Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA.
J Gen Intern Med. 2024 Mar;39(4):643-651. doi: 10.1007/s11606-023-08503-x. Epub 2023 Nov 6.
Risk stratification and population management strategies are critical for providing effective and equitable care for the growing population of older adults in the USA. Both frailty and neighborhood disadvantage are constructs that independently identify populations with higher healthcare utilization and risk of adverse outcomes.
To examine the joint association of these factors on acute healthcare utilization using two pragmatic measures based on structured data available in the electronic health record (EHR).
In this retrospective observational study, we used EHR data to identify patients aged ≥ 65 years at Atrium Health Wake Forest Baptist on January 1, 2019, who were attributed to affiliated Accountable Care Organizations. Frailty was categorized through an EHR-derived electronic Frailty Index (eFI), while neighborhood disadvantage was quantified through linkage to the area deprivation index (ADI). We used a recurrent time-to-event model within a Cox proportional hazards framework to examine the joint association of eFI and ADI categories with healthcare utilization comprising emergency visits, observation stays, and inpatient hospitalizations over one year of follow-up.
We identified a cohort of 47,566 older adults (median age = 73, 60% female, 12% Black). There was an interaction between frailty and area disadvantage (P = 0.023). Each factor was associated with utilization across categories of the other. The magnitude of frailty's association was larger than living in a disadvantaged area. The highest-risk group comprised frail adults living in areas of high disadvantage (HR 3.23, 95% CI 2.99-3.49; P < 0.001). We observed additive effects between frailty and living in areas of mid- (RERI 0.29; 95% CI 0.13-0.45; P < 0.001) and high (RERI 0.62, 95% CI 0.41-0.83; P < 0.001) neighborhood disadvantage.
Considering both frailty and neighborhood disadvantage may assist healthcare organizations in effectively risk-stratifying vulnerable older adults and informing population management strategies. These constructs can be readily assessed at-scale using routinely collected structured EHR data.
风险分层和人群管理策略对于为美国不断增长的老年人口提供有效和公平的护理至关重要。衰弱和邻里劣势都是独立识别具有更高医疗保健利用率和不良结果风险的人群的构建。
使用电子健康记录 (EHR) 中可用的两种基于结构化数据的实用措施,研究这些因素对急性医疗保健利用的联合关联。
在这项回顾性观察性研究中,我们使用 EHR 数据确定 2019 年 1 月 1 日在阿特鲁姆健康威克森林浸信会的年龄≥65 岁的患者,并将其归属于附属的问责制医疗保健组织。通过 EHR 衍生的电子衰弱指数 (eFI) 对衰弱进行分类,而邻里劣势则通过与区域贫困指数 (ADI) 联系进行量化。我们使用复发时间事件模型在 Cox 比例风险框架内,研究 eFI 和 ADI 类别与医疗保健利用的联合关联,包括一年随访期间的急诊就诊、观察住院和住院治疗。
我们确定了一个由 47566 名老年人组成的队列(中位数年龄=73 岁,60%为女性,12%为黑人)。衰弱和区域劣势之间存在交互作用(P=0.023)。每个因素都与其他因素的类别利用相关。衰弱的关联幅度大于生活在劣势地区。风险最高的群体是生活在高劣势地区的虚弱成年人(HR 3.23,95%CI 2.99-3.49;P<0.001)。我们观察到衰弱和生活在中(RERI 0.29;95%CI 0.13-0.45;P<0.001)和高(RERI 0.62,95%CI 0.41-0.83;P<0.001)邻里劣势地区之间存在累加效应。
同时考虑衰弱和邻里劣势可以帮助医疗保健组织有效地对脆弱的老年人进行风险分层,并为人口管理策略提供信息。这些结构可以使用常规收集的结构化 EHR 数据进行大规模评估。