Evidence map›Paper›PMID 41533922›Full record

ReviewCritical pathways in cardiology2026

Considerations for the Adoption of Digital Algorithms and Cardiovascular Decision-Support Tools in Clinical Practice.

Christopher W Baugh, C Michael Gibson, Evangelos Giannitsis, David A Morrow, James L Januzzi, Cynthia Papendick, Hans-Peter Brunner-La Rocca, Lori B Daniels, Helena Palau, Ludovica Visciola and 1 more

Abstract readReview
In one paragraph

Review in Critical pathways in cardiology, 2026. 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

11 authors.

Christopher W BaughFrom the Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard University, Boston, MA.
C Michael GibsonDepartment of Medicine, Beth Israel Deaconess Medical Center, Baim Institute for Clinical Research, Harvard Medical School, Harvard University, Boston, MA.
Evangelos GiannitsisDepartment of Internal Medicine III, Cardiology, University Hospital of Heidelberg, Heidelberg, Germany.
David A MorrowCardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard University, Boston, MA.
James L JanuzziDepartment of Medicine, Division of Cardiology, Massachusetts General Hospital, Baim Institute for Clinical Research, Harvard Medical School, Harvard University, Boston, MA.
Cynthia PapendickDepartment of Health, Central Adelaide Local Health Network, University of Adelaide School of Medicine, Adelaide, South Australia, Australia.
Hans-Peter Brunner-La RoccaDepartment of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht, the Netherlands.
Lori B DanielsDepartment of Medicine, Division of Cardiovascular Medicine, University of California San Diego, La Jolla, CA.
Helena PalauDigital Technology & Healthcare Information, Healthcare Expertise, Clinical Value and Validation, Roche Diagnostics S.L., Barcelona, Spain.
Ludovica VisciolaMedical Affairs Lead, Digital Solutions, Clinical Development and Medical Affairs (CDMA), Roche Diagnostics Solutions, Roche Diagnostics, Rotkreuz, Switzerland.
Martin ThanDepartment of Medicine, University of Otago Christchurch and Emergency Department, Christchurch Hospital, Christchurch, New Zealand.

Funding

Roche Diagnostics GmbH (Penzberg, Germany)
6 · The paper itself

Abstract

Early detection of cardiovascular disease and implementation of evidence-based treatments can reduce cardiovascular morbidity and mortality. Medical algorithms and decision-making tools provide a compelling option for screening, risk prediction, and treatment management. Such digital tools have the potential to aid both healthcare professionals and patients, providing support to decrease unwarranted diagnostic and treatment variability while guiding personalized care, with the overall objective of improving clinical outcomes. However, incorporating digital tools in healthcare settings is challenging, and evidence the required to support their adoption and understand the limitations can be lacking. A multinational panel of expert cardiologists and emergency physicians across North America, Europe, and Oceania gathered to deliberate on the current landscape of digital tools and medical algorithms, drawing on prior clinical experiences and knowledge of country-specific regulations. In this viewpoint, the evidence to support and guide the adoption of digital tools in cardiovascular clinical practice and the necessary components for successful integration into clinical workflows were discussed. Digital tools must be developed with the needs of the healthcare professionals, other relevant stakeholders (eg, administration personnel), and patients in mind to give them the best chance of widespread adoption. Academia, industry, and regulatory bodies should work together to cultivate and accelerate the implementation of digital tools in healthcare. The considerations discussed here may help decision makers to determine if a digital tool has the components necessary to integrate into the clinical workflow successfully.

Indexed as

AlgorithmsCardiovascular DiseasesDecision Support Systems, ClinicalDigital HealthHumansartificial intelligencedecision-making support tooldigital toolsmedical algorithm

Identifiers

PMID41533922
PMCPMC12919653

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.