Identifying patients with hypertension: a case for auditing electronic health record data.

Perspect Health Inf Manag

Office of Health Services Research, West Virginia University, Department of Community Medicine, Morgantown, WV, USA.

Published: November 2012

AI Article Synopsis

  • Electronic health record (EHR) data issues hinder research and quality improvement in healthcare.
  • This study investigates the effectiveness of importing de-identified EHR data to better identify patients with essential hypertension.
  • Results show that combining diagnostic coding with free-text coding significantly increases patient identification, which has important implications for improving care quality and achieving healthcare standards.

Article Abstract

Problems in the structure, consistency, and completeness of electronic health record data are barriers to outcomes research, quality improvement, and practice redesign. This nonexperimental retrospective study examines the utility of importing de-identified electronic health record data into an external system to identify patients with and at risk for essential hypertension. We find a statistically significant increase in cases based on combined use of diagnostic and free-text coding (mean = 1,256.1, 95% CI 1,232.3-1,279.7) compared to diagnostic coding alone (mean = 1,174.5, 95% CI 1,150.5-1,198.3). While it is not surprising that significantly more patients are identified when broadening search criteria, the implications are critical for quality of care, the movement toward the National Committee for Quality Assurance's Patient-Centered Medical Home program, and meaningful use of electronic health records. Further, we find a statistically significant increase in potential cases based on the last two or more blood pressure readings greater than or equal to 140/90 mm Hg (mean = 1,353.9, 95% CI 1,329.9-1,377.9).

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3329209PMC

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