Underdiagnosis of Hypertension Using Electronic Health Records

  • Banerjee D
  • Chung S
  • Wong E
 et al. 
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Abstract

Background Hypertension is highly prevalent and contributes to cardiovascular morbidity and mortality. Appropriate identification of hypertension is fundamental for its management. The rates of appropriate hypertension diagnosis in outpatient settings using an electronic health record (EHR) have not been well studied. We sought to identify prevalent and incident hypertension cases in a large outpatient healthcare system, examine the diagnosis rates of prevalent and incident hypertension, and identify clinical and demographic factors associated with appropriate hypertension diagnosis.MethodsWe analyzed a 3-year, cross-sectional sample of 251,590 patients aged (greater-than or equal to)18 years using patient EHRs. Underlying hypertension was defined as two or more abnormal blood pressure (ABP) readings (greater-than or equal to)140/90 mm Hg and/or pharmaceutical treatment. Appropriate hypertension diagnosis was defined by the reporting of ICD-9 codes (401.0-401.9). Factors associated with hypertension diagnosis were assessed through multivariate analyses of patient clinical and demographic characteristics. Results The prevalence of hypertension was 28.7%, and the diagnosis rate was 62.9%. The incidence of hypertension was 13.3%, with a diagnosis rate of 19.9%. Predictors of diagnosis for prevalent hypertension included older age, Asian, African American, higher body mass index (BMI), and increased number of ABP readings. Predictors for incident hypertension diagnosis were similar. In patients with two or more ABP readings, hypertension diagnosis was associated with significantly higher medication treatment rates (92.6% vs. 15.8%, P < 0.0001). Conclusion sOutpatient EHR diagnosis rates are suboptimal, yet EHR diagnosis of hypertension is strongly associated with treatment. Targeted efforts to improve diagnosis should be a priority.

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Authors

  • D. Banerjee

  • S. Chung

  • E. C. Wong

  • E. J. Wang

  • R. S. Stafford

  • L. P. Palaniappan

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