Evidence map›Paper›PMID 32823309›Full record

ReviewYearbook of medical informatics2020

Pragmatic Considerations on Clinical Decision Support from the 2019 Literature.

C Duclos, J Bouaud, Section Editors for the IMIA Yearbook Section on Decision Support

Abstract readReview
In one paragraph

Review in Yearbook of medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

C DuclosUniversité Sorbonne Paris Nord, Sorbonne Université, INSERM, UMR_S 1142, LIMICS, Paris, France.
J BouaudAP-HP, Delegation for Clinical Research and Innovation, Paris, France.
Section Editors for the IMIA Yearbook Section on Decision Support

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo summarize significant research contributions published in 2019 in the field of computerized clinical decision support and select the best papers for the Decision Support section of the International Medical Informatics Association (IMIA) Yearbook.

methodsTwo bibliographic databases were searched for papers referring to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. From search results, section editors established a list of candidate best papers, which were then peer-reviewed by external reviewers. The IMIA Yearbook editorial committee finally selected the best papers on the basis of all reviews including the section editors' evaluation.

resultsA total of 1,378 articles were retrieved. Fifteen best paper candidates were selected, the reviews of which resulted in the selection of three best papers. One paper reports on a guideline modeling approach based on clinical decision trees, both clinically interpretable and suitable for implementation in CDSSs. In another paper, authors promote the use of extended Timed Transition Diagrams in CDSSs to formalize consistently recurrent medical processes for chronic diseases management. The third paper proposes a conceptual framework and a grid for assessing the performance of predictive tools based on the critical appraisal of published evidence.

conclusionsAs showed by the number and the variety of works related to decision support, research in the field is very active. This year's selection highlighted pragmatic works that promote transparency and trust required by decision support tools.

Indexed as

Decision Support Systems, ClinicalDecision TreesMedical Order Entry SystemsChronic DiseaseHumansPractice Guidelines as Topic

Identifiers

PMID32823309
PMCPMC7442518

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.