Evidence map›Paper›PMID 19210782›Full record

SynthesisBMC medical informatics and decision making2009

Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials.

Brent Mollon, Jaron Chong, Anne M Holbrook, Melani Sung, Lehana Thabane, Gary Foster

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

Synthesis in BMC medical informatics and decision making, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 18 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 18 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.

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

57 citing papers in PubMed, 18 syntheses or guidelines pooled it.

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  3. Effects of health information technology on patient outcomes: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2016
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  9. Computerized advice on drug dosage to improve prescribing practice.The Cochrane database of systematic reviews · 2013
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  15. Guideline
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  18. Computerized clinical decision support for prescribing: provision does not guarantee uptake.Journal of the American Medical Informatics Association : JAMIA
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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.

Brent MollonThe Centre for Evaluation of Medicines, McMaster University, Hamilton, Ontario, Canada. brent.mollon@learnlink.mcmaster.ca
Jaron Chong
Anne M Holbrook
Melani Sung
Lehana Thabane
Gary Foster

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputerized decision support systems (CDSS) are believed to have the potential to improve the quality of health care delivery, although results from high quality studies have been mixed. We conducted a systematic review to evaluate whether certain features of prescribing decision support systems (RxCDSS) predict successful implementation, change in provider behaviour, and change in patient outcomes.

methodsA literature search of Medline, EMBASE, CINAHL and INSPEC databases (earliest entry to June 2008) was conducted to identify randomized controlled trials involving RxCDSS. Each citation was independently assessed by two reviewers for outcomes and 28 predefined system features. Statistical analysis of associations between system features and success of outcomes was planned.

resultsOf 4534 citations returned by the search, 41 met the inclusion criteria. Of these, 37 reported successful system implementations, 25 reported success at changing health care provider behaviour, and 5 noted improvements in patient outcomes. A mean of 17 features per study were mentioned. The statistical analysis could not be completed due primarily to the small number of studies and lack of diversity of outcomes. Descriptive analysis did not confirm any feature to be more prevalent in successful trials relative to unsuccessful ones for implementation, provider behaviour or patient outcomes.

conclusionWhile RxCDSSs have the potential to change health care provider behaviour, very few high quality studies show improvement in patient outcomes. Furthermore, the features of the RxCDSS associated with success (or failure) are poorly described, thus making it difficult for system design and implementation to improve.

Indexed as

Decision Support Systems, ClinicalDrug Therapy, Computer-AssistedAttitude of Health PersonnelHumansMedical Order Entry SystemsQuality Assurance, Health CareRandomized Controlled Trials as Topic

Identifiers

PMID19210782
PMCPMC2667396

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.