Center for Population Health IT, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Center for Population Health IT, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Am J Prev Med. 2019 Jun;56(6):811-818. doi: 10.1016/j.amepre.2018.12.012. Epub 2019 Apr 17.
This study aims to assess the effect of individual and geographic-level social determinants of health on risk of hospitalization in the Veterans Health Administration primary care clinics known as the Patient Aligned Care Team.
For a population of Veterans enrolled in the primary care clinics, the study team extracted patient-level characteristics and healthcare utilization records from 2015 Veterans Health Administration electronic health record data. They also collected census data on social determinants of health factors for all U.S. census tracts. They used generalized estimating equation modeling and a spatial-based GIS analysis to assess the role of key social determinants of health on hospitalization. Data analysis was completed in 2018.
A total of 6.63% of the Veterans Health Administration population was hospitalized during 2015. Most of the hospitalized patients were male (93.40%) and white (68.80%); the mean age was 64.5 years. In the generalized estimating equation model, white Veterans had a 15% decreased odds of hospitalization compared with non-white Veterans. After controlling for patient-level characteristics, Veterans residing in census tracts with the higher neighborhood SES index experienced decreased odds of hospitalization. A spatial-based analysis presented variations in the hospitalization rate across the Veterans Health Administration primary care clinics and identified the clinic sites with an elevated risk of hospitalization (hotspots) compared with other clinics across the country.
By linking patient and population-level data at a geographic level, social determinants of health assessments can help with designing population health interventions and identifying features leading to potentially unnecessary hospitalization in selected geographic areas that appear to be outliers.
本研究旨在评估个体和地理层面的健康社会决定因素对退伍军人健康管理局(Veterans Health Administration,VHA)患者医疗团队初级保健诊所住院风险的影响。
对于在初级保健诊所注册的退伍军人人群,研究团队从 2015 年退伍军人健康管理局电子健康记录数据中提取了患者特征和医疗保健利用记录,并收集了全美所有普查区健康社会决定因素的普查数据。他们使用广义估计方程模型和基于空间的 GIS 分析来评估关键健康社会决定因素对住院的作用。数据分析于 2018 年完成。
2015 年,VHA 人群中有 6.63%的人住院。大多数住院患者为男性(93.40%)和白人(68.80%);平均年龄为 64.5 岁。在广义估计方程模型中,与非白人退伍军人相比,白人退伍军人的住院几率降低了 15%。在控制了患者特征后,居住在邻里社会经济地位指数较高的普查区的退伍军人,其住院几率降低。基于空间的分析显示,VHA 初级保健诊所的住院率存在差异,并确定了与全国其他诊所相比住院风险较高的诊所(热点)。
通过在地理层面上链接患者和人群层面的数据,健康社会决定因素评估可以帮助设计人群健康干预措施,并确定在某些地理区域可能导致不必要住院的特征,这些区域似乎是异常值。