Marino Miguel, Angier Heather, Valenzuela Steele, Hoopes Megan, Killerby Marie, Blackburn Brenna, Huguet Nathalie, Heintzman John, Hatch Brigit, O'Malley Jean P, DeVoe Jennifer E
Department of Family Medicine, Oregon Health & Science University, Portland, OR, USA.
School of Public Health, Oregon Health & Science University, Portland, OR, USA.
Prev Med Rep. 2018 Jul 27;11:297-304. doi: 10.1016/j.pmedr.2018.07.009. eCollection 2018 Sep.
Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristics are associated with accurate documentation. Our objective was to evaluate the validity of EHR data for monitoring longitudinal Medicaid coverage and assess variation by patient demographics, visit types, and clinic characteristics. We conducted a retrospective, observational study comparing Medicaid status agreement between Oregon community health center EHR data linked at the patient-level to Medicaid enrollment data (gold standard). We included adult patients with a Medicaid identification number and ≥1 clinic visit between 1/1/2013-12/31/2014 [>1 million visits (n = 135,514 patients)]. We estimated statistical correspondence between EHR and Medicaid data at each visit (visit-level) and for different insurance cohorts over time (patient-level). Data were collected in 2016 and analyzed 2017-2018. We observed excellent agreement between EHR and Medicaid data for health insurance information: kappa (>0.80), sensitivity (>0.80), and specificity (>0.85). Several characteristics were associated with agreement; at the visit-level, agreement was lower for patients who preferred a non-English language and for visits missing income information. At the patient-level, agreement was lower for black patients and higher for older patients seen in primary care community health centers. Community health center EHR data are a valid source of Medicaid coverage information. Agreement varied with several characteristics, something researchers and clinic staff should consider when using health insurance information from EHR data.
医疗保险覆盖有助于获得预防性筛查和其他基本医疗服务，并与改善健康结果相关联；因此，了解电子健康记录（EHR）中覆盖信息的记录情况以及哪些特征与准确记录相关至关重要。我们的目标是评估EHR数据用于监测纵向医疗补助覆盖情况的有效性，并评估患者人口统计学特征、就诊类型和诊所特征的差异。我们进行了一项回顾性观察研究，比较俄勒冈州社区健康中心患者层面与医疗补助登记数据（金标准）相链接的EHR数据中的医疗补助状态一致性。我们纳入了有医疗补助识别号码且在2013年1月1日至2014年12月31日期间有≥1次诊所就诊的成年患者[超过100万次就诊（n = 135,514名患者）]。我们估计了每次就诊（就诊层面）以及不同保险队列随时间（患者层面）EHR与医疗补助数据之间的统计一致性。数据于2016年收集，并在2017 - 2018年进行分析。我们观察到EHR与医疗补助数据在健康保险信息方面具有极佳的一致性：kappa（>0.80）、敏感性（>0.80）和特异性（>0.85）。有几个特征与一致性相关；在就诊层面，偏好非英语语言的患者以及缺少收入信息的就诊的一致性较低。在患者层面，黑人患者的一致性较低，而在初级保健社区健康中心就诊的老年患者的一致性较高。社区健康中心EHR数据是医疗补助覆盖信息的有效来源。一致性随几个特征而变化，研究人员和诊所工作人员在使用EHR数据中的健康保险信息时应予以考虑。
