Validity of Cardiovascular Data From Electronic Sources

Abstract

Understanding the validity of data from electronic data research networks is critical to national research initiatives and learning healthcare systems for cardiovascular care. Our goal was to evaluate the degree of agreement of electronic data research networks in comparison with data collected by standardized research approaches in a cohort study. We linked individual-level data from MESA (Multi-Ethnic Study of Atherosclerosis), a community-based cohort, with HealthLNK, a 2006 to 2012 database of electronic health records from 6 Chicago health systems. To evaluate the correlation and agreement of blood pressure in HealthLNK in comparison with in-person MESA examinations, and body mass index in HealthLNK in comparison with MESA, we used Pearson correlation coefficients and Bland-Altman plots. Using diagnoses in MESA as the criterion standard, we calculated the performance of HealthLNK for hypertension, obesity, and diabetes mellitus diagnosis by using International Classification of Diseases, Ninth Revision codes and clinical data. We also identified potential myocardial infarctions, strokes, and heart failure events in HealthLNK and compared them with adjudicated events in MESA. Of the 1164 MESA participants enrolled at the Chicago Field Center, 802 (68.9%) participants had data in HealthLNK. The correlation was low for systolic blood pressure (0.39; P<0.0001). In comparison with MESA, HealthLNK overestimated systolic blood pressure by 6.5 mm Hg (95% confidence interval, 4.2-7.8). There was a high correlation between body mass index in MESA and HealthLNK (0.94; P<0.0001). HealthLNK underestimated body mass index by 0.3 kg/m2 (95% confidence interval, -0.4 to -0.1). With the use of International Classification of Diseases, Ninth Revision codes and clinical data, the sensitivity and specificity of HealthLNK queries for hypertension were 82.4% and 59.4%, for obesity were 73.0% and 89.8%, and for diabetes mellitus were 79.8% and 93.3%. In comparison with adjudicated cardiovascular events in MESA, the concordance rates for myocardial infarction, stroke, and heart failure were, respectively, 41.7% (5/12), 61.5% (8/13), and 62.5% (10/16). These findings illustrate the limitations and strengths of electronic data repositories in comparison with information collected by traditional standardized epidemiological approaches for the ascertainment of cardiovascular risk factors and events.