Evidence map›Paper›PMID 40912680›Full record

ArticleApplied clinical informatics2025

"I worry we'll blow right by it:" Barriers to Uptake of the STRATIFY-CDS for Acute Heart Failure.

Matthew A Christensen, Carrie Reale, Shilo Anders, Tim Coffman, Hala Alaw, Janos L Mathe, Dan Albert, Anna Sachs, Allison B McCoy, Dandan Liu and 3 more

Abstract read
In one paragraph

Article in Applied clinical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Matthew A ChristensenDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Carrie RealeDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Shilo AndersDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Tim CoffmanDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Hala AlawHealth Information Technology and Services, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Janos L MatheHealth Information Technology and Services, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Dan AlbertHealth Information Technology and Services, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Anna SachsCenter for Health Services Research, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Allison B McCoyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Dandan LiuDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Alan B StorrowDepartment of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Sunil KripalaniDepartment of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States.
Laurie L NovakDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Funding

Tailored dissemination and implementation of emergency care clinical decision support to improve emergency department dispositionR01HL157596 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KRIPALANI, SUNIL, LIU, DANDAN · 2021 to 2024
$3.0M
Interdisciplinary Training in Injury and Critical IllnessT32GM135094 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI PATEL, MAYUR B · 2021 to 2025
$967k
NHLBI NIH HHS R01 HL157596NIGMS NIH HHS T32 GM135094
6 · The paper itself

Abstract

Clinical decision support (CDS) tools in electronic health records (EHRs) often face low uptake due to limited usability, workflow integration, and other implementation issues. We recently designed and implemented the STRATIFY-CDS tool, which calculates a validated risk-prediction model and recommends disposition for emergency department (ED) patients with acute heart failure. Despite applying human-centered design and implementation science strategies, initial utilization in the first 3 months of the STRATIFY-CDS tool was just 3%.To identify usability issues and contextual barriers to uptake of STRATIFY-CDS tool among ED clinicians.We performed an exploratory qualitative and simulation study with ED clinicians at Vanderbilt University Medical Center who had used the STRATIFY-CDS tool at least once. Semi-structured interviews with interactive simulation (summative usability) were conducted via videoconference. Two authors performed thematic analysis informed by the Technology Acceptance Model.Of 13 invited ED clinicians, 10 participated (7 attending and 3 resident physicians) with 1 to 11 prior tool uses. Although the main user interface had high perceived usability, participants struggled to find the launch button. The

Indexed as

Decision Support Systems, ClinicalHeart FailureAcute DiseaseElectronic Health RecordsEmergency Service, HospitalHumans

Identifiers

PMID40912680
PMCPMC12413277

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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.