The impact of a primary aldosteronism predictive model in secondary hypertension decision support.

Autor:	Mack PB; Institute of Quality and Safety, Novant Health, Winston-Salem, NC 27103, United States.; Community Health and Wellness Institute, Novant Health, Winston-Salem, NC 27103, United States., Cole C; Cognitive Computing, Novant Health, Winston-Salem, NC 27103, United States., Lee M; Cognitive Computing, Novant Health, Winston-Salem, NC 27103, United States., Peterson L; Cognitive Computing, Novant Health, Winston-Salem, NC 27103, United States., Lundy M; Cognitive Computing, Novant Health, Winston-Salem, NC 27103, United States., Hegarty K; Cognitive Computing, Novant Health, Winston-Salem, NC 27103, United States.; Institute for Innovation and AI, Novant Health, Winston-Salem, NC 27103, United States., Espinoza W; Cognitive Computing, Novant Health, Winston-Salem, NC 27103, United States.
Jazyk:	angličtina
Zdroj:	JAMIA open [JAMIA Open] 2024 Oct 28; Vol. 7 (4), pp. ooae123. Date of Electronic Publication: 2024 Oct 28 (Print Publication: 2024).
DOI:	10.1093/jamiaopen/ooae123
Abstrakt:	Objectives: To determine whether the addition of a primary aldosteronism (PA) predictive model to a secondary hypertension decision support tool increases screening for PA in a primary care setting. Materials and Methods: One hundred fifty-three primary care clinics were randomized to receive a secondary hypertension decision support tool with or without an integrated predictive model between August 2023 and April 2024. Results: For patients with risk scores in the top 1 percentile, 63/2896 (2.2%) patients where the alert was displayed in model clinics had the order set launched, while 12/1210 (1.0%) in no-model clinics had the order set launched ( P = .014 ). Nineteen of 2896 (0.66%) of these highest risk patients in model clinics had an aldosterone-to-renin ratio (ARR) ordered compared to 0/1210 (0.0%) patients in no-model clinics ( P = .010 ). For patients with scores not in the top 1 percentile, 438/20 493 (2.1%) patients in model clinics had the order set launched compared to 273/17 820 (1.5%) in no-model clinics ( P  < .001). One hundred twenty-four of 20 493 (0.61%) in model clinics had an ARR ordered compared to 34/17 820 (0.19%) in the no-model clinics ( P  < .001). Discussion: The addition of a PA predictive model to secondary hypertension alert displays and triggering criteria along with order set displays and order preselection criteria results in a statistically and clinically significant increase in screening for PA, a condition that clinicians insufficiently screen for currently. Conclusion: Addition of a predictive model for an under-screened condition to traditional clinical decision support may increase screening for these conditions. Competing Interests: None declared. (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)
Databáze:	MEDLINE
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