PURPOSE OF REVIEW: Use of the electronic health record (EHR) for CVD surveillance is increasingly common. However, these data can introduce systematic error that influences the internal and external validity of study findings. We reviewed recent literature on EHR-based studies of CVD risk to summarize the most common types of bias that arise. Subsequently, we recommend strategies informed by work from others as well as our own to reduce the impact of these biases in future research. RECENT FINDINGS: Systematic error, or bias, is a concern in all observational research including EHR-based studies of CVD risk surveillance. Patients captured in an EHR system may not be representative of the general population, due to issues such as informed presence bias, perceptions about the healthcare system that influence entry, and access to health services. Further, the EHR may contain inaccurate information or be missing key data points of interest due to loss to follow-up or over-diagnosis bias. Several strategies, including implementation of unique patient identifiers, adoption of standardized rules for inclusion/exclusion criteria, statistical procedures for data harmonization and analysis, and incorporation of patient-reported data have been used to reduce the impact of these biases. SUMMARY: EHR data provide an opportunity to monitor and characterize CVD risk in populations. However, understanding the biases that arise from EHR datasets is instrumental in planning epidemiological studies and interpreting study findings. Strategies to reduce the impact of bias in the context of EHR data can increase the quality and utility of these data.
Background: Electronic health record (EHR) data can measure cardiovascular health (CVH) of patient populations, but have limited generalizability when derived from one health care system. Objective: We used The Guideline Advantage™ (TGA) data repository, comprising EHR data of patients from 8 diverse health care systems, to describe CVH of adult patients and progress towards the American Heart Association’s (AHA’s) 2020 Impact Goals. Methods: Our analysis included 203,488 patients with 677,733 encounters recorded in TGA from 2012 to 2015. Five measures from EHRs [cigarette smoking status, body mass index (BMI), blood pressure (BP), cholesterol, and diabetes mellitus (DM)] were categorized as poor/intermediate/ideal according to AHA’s Life’s Simple 7 algorithm. We presented distributions and trends of CVH for each metric over time, first using all available data, and then in a subsample (n = 1,890) of patients with complete data on all metrics. Results: Among all patients, the greatest stride towards ideal CVH attainment from 2012 to 2015 was for cigarette smoking (50.6 percent to 65 percent), followed by DM (17.3 percent to 20.7 percent) and BP (21.1 percent to 23.2 percent). Overall, prevalence of ideal CVH did not increase for any metric in the subsample. Males slightly improved in ideal CVH for BMI and cholesterol; meanwhile, females saw no improvement in ideal CVH for any metric. As ideal CVH for BP and cholesterol increased slightly among white patients, ideal CVH for BP, cholesterol, BMI, and DM worsened for non-whites. Conclusion: Despite improvements in some CVH metrics in the outpatient setting, more tangible progress is needed to meet AHA’s 2020 Impact Goals.
Introduction: New High Blood Pressure (BP) Guidelines released by the American Heart Association (AHA) and the American College of Cardiology redefined hypertension, imparting implications for monitoring cardiovascular health (CVH). The impact on reclassification of patients according to electronic health record (EHR) data as a result of changes in criteria for BP cut points has not yet been described. Hypothesis: We hypothesized that more stringent cut points for hypertension would increase the prevalence of United States (US) adults with poor CVH for BP. Methods: We analyzed outpatient visit data recorded in The Guideline Advantage©, a repository of EHRs of patients from eight diverse healthcare systems in the US from 2012-2015. For each year, the first non-missing BP measurement for each patient was categorized into poor (hypertensive), intermediate (pre-hypertensive), and ideal (normotensive) for CVH, first in accordance with AHA’s Life Simple 7 guidelines, and then in accordance with the new guidelines. We compared overall trends with trends stratified by race and sex, in distributions of poor and intermediate categories, and in the proportion eligible for pharmacological treatment (BP ≥ 130/80). Results: A total of 172,209 unique patients contributed 348,933 BP measurements, and most were female (58.63%) and white (75.09%). Although the prevalence of poor CVH for BP was consistently 3-fold higher under the new guidelines and the difference in prevalence was significant (p<0.0001), it decreased over time for the both the old (9.4% to 8.7%) and new (27.8% to 26.4%) guidelines. Over time, the proportion classified as hypertensive decreased (12.4% to 10.4 vs. 33.9% to 30.3%) for males and increased for non-whites (10.2% to 13.9% vs. 27.1% to 35.3%) from the old and new guidelines, respectively, but remained stable for females and whites. Similarly, the annual difference in the proportion of intermediate CVH for BP was significant (p<0.0001); however, pre-hypertension prevalence slightly increased under the old (57.9% to 58.5%) and new (39.5% to 40.7%) guidelines. Among untreated adults eligible for pharmacological intervention, the proportion remained relatively unchanged over time; in 2015, patients lacking treatment yet meeting treatment criteria was 23% and 7.3% under the new and old guidelines, respectively, resulting in a difference of 15.7% (p<0.0001). Whites (66.8%) and females (50.6%), compared with non-whites and males, respectively, comprised the majority. Conclusions: Prevalence of poor CVH for BP among US adults substantially increases in the outpatient setting when categorizing measures with the new guidelines. Active participation by clinicians and public health practitioners are needed to address the higher prevalence of and disparities in both hypertension and treatment prescription identified with the old versus new guidelines.
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