Evidence map›Paper›PMID 42261960›Full record

ArticleJournal of the American Heart Association2026

Barriers to Optimization of Medical Therapy and the Role of Checklist-Based Decision Support in Heart Failure.

Brett M Montelaro, Edward Woods, Candace D Speight, Eisha P Udeshi, Andrea R Mitchell, Michael A Burke, Jamie Diamond, Alanna A Morris, Engels N Obi, Andra S Stevenson and 2 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Brett M MontelaroDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.ORCID 0009-0005-5359-1507
Edward WoodsDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.
Candace D SpeightDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.
Eisha P UdeshiDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.ORCID 0009-0004-1730-0402
Andrea R MitchellDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.
Michael A BurkeDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.ORCID 0000-0003-1491-1131
Jamie DiamondDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.ORCID 0000-0002-4104-9965
Alanna A MorrisDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.ORCID 0000-0002-8033-3707
Engels N ObiMerck & Co., Inc. Rahway NJ USA.ORCID 0000-0002-1807-3465
Andra S StevensonMerck & Co., Inc. Rahway NJ USA.
Molly TiedekenMerck & Co., Inc. Rahway NJ USA.
Neal W DickertDepartment of Medicine, Division of Cardiology Emory University School of Medicine Atlanta GA USA.ORCID 0000-0003-4415-3861

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGuideline-directed medical therapy (GDMT) reduces morbidity and mortality in heart failure with reduced ejection fraction, yet it remains underused. Patient-activation interventions, including checklist-based decision support, have shown improvement in GDMT optimization, and iterative refinement of such tools may enhance their impact. We analyzed recorded clinician-patient encounters, in which a checklist-based activation tool was used, to identify barriers to GDMT optimization and opportunities to enhance decision support.

methodsThis was a secondary analysis of transcript data from the POCKET-COST-HF (Integrating Cost Into Shared Decision-Making for Heart Failure With Reduced Ejection Fraction) trial, which implemented a checklist-based tool focused on prescription price transparency. Patients and clinicians at 2 academic health centers received adapted versions of the EPIC-HF (Electronically Delivered Patient-Activation Tool for Intensification of Medications for Chronic Heart Failure With Reduced Ejection Fraction) checklist outlining approved medications and target doses for HFrEF. Encounters were audio recorded and transcribed and underwent content analysis to identify barriers and opportunities for checklist improvement.

resultsEncounters between 247 patients with heart failure with reduced ejection fraction (mean age 62.9, 29.5% female, 26.3% Black) and 39 clinicians were included. Baseline GDMT use was high (95% beta blockers, 81% angiotensin-converting enzyme inhibitors/angiotensin receptor blockers/angiotensin receptor-neprilysin inhibitors, 63% mineralocorticoid receptor antagonists, and 43% SGLT2 [sodium-glucose cotransporter 2] inhibitors). The checklist was referenced in 48.6% of encounters, and GDMT optimization discussed in 75.7%. Barriers to optimization were identified in 61.5% of encounters, the most common (74.3%) being medical (eg, hypotension). Nonmedical barriers included medication cost (29.6%) and resistance from patients or clinicians (13.8%), often reflecting clinical inertia or desire to minimize medications.

conclusionsNonmedical barriers to GDMT optimization may be addressed by decision-support tools such as checklists. These data suggest that attention to cost, clinical inertia, and desire to minimize medications should be prioritized in future iterations.

Indexed as

Cardiovascular AgentsChecklistDecision Support TechniquesHeart FailureAgedDecision Making, SharedFemaleGuideline AdherenceHumansMaleMiddle AgedPractice Guidelines as TopicStroke VolumeCardiovascular Agentsdecision‐making, sharedguideline‐directed medical therapyheart failureheart failure with reduced ejection fractionpatient participationqualitative research

Identifiers

PMID42261960
PMCPMC13323806

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.