义，他们没有资格成为所有付款人的指数入场券，则将其排除在外。
方法：主要结局是30天全因再入院。该二进制索引是根据HFH内部数据以及来自密歇根州健康信息网络的外部验证的再入院数据确定的。
结果：种族和所有SDOH均与再入院显着相关。抑郁症对再入院的影响取决于种族，与非洲裔美国人或非西班牙裔白人相比，西班牙裔患者的影响最强。空间分析确定了底特律市的邮政编码，密歇根州,对于具有多个SDOH的个人来说，代表过多。
结论：在提供医疗保健服务时，必须考虑SDOH与种族种族之间的复杂关系。从这项研究的见解，找出最脆弱的病人，可以利用进一步改进现有模型来预测未来工作中个人30天再入院的风险。
