Evidence map›Paper›PMID 32047862›Full record

ReviewNPJ digital medicine2020

An overview of clinical decision support systems: benefits, risks, and strategies for success.

Reed T Sutton, David Pincock, Daniel C Baumgart, Daniel C Sadowski, Richard N Fedorak, Karen I Kroeker

2 registry-linked trialsAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 1,213 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,213citing papers in PubMed, 5 pooled it
–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.

NCT06693778 active not recruitingnot on this mapstarted 2023, after this paper: background citation

Utilizing Electronic Clinical Decision Support to Enhance mTBI Care at the Primary Care Point of Entry

TypeobservationalSponsorChildren's Hospital of PhiladelphiaRan2023 to 2027Enrolled3,000ConditionsBrain Concussion, Mild Traumatic Brain InjuryArmselectronic Clinical Decision Support tool for risk stratification of pediatric patients with mTBI
NCT07398235 completednot on this mapstarted 2026, after this paper: background citation

A Qualitative Study to Explore the Barriers to Adoption of Clinical Decision Support Systems

Typeobservational_patient_registrySponsorMedway NHS Foundation TrustRan2026 to 2026Enrolled18ConditionsClinical Decision Support System (CDSS)ArmsSemi-structured interview
3 · Its place in the literature

Who cites it

1,213 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  4. Major Adverse Cardiac Events with Ondansetron: A Systematic Review.Clinical pharmacology and therapeutics · 2026
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1,153 more citing papers are in PubMed but not listed here.

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.

Reed T Sutton1Department of Medicine, Division of Gastroenterology, University of Alberta, Edmonton, Canada.ORCID 0000-0002-3009-1914
David Pincock2Chief Medical Information Office, Alberta Health Services, Edmonton, Canada.
Daniel C Baumgart1Department of Medicine, Division of Gastroenterology, University of Alberta, Edmonton, Canada.
Daniel C Sadowski1Department of Medicine, Division of Gastroenterology, University of Alberta, Edmonton, Canada.
Richard N Fedorak1Department of Medicine, Division of Gastroenterology, University of Alberta, Edmonton, Canada.
Karen I Kroeker1Department of Medicine, Division of Gastroenterology, University of Alberta, Edmonton, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computerized clinical decision support systems, or CDSS, represent a paradigm shift in healthcare today. CDSS are used to augment clinicians in their complex decision-making processes. Since their first use in the 1980s, CDSS have seen a rapid evolution. They are now commonly administered through electronic medical records and other computerized clinical workflows, which has been facilitated by increasing global adoption of electronic medical records with advanced capabilities. Despite these advances, there remain unknowns regarding the effect CDSS have on the providers who use them, patient outcomes, and costs. There have been numerous published examples in the past decade(s) of CDSS success stories, but notable setbacks have also shown us that CDSS are not without risks. In this paper, we provide a state-of-the-art overview on the use of clinical decision support systems in medicine, including the different types, current use cases with proven efficacy, common pitfalls, and potential harms. We conclude with evidence-based recommendations for minimizing risk in CDSS design, implementation, evaluation, and maintenance.

Indexed as

DiagnosisDrug regulationHealth servicesMedical imaging

Identifiers

PMID32047862
PMCPMC7005290

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.