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Published on: September 15, 2017
Active Choice Nudge to Increase Screening for Primary Aldosteronism in At-Risk Patients
Jesse E Passman1,2, Jasmine Hwang1,2, Justin Tang3
1From the Department of Surgery (Passman, Hwang, Wachtel), University of Pennsylvania Health System, Philadelphia, PA.
Background:
Primary aldosteronism (PA) is the most common cause of secondary hypertension, yet screening remains startlingly infrequent. We describe (1) PA screening practices in a large, diverse health system, (2) the development of a computable phenotype for PA screening, and (3) the design and pilot deployment of an electronic health record (EHR)-based active choice nudge to recommend PA screening.
Study Design:
A multidisciplinary team developed a multipronged intervention to improve PA screening informed by guidelines, expertise, and multivariable analyses of factors associated with screening. The intervention included EHR-based tools to automatically identify screen-eligible patients, an active choice nudge recommending screening for these patients, and screening result interpretation. The intervention was piloted across 2 primary care practices for 7 months. Screening frequencies were compared with clinics not receiving the intervention.
Results:
The baseline frequency of screening of eligible patients within 1 year was 1.4%. Higher mean systolic blood pressure (odds ratio [OR] 1.4; p < 0.001), more antihypertensive medications (OR 1.3; p = 0.002), lower minimum serum potassium (OR 2.0; p = 0.001), specialist care (OR 3.0; p < 0.001), and Black race (OR 1.5; p = 0.001) were associated with a higher likelihood of screening. The refined computable phenotype identified a subcohort with a higher frequency of positive screening (8.6% vs 4.1%; p = 0.03). In a pilot study of an active choice nudge, a greater proportion of eligible patients were screened in the intervention clinics (16.4%) than in the nonintervention clinics (1.8%; p < 0.001).
Conclusions:
PA screening rates are low. This pilot study suggests an EHR-based nudge leveraging a precise computable phenotype can dramatically increase appropriate PA screening.
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