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Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake
BACKGROUND: Computerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908582/ https://www.ncbi.nlm.nih.gov/pubmed/35272667 http://dx.doi.org/10.1186/s13012-022-01199-3 |
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author | Kouri, Andrew Yamada, Janet Lam Shin Cheung, Jeffrey Van de Velde, Stijn Gupta, Samir |
author_facet | Kouri, Andrew Yamada, Janet Lam Shin Cheung, Jeffrey Van de Velde, Stijn Gupta, Samir |
author_sort | Kouri, Andrew |
collection | PubMed |
description | BACKGROUND: Computerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective of this systematic review and meta-regression was to determine reported CDSS uptake and identify which CDSS features may influence uptake. METHODS: Medline, Embase, CINAHL, and the Cochrane Database of Controlled Trials were searched from January 2000 to August 2020. Randomized, non-randomized, and quasi-experimental trials reporting CDSS uptake in any patient population or setting were included. The main outcome extracted was CDSS uptake, reported as a raw proportion, and representing the number of times the CDSS was used or accessed over the total number of times it could have been interacted with. We also extracted context, content, system, and implementation features that might influence uptake, for each CDSS. Overall weighted uptake was calculated using random-effects meta-analysis and determinants of uptake were investigated using multivariable meta-regression. RESULTS: Among 7995 citations screened, 55 studies involving 373,608 patients and 3607 providers met full inclusion criteria. Meta-analysis revealed that overall CDSS uptake was 34.2% (95% CI 23.2 to 47.1%). Uptake was only reported in 12.4% of studies that otherwise met inclusion criteria. Multivariable meta-regression revealed the following factors significantly associated with uptake: (1) formally evaluating the availability and quality of the patient data needed to inform CDSS advice; and (2) identifying and addressing other barriers to the behaviour change targeted by the CDSS. CONCLUSIONS AND RELEVANCE: System uptake was seldom reported in CDSS trials. When reported, uptake was low. This represents a major and potentially modifiable barrier to overall CDSS effectiveness. We found that features relating to CDSS context and implementation strategy best predicted uptake. Future studies should measure the impact of addressing these features as part of the CDSS implementation strategy. Uptake reporting must also become standard in future studies reporting CDSS intervention effects. REGISTRATION: Pre-registered on PROSPERO, CRD42018092337 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13012-022-01199-3. |
format | Online Article Text |
id | pubmed-8908582 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-89085822022-03-18 Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake Kouri, Andrew Yamada, Janet Lam Shin Cheung, Jeffrey Van de Velde, Stijn Gupta, Samir Implement Sci Systematic Review BACKGROUND: Computerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective of this systematic review and meta-regression was to determine reported CDSS uptake and identify which CDSS features may influence uptake. METHODS: Medline, Embase, CINAHL, and the Cochrane Database of Controlled Trials were searched from January 2000 to August 2020. Randomized, non-randomized, and quasi-experimental trials reporting CDSS uptake in any patient population or setting were included. The main outcome extracted was CDSS uptake, reported as a raw proportion, and representing the number of times the CDSS was used or accessed over the total number of times it could have been interacted with. We also extracted context, content, system, and implementation features that might influence uptake, for each CDSS. Overall weighted uptake was calculated using random-effects meta-analysis and determinants of uptake were investigated using multivariable meta-regression. RESULTS: Among 7995 citations screened, 55 studies involving 373,608 patients and 3607 providers met full inclusion criteria. Meta-analysis revealed that overall CDSS uptake was 34.2% (95% CI 23.2 to 47.1%). Uptake was only reported in 12.4% of studies that otherwise met inclusion criteria. Multivariable meta-regression revealed the following factors significantly associated with uptake: (1) formally evaluating the availability and quality of the patient data needed to inform CDSS advice; and (2) identifying and addressing other barriers to the behaviour change targeted by the CDSS. CONCLUSIONS AND RELEVANCE: System uptake was seldom reported in CDSS trials. When reported, uptake was low. This represents a major and potentially modifiable barrier to overall CDSS effectiveness. We found that features relating to CDSS context and implementation strategy best predicted uptake. Future studies should measure the impact of addressing these features as part of the CDSS implementation strategy. Uptake reporting must also become standard in future studies reporting CDSS intervention effects. REGISTRATION: Pre-registered on PROSPERO, CRD42018092337 SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13012-022-01199-3. BioMed Central 2022-03-10 /pmc/articles/PMC8908582/ /pubmed/35272667 http://dx.doi.org/10.1186/s13012-022-01199-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Systematic Review Kouri, Andrew Yamada, Janet Lam Shin Cheung, Jeffrey Van de Velde, Stijn Gupta, Samir Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake |
title | Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake |
title_full | Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake |
title_fullStr | Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake |
title_full_unstemmed | Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake |
title_short | Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake |
title_sort | do providers use computerized clinical decision support systems? a systematic review and meta-regression of clinical decision support uptake |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8908582/ https://www.ncbi.nlm.nih.gov/pubmed/35272667 http://dx.doi.org/10.1186/s13012-022-01199-3 |
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