Improving Hypertension Quality Measurement Using Electronic Health Records

Bibliographic Data

ID9099292
AuthorsStephen D Persell (0000-0003-2462-1314, Northwestern University, corresponding author), Abel N Kho, Abel Kho (0000-0003-1993-5634, General Department of Preventive Medicine, corresponding author), Jason A Thompson (Northwestern University, corresponding author), David W Baker (0000-0001-7349-7554, Northwestern University, corresponding author)
Year2009
Volume47
Issue4
Pages388-394
Publication date2009-04-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0b013e31818b070c
PMID19330887
OpenAlexW2009588154
LanguageEN
Citations received2
References cited38

BACKGROUND: Simple hypertension outcome measures may not indicate which patients receive poor care. This could be problematic as incentives increase. OBJECTIVE: Compare measured quality using simple outcome measures to more sophisticated measures utilizing data available within an electronic health record. DESIGN: Cross-sectional study. SUBJECTS: A total of 5905 hypertensive adults with 3 or more clinic visits between July 1, 2005 and December 31, 2006 at an internal medicine clinic. MEASURES: We measured simple control as the proportion of diagnosed hypertension patients with their last blood pressure below goal (<140/90 mm Hg or <130/80 if diabetic). We compared this to sequentially more complex measures. RESULTS: Among nondiabetic patients, baseline measurement of control was 58.1% [95% confidence interval (CI), 56.5-59.6]. Counting patients as having adequate care whose last or mean blood pressure was at or below goal raised performance to 75.4%. Accounting for patients prescribed aggressive treatment raised it to 82.5%. Accounting for low diastolic blood pressure raised it to 83.6%. Including patients with undiagnosed hypertension lowered it to 80.5%. For diabetes patients, baseline measurement of control was 29.9% (95% CI, 27.6-32.3) and changed to 46.4%, 72.8%, 76.7%, and 73.6%, respectively. CONCLUSIONS: It is possible to use electronic health record data to devise hypertension measures that may better reflect who has actionable uncontrolled blood pressure, do not penalize clinicians treating resistant hypertension patients, reduce the encouragement of potentially unsafe practices, and identify patients possibly receiving poor care with no hypertension diagnosis. This could improve the detection of true quality problems and remove incentives to over treat or stop caring for patients with resistant hypertension

Health care · Health records · Political science · Quality (philosophy) · Blood Pressure and Hypertension Studies · Electronic Health Records Systems · Medicine · Primary Care and Health Outcomes

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