Evidence map›Paper›PMID 34927003›Full record

ArticleJAMIA open2021

A scoping review of knowledge authoring tools used for developing computerized clinical decision support systems.

Sujith Surendran Nair, Chenyu Li, Ritu Doijad, Paul Nagy, Harold Lehmann, Hadi Kharrazi

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Sujith Surendran NairDivision of General Internal Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0002-0262-7646
Chenyu LiDivision of General Internal Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Ritu DoijadDivision of General Internal Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Paul NagyDivision of General Internal Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Harold LehmannDivision of General Internal Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Hadi KharraziDivision of General Internal Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveClinical Knowledge Authoring Tools (CKATs) are integral to the computerized Clinical Decision Support (CDS) development life cycle. CKATs enable authors to generate accurate, complete, and reliable digital knowledge artifacts in a relatively efficient and affordable manner. This scoping review aims to compare knowledge authoring tools and derive the common features of CKATs. MATERIALS AND

methodsWe performed a keyword-based literature search, followed by a snowball search, to identify peer-reviewed publications describing the development or use of CKATs. We used PubMed and Embase search engines to perform the initial search (

resultsAmong the identified CKATs, 55% use an open source platform, 70% provide an application programming interface for CDS system integration, and 79% provide features to validate/test the knowledge. The majority of the reviewed CKATs describe the flow of information, offer a graphical user interface for knowledge authors, and provide intellisense coding features (94%, 97%, and 97%, respectively). The composed list of criteria for CKAT included topics such as simulating the clinical setting, validating the knowledge, standardized clinical models and vocabulary, and domain independence. None of the reviewed CKATs met all common criteria.

conclusionOur scoping review highlights the key specifications for a CKAT. The CKAT specification proposed in this review can guide CDS authors in developing more targeted CKATs.

Indexed as

Clinical Decision SupportClinical Knowledge Authoring Toolsdecision support rule authoringknowledge engineeringscoping review of literature

Identifiers

PMID34927003
PMCPMC8677433

What OpenQuestion holds

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LicenceCC BY-NC
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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.