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

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 suppor...

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Autores principales: Mollon, Brent, Chong, Jaron JR, Holbrook, Anne M, Sung, Melani, Thabane, Lehana, Foster, Gary
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2667396/
https://www.ncbi.nlm.nih.gov/pubmed/19210782
http://dx.doi.org/10.1186/1472-6947-9-11
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author Mollon, Brent
Chong, Jaron JR
Holbrook, Anne M
Sung, Melani
Thabane, Lehana
Foster, Gary
author_facet Mollon, Brent
Chong, Jaron JR
Holbrook, Anne M
Sung, Melani
Thabane, Lehana
Foster, Gary
author_sort Mollon, Brent
collection PubMed
description 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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spelling pubmed-26673962009-04-10 Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials Mollon, Brent Chong, Jaron JR Holbrook, Anne M Sung, Melani Thabane, Lehana Foster, Gary BMC Med Inform Decis Mak Research Article 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. BioMed Central 2009-02-11 /pmc/articles/PMC2667396/ /pubmed/19210782 http://dx.doi.org/10.1186/1472-6947-9-11 Text en Copyright ©2009 Mollon et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mollon, Brent
Chong, Jaron JR
Holbrook, Anne M
Sung, Melani
Thabane, Lehana
Foster, Gary
Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
title Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
title_full Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
title_fullStr Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
title_full_unstemmed Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
title_short Features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
title_sort features predicting the success of computerized decision support for prescribing: a systematic review of randomized controlled trials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2667396/
https://www.ncbi.nlm.nih.gov/pubmed/19210782
http://dx.doi.org/10.1186/1472-6947-9-11
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