{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T07:07:00Z","timestamp":1793862420408,"version":"4.6.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"40","license":[{"start":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T00:00:00Z","timestamp":1693440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100004325","name":"AstraZeneca","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004325","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,21]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background and Aims<\/jats:title><jats:p>Patients hospitalized for acute heart failure (AHF) continue to be discharged on an inadequate number of guideline-directed medical therapies (GDMT) despite evidence that inpatient initiation is beneficial. This study aimed to examine whether a tailored electronic health record (EHR) alert increased rates of GDMT prescription at discharge in eligible patients hospitalized for AHF.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Pragmatic trial of messaging to providers about treatment of acute heart failure (PROMPT-AHF) was a pragmatic, multicenter, EHR-based, and randomized clinical trial. Patients were automatically enrolled 48 h after admission if they met pre-specified criteria for an AHF hospitalization. Providers of patients in the intervention arm received an alert during order entry with relevant patient characteristics along with individualized GDMT recommendations with links to an order set. The primary outcome was an increase in the number of GDMT prescriptions at discharge.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Thousand and twelve patients were enrolled between May 2021 and November 2022. The median age was 74 years; 26% were female, and 24% were Black. At the time of the alert, 85% of patients were on \u03b2-blockers, 55% on angiotensin-converting enzyme inhibitor\/angiotensin receptor blocker\/angiotensin receptor-neprilysin inhibitor, 20% on mineralocorticoid receptor antagonist (MRA) and 17% on sodium-glucose cotransporter 2 inhibitor. The primary outcome occurred in 34% of both the alert and no alert groups [adjusted risk ratio (RR): 0.95 (0.81, 1.12), P = .99]. Patients randomized to the alert arm were more likely to have an increase in MRA [adjusted RR: 1.54 (1.10, 2.16), P = .01]. At the time of discharge, 11.2% of patients were on all four pillars of GDMT.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>A real-time, targeted, and tailored EHR-based alert system for AHF did not lead to a higher number of overall GDMT prescriptions at discharge. Further refinement and improvement of such alerts and changes to clinician incentives are needed to overcome barriers to the implementation of GDMT during hospitalizations for AHF. GDMT remains suboptimal in this setting, with only one in nine patients being discharged on a comprehensive evidence-based regimen for heart failure.<\/jats:p><\/jats:sec>","DOI":"10.1093\/eurheartj\/ehad512","type":"journal-article","created":{"date-parts":[[2023,8,31]],"date-time":"2023-08-31T08:41:17Z","timestamp":1693471277000},"page":"4233-4242","source":"Crossref","is-referenced-by-count":39,"title":["Electronic health record alerts for management of heart failure with reduced ejection fraction in hospitalized patients: the PROMPT-AHF trial"],"prefix":"10.1093","volume":"44","author":[{"given":"Lama","family":"Ghazi","sequence":"first","affiliation":[{"name":"School of Public Health, University of Alabama at Birmingham , Birmingham, AL , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Yamamoto","sequence":"additional","affiliation":[{"name":"Clinical and Translational Research Accelerator, Yale University , New Haven, CT, 06510 , 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