Evidence map›Paper›PMID 40206997›Full record

ArticleMayo Clinic proceedings. Digital health2025

Development of a Human Factors-Based Guideline to Support the Design, Evaluation, and Continuous Improvement of Clinical Decision Support.

Selvana Awad, Thomas Loveday, Richard Lau, Melissa T Baysari

Abstract read
In one paragraph

Article in Mayo Clinic proceedings. Digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

4 authors.

Selvana AwadBiomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Australia.
Thomas LovedayeHealth NSW, New South Wales, Australia.
Richard LaueHealth NSW, New South Wales, Australia.
Melissa T BaysariBiomedical Informatics and Digital Health, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop a vendor-agnostic, human factors (HF)-based guideline to guide the design, evaluation, and continuous improvement of clinical decision support (CDS). Participants and Methods: The study used a 2-phased iterative approach between June 2022 and June 2024. Phase 1 involved a search for relevant industry standards and literature and consultation with multidisciplinary subject matter experts. Phase 2 involved a workshop with 30 health care and academic stakeholders to evaluate face validity and perceived usefulness of the initial section of the guideline. Participants were asked if the guideline met their expectations, to report on usefulness and ease of use and to suggest areas for improvement. Results: Phase 1 resulted in a compilation of accessible, best practice, and context-appropriate HF guidance for CDS design and optimization. The guideline supports users in determining whether use of CDS is appropriate, and if yes, CDS options and design guidance. During phase 2, the guideline addressed 15 of participants' 19 expectations for a CDS guideline. Participants said the guideline was helpful, comprehensive, easy to use, and provided step-by-step guidance, boundaries, and transparency around CDS decisions. Participants recommended strengthening guidance around the need to understand system capabilities and the technical burden or complexity of CDS, and further guidance on how to approach CDS optimization using the guideline. Conclusion: The 2-phased iterative development and feedback process resulted in the development of an HF-informed guideline to provide consolidated, accessible, and current best practice guidance on the appropriateness of CDS and CDS options, as well as designing, evaluating, and continuously improving CDS. Future work will evaluate the impact and implementation of the guideline in real-world settings.

Identifiers

PMID40206997
PMCPMC11975816

What OpenQuestion holds

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Registered trials

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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.