Evidence map›Paper›PMID 32313835›Full record

ArticleLearning health systems2020

Building and maintaining trust in clinical decision support: Recommendations from the Patient-Centered CDS Learning Network.

Joshua E Richardson, Blackford Middleton, Jodyn E Platt, Barry H Blumenfeld

Abstract read
In one paragraph

Article in Learning health systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  13. The technical landscape for patient-centered CDS: progress, gaps, and challenges.Journal of the American Medical Informatics Association : JAMIA · 2022
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  15. Preferences of gastric cancer survivors for follow-up care-a multicenter discrete choice experiment study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
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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.

Joshua E RichardsonApplied Health Informatics Program RTI International Chicago Illinois.ORCID https://orcid.org/0000-0003-3066-2673
Blackford MiddletonApervita, Inc Chicago Illinois.
Jodyn E PlattLearning Health Sciences University of Michigan Medical School Ann Arbor Michigan.
Barry H BlumenfeldApplied Health Informatics Program RTI International Waltham MA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowledge artifacts in digital repositories for clinical decision support (CDS) can promote the use of CDS in clinical practice. However, stakeholders will benefit from knowing which they can trust before adopting artifacts from knowledge repositories. We discuss our investigation into trust for knowledge artifacts and repositories by the Patient-Centered CDS Learning Network's Trust Framework Working Group (TFWG). The TFWG identified 12 actors (eg, vendors, clinicians, and policy makers) within a CDS ecosystem who each may play a meaningful role in prioritizing, authoring, implementing, or evaluating CDS and developed 33 recommendations distributed across nine "trust attributes." The trust attributes and recommendations represent a range of considerations such as the "Competency" of knowledge artifact engineers and the "Organizational Capacity" of institutions that develop and implement CDS. The TFWG findings highlight an initial effort to make trust explicit and embedded within CDS knowledge artifacts and repositories and thus more broadly accepted and used.

Indexed as

decision support systems, clinicalhealth policylearning health systemtrust

Identifiers

PMID32313835
PMCPMC7156865

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.