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Improving hypertension quality measurement using electronic health records
Stephen D Persell1, Abel N Kho, Jason A Thompson
1Division of General Internal Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA. spersell@nmff.org
Insights
Sophisticated electronic health record measures better identify patients with uncontrolled hypertension and potential care gaps than simple metrics. This improves quality detection and avoids penalizing clinicians for complex cases.
Area of Science:
- Clinical Quality Measurement
- Health Informatics
- Hypertension Management
Background:
- Simple hypertension outcome measures may not accurately reflect patient care quality.
- Increasing incentives based on simple metrics can be problematic.
Purpose of the Study:
- Compare quality measurement using simple hypertension outcomes versus sophisticated measures.
- Utilize data from electronic health records for enhanced quality assessment.
Main Methods:
- Cross-sectional study of 5905 hypertensive adults.
- Compared simple blood pressure control rates to complex measures using EHR data.
- Defined control as blood pressure below goal (<140/90 mm Hg or <130/80 if diabetic).
Main Results:
- For non-diabetic patients, sophisticated measures increased performance from 58.1% to 83.6%.
- For diabetic patients, performance improved from 29.9% to 76.7% with complex measures.
- Advanced metrics better accounted for treatment aggressiveness and patient complexity.
Conclusions:
- Electronic health record data can create better hypertension quality measures.
- Improved measures can identify actionable uncontrolled blood pressure and potential poor care.
- These measures avoid penalizing clinicians for resistant hypertension and reduce incentives for unsafe practices.
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.
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Monitoring Both Arms:
Monitoring BP in both arms during the initial assessment is advisable, as the systolic value may differ by five to ten mm Hg between arms. For subsequent BP assessments, use the arm with the higher reading.