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Published in: BMC Medical Informatics and Decision Making 1/2009

Open Access 01-12-2009 | Research article

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

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

Published in: BMC Medical Informatics and Decision Making | Issue 1/2009

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Abstract

Background

Computerized 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.

Methods

A 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.

Results

Of 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.

Conclusion

While 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.
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Metadata
Title
Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
Authors
Brent Mollon
Jaron JR Chong
Anne M Holbrook
Melani Sung
Lehana Thabane
Gary Foster
Publication date
01-12-2009
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2009
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/1472-6947-9-11

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