Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
Division of Cardiology, School of Medicine, Emory University, Atlanta, Georgia, United States of America.
PLoS One. 2020 Jul 22;15(7):e0236189. doi: 10.1371/journal.pone.0236189. eCollection 2020.
Research based on secondary analysis of data stored in electronic health records (EHR) has gained popularity, but whether the data are consistent with those collected under a study setting is unknown. The objective is to assess the agreement between data obtained in a prospective study and routine-care data extracted retrospectively from the EHR. We compared the data collected in a longitudinal lifestyle intervention study with those recorded in the EHR system over 5 years. A total of 225 working adults were recruited at an academic institution between 2008-2012, whose EHR data were also available during the same time period. After aligning the participants' study visit dates with their hospital encounter dates, data on blood pressure, body mass index (BMI), and laboratory measurements (including high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides, and total cholesterol) were compared via a paired t-test for equivalence with pre-specified margins. Summary statistics were used to compare smoking status and medication prescriptions. Overall, data were consistent between the two sources (i.e., BMI, smoking status, medication prescriptions), whereas some differences were found in cholesterol measurements (i.e., HDL and total cholesterol), possibly due to different lab assays and subject's fasting status. In conclusion, some EHR data are fairly consistent with those collected in a clinical study, whereas others may require further examination. Researchers should evaluate the consistency and quality of EHR data and compare them with other sources of data when possible.
基于电子健康记录（EHR）中存储的数据进行二次分析的研究已经越来越受欢迎，但这些数据是否与研究环境中收集的数据一致尚不清楚。本研究旨在评估从前瞻性研究中获得的数据与从 EHR 中回顾性提取的常规护理数据之间的一致性。我们比较了一项纵向生活方式干预研究中收集的数据与 EHR 系统中 5 年内记录的数据。2008 年至 2012 年间，我们在一所学术机构招募了 225 名在职成年人，在此期间他们的 EHR 数据也可用。在将参与者的研究访问日期与他们的医院就诊日期对齐后，通过配对 t 检验比较血压、体重指数（BMI）和实验室测量值（包括高密度脂蛋白（HDL）、低密度脂蛋白（LDL）、甘油三酯和总胆固醇），以与预先指定的边界进行等效性比较。使用汇总统计数据比较吸烟状况和药物处方。总体而言，两种来源的数据（即 BMI、吸烟状况、药物处方）是一致的，而胆固醇测量值（即 HDL 和总胆固醇）存在一些差异，这可能是由于不同的实验室检测和受试者的禁食状态不同。总之，EHR 中的一些数据与临床研究中收集的数据相当一致，而其他数据可能需要进一步检查。研究人员应评估 EHR 数据的一致性和质量，并在可能的情况下将其与其他来源的数据进行比较。
