Evidence map›Paper›PMID 21824386›Full record

SynthesisImplementation science : IS2011

Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review.

Pavel S Roshanov, Shikha Misra, Hertzel C Gerstein, Amit X Garg, Rolf J Sebaldt, Jean A Mackay, Lorraine Weise-Kelly, Tamara Navarro, Nancy L Wilczynski, R Brian Haynes and 1 more

Open access · goldAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Implementation science : IS, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 12 pooled it
34.9field-weighted citation impact, top 1% 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

112 citing papers in PubMed, 12 syntheses or guidelines pooled it, 244 citations in OpenAlex.

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  12. Computer decision support systems for asthma: a systematic review.NPJ primary care respiratory medicine · 2014
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52 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

11 authors at 4 institutions in 1 country.

Pavel S RoshanovHealth Research Methodology Program, McMaster University, 1280 Main Street West, Hamilton, ON, Canada.
Shikha Misra
Hertzel C Gerstein
Amit X Garg
Rolf J Sebaldt
Jean A Mackay
Lorraine Weise-Kelly
Tamara Navarro
Nancy L Wilczynski
R Brian Haynes
CCDSS Systematic Review Team
McMaster University · CAHamilton Health Sciences · CAUniversity of Toronto · CAWestern University · CA

Funding

Canadian Institutes of Health Research KRS 91791
6 · The paper itself

Abstract

backgroundThe use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations).

methodsWe conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes.

resultsOf 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported.

conclusionsA small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

Indexed as

Cooperative BehaviorAsthmaCardiovascular DiseasesChronic DiseaseDecision MakingDecision Support Systems, ClinicalDiabetes MellitusDyslipidemiasHumansHypertensionMonitoring, PhysiologicPulmonary Disease, Chronic Obstructive

Identifiers

PMID21824386
PMCPMC3170626
OpenAlexW2148482036

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.