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Validation of a Health System Measure to Capture Intensive Medication Treatment of Hypertension in the Veterans
Lillian Min1,2,3,4, Jin-Kyung Ha2, Timothy P Hofer3,4,5
1VA Ann Arbor Medical Center, Geriatric Research, Education, and Clinical Center, Ann Arbor, Michigan.
Insights
An electronic health record algorithm accurately identifies intensive hypertension care (IHC) using medication and blood pressure data. This method reliably estimates IHC from routine health system data.
Area of Science:
- Geriatric Medicine
- Cardiology
- Health Informatics
Background:
- Blood pressure (BP) targets are key for high-quality hypertension care, but do not fully reflect treatment intensity, especially in older adults.
- Managing pharmacological treatment intensity is crucial for older patients with hypertension.
Purpose of the Study:
- To develop and validate an electronic health record (EHR) data-only algorithm to identify intensive hypertension care (IHC).
- IHC is defined as 3 or more BP medications and BP < 120 mm Hg.
- To identify conditions associated with greater IHC or algorithm inaccuracies.
Main Methods:
- A cross-sectional study using EHR data from 319 older adults (≥65 years) in the Veterans Health Administration (VHA).
- Compared an EHR-only algorithm using pharmacy and BP data against a reference standard of clinical IHC derived from free-text notes.
- Calculated correlation, sensitivity, and specificity of the algorithm; examined contributing conditions.
Main Results:
- The EHR algorithm for medication count strongly correlated with the reference standard (r=0.84).
- Sensitivity for detecting clinical IHC was 92.2%, and specificity was 97.2%.
- Only 2.1% of visits were false positives; 1.5% involved IHC with contributing conditions.
Conclusions:
- Health system data can reliably estimate intensive hypertension care (IHC).
- The developed algorithm accurately captures IHC from routinely collected EHR data.
- This approach supports quality assessment and management of hypertension in older populations.
Importance:
Blood pressure (BP) targets are the main measure of high-quality hypertension care in health systems. However, BP alone does not reflect intensity of pharmacological treatment, which should be carefully managed in older patients.
Objectives:
To develop and validate an electronic health record (EHR) data-only algorithm using pharmacy and BP data to capture intensive hypertension care (IHC), defined as 3 or more BP medications and BP less than 120 mm Hg, and to identify conditions associated with greater IHC, either through greater algorithm false-positive IHC, or by contributing clinically to delivering more IHC.
Design, Setting, And Participants:
This cross-sectional study was conducted among 319 randomly selected patients aged 65 years or older receiving IHC from the Veterans Health Administration (VHA) from July 1, 2011, to June 30, 2013. Data were collected from a total of 3625 primary care visits. Data were analyzed from January 2017 to March 2020.
Exposures:
Calibration and measurement of the algorithm for IHC (algorithm IHC).
Main Outcomes And Measures:
For each primary care visit, the reference standard, clinical IHC, was determined by detailed review of free-text clinical notes. The correlation in BP medication count between the EHR-only algorithm vs the reference standard and the sensitivity and specificity of the algorithm IHC were calculated. In addition, presence vs absence of contributing conditions acting in combination with hypertension management were measured to examine incidence of IHC associated with contributing conditions, including an acute condition that lowered BP (eg, dehydration), another condition requiring a BP target lower than the standard 140 mm Hg (eg, diabetes), or the patient needing a BP-lowering medication for a nonhypertension condition (eg, β-blocker for atrial fibrillation) resulting in low BP.
Results:
Among 319 patients with 3625 visits (mean [SD] age, 75.6 [7.2] years; 3592 [99.1%] men), 911 visits (25.1%) had clinical IHC by the reference standard. The algorithm for determining medication count was highly correlated with the reference standard (r = 0.84). Sensitivity of detecting clinical IHC was 92.2% (95% CI, 89.3%-95.1%), and specificity was 97.2% (95% CI, 96.1%-98.3%), suggesting that clinical IHC can be identified from routinely collected data. Only 75 visits (2.1%) were algorithm IHC false positives, 55 visits (1.5%) involved IHC with contributing conditions, and 125 visits (3.5%) involved either false-positive or IHC with contributing conditions. Among select contributing conditions, congestive heart failure (37 patients [5.2%]) was most associated with a prespecified combined false-positive or IHC with contributing conditions rate higher than 5%.
Conclusions And Relevance:
These findings suggest that health system data can be used reliably to estimate IHC.
