Evidence mapPaperPMID 35818299Full record

SynthesisJournal of the American Medical Informatics Association : JAMIA2022

Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis.

Winnie Chen, Kirsten Howard, Gillian Gorham, Claire Maree O'Bryan, Patrick Coffey, Bhavya Balasubramanya, Asanga Abeyaratne, Alan Cass

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
8.3field-weighted citation impact, top 2% of its field
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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 32 citations in OpenAlex.

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  15. Research synthesis as a strategy for advancing biomedical and health informatics knowledge.Journal of the American Medical Informatics Association : JAMIA · 2022
    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

8 authors at 2 institutions in 1 country.

Winnie ChenMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.ORCID 0000-0002-3473-3080
Kirsten HowardSchool of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.
Gillian GorhamMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.
Claire Maree O'BryanMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.
Patrick CoffeyMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.
Bhavya BalasubramanyaMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.
Asanga AbeyaratneMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.
Alan CassMenzies School of Health Research, Charles Darwin University, Casuarina, Northern Territory, Australia.
Charles Darwin University · AUThe University of Sydney · AU

Funding

Australian Government Research Training Program (RTP) ScholarshipMenzies School of Health Research scholarshipRoyal Australian College of General Practitioners (RACGP)
6 · The paper itself

Abstract

objectivesElectronic health record-based clinical decision support (CDS) has the potential to improve health outcomes. This systematic review investigates the design, effectiveness, and economic outcomes of CDS targeting several common chronic diseases. MATERIAL AND

methodsWe conducted a search in PubMed (Medline), EBSCOHOST (CINAHL, APA PsychInfo, EconLit), and Web of Science. We limited the search to studies from 2011 to 2021. Studies were included if the CDS was electronic health record-based and targeted one or more of the following chronic diseases: cardiovascular disease, diabetes, chronic kidney disease, hypertension, and hypercholesterolemia. Studies with effectiveness or economic outcomes were considered for inclusion, and a meta-analysis was conducted.

resultsThe review included 76 studies with effectiveness outcomes and 9 with economic outcomes. Of the effectiveness studies, 63% described a positive outcome that favored the CDS intervention group. However, meta-analysis demonstrated that effect sizes were heterogenous and small, with limited clinical and statistical significance. Of the economic studies, most full economic evaluations (n = 5) used a modeled analysis approach. Cost-effectiveness of CDS varied widely between studies, with an estimated incremental cost-effectiveness ratio ranging between USD$2192 to USD$151 955 per QALY.

conclusionWe summarize contemporary chronic disease CDS designs and evaluation results. The effectiveness and cost-effectiveness results for CDS interventions are highly heterogeneous, likely due to differences in implementation context and evaluation methodology. Improved quality of reporting, particularly from modeled economic evaluations, would assist decision makers to better interpret and utilize results from these primary research studies. REGISTRATION: PROSPERO (CRD42020203716).

Indexed as

Decision Support Systems, ClinicalChronic DiseaseCost-Benefit AnalysisHumanschronic diseaseclinical decision support systemseconomic evaluationmeta-analysissystematic review

Identifiers

PMID35818299
PMCPMC9471723
OpenAlexW4285030685

What Socratic 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 Socratic graph.