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BMC Med Inform Decis Mak. 2009 Feb 11;9:11. doi: 10.1186/1472-6947-9-11.

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

Author information

  • 1The Centre for Evaluation of Medicines, McMaster University, Hamilton, Ontario, Canada. brent.mollon@learnlink.mcmaster.ca

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.

PMID:
19210782
[PubMed - indexed for MEDLINE]
PMCID:
PMC2667396
Free PMC Article
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