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Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials

OBJECTIVE: To report the improvements achieved with clinical decision support systems and examine the heterogeneity from pooling effects across diverse clinical settings and intervention targets. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline up to August 2019. ELIGIBILITY CRITER...

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Autores principales: Kwan, Janice L, Lo, Lisha, Ferguson, Jacob, Goldberg, Hanna, Diaz-Martinez, Juan Pablo, Tomlinson, George, Grimshaw, Jeremy M, Shojania, Kaveh G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495041/
https://www.ncbi.nlm.nih.gov/pubmed/32943437
http://dx.doi.org/10.1136/bmj.m3216
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author Kwan, Janice L
Lo, Lisha
Ferguson, Jacob
Goldberg, Hanna
Diaz-Martinez, Juan Pablo
Tomlinson, George
Grimshaw, Jeremy M
Shojania, Kaveh G
author_facet Kwan, Janice L
Lo, Lisha
Ferguson, Jacob
Goldberg, Hanna
Diaz-Martinez, Juan Pablo
Tomlinson, George
Grimshaw, Jeremy M
Shojania, Kaveh G
author_sort Kwan, Janice L
collection PubMed
description OBJECTIVE: To report the improvements achieved with clinical decision support systems and examine the heterogeneity from pooling effects across diverse clinical settings and intervention targets. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline up to August 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES AND METHODS: Randomised or quasi-randomised controlled trials reporting absolute improvements in the percentage of patients receiving care recommended by clinical decision support systems. Multilevel meta-analysis accounted for within study clustering. Meta-regression was used to assess the degree to which the features of clinical decision support systems and study characteristics reduced heterogeneity in effect sizes. Where reported, clinical endpoints were also captured. RESULTS: In 108 studies (94 randomised, 14 quasi-randomised), reporting 122 trials that provided analysable data from 1 203 053 patients and 10 790 providers, clinical decision support systems increased the proportion of patients receiving desired care by 5.8% (95% confidence interval 4.0% to 7.6%). This pooled effect exhibited substantial heterogeneity (I(2)=76%), with the top quartile of reported improvements ranging from 10% to 62%. In 30 trials reporting clinical endpoints, clinical decision support systems increased the proportion of patients achieving guideline based targets (eg, blood pressure or lipid control) by a median of 0.3% (interquartile range −0.7% to 1.9%). Two study characteristics (low baseline adherence and paediatric settings) were associated with significantly larger effects. Inclusion of these covariates in the multivariable meta-regression, however, did not reduce heterogeneity. CONCLUSIONS: Most interventions with clinical decision support systems appear to achieve small to moderate improvements in targeted processes of care, a finding confirmed by the small changes in clinical endpoints found in studies that reported them. A minority of studies achieved substantial increases in the delivery of recommended care, but predictors of these more meaningful improvements remain undefined.
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spelling pubmed-74950412020-09-28 Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials Kwan, Janice L Lo, Lisha Ferguson, Jacob Goldberg, Hanna Diaz-Martinez, Juan Pablo Tomlinson, George Grimshaw, Jeremy M Shojania, Kaveh G BMJ Research OBJECTIVE: To report the improvements achieved with clinical decision support systems and examine the heterogeneity from pooling effects across diverse clinical settings and intervention targets. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline up to August 2019. ELIGIBILITY CRITERIA FOR SELECTING STUDIES AND METHODS: Randomised or quasi-randomised controlled trials reporting absolute improvements in the percentage of patients receiving care recommended by clinical decision support systems. Multilevel meta-analysis accounted for within study clustering. Meta-regression was used to assess the degree to which the features of clinical decision support systems and study characteristics reduced heterogeneity in effect sizes. Where reported, clinical endpoints were also captured. RESULTS: In 108 studies (94 randomised, 14 quasi-randomised), reporting 122 trials that provided analysable data from 1 203 053 patients and 10 790 providers, clinical decision support systems increased the proportion of patients receiving desired care by 5.8% (95% confidence interval 4.0% to 7.6%). This pooled effect exhibited substantial heterogeneity (I(2)=76%), with the top quartile of reported improvements ranging from 10% to 62%. In 30 trials reporting clinical endpoints, clinical decision support systems increased the proportion of patients achieving guideline based targets (eg, blood pressure or lipid control) by a median of 0.3% (interquartile range −0.7% to 1.9%). Two study characteristics (low baseline adherence and paediatric settings) were associated with significantly larger effects. Inclusion of these covariates in the multivariable meta-regression, however, did not reduce heterogeneity. CONCLUSIONS: Most interventions with clinical decision support systems appear to achieve small to moderate improvements in targeted processes of care, a finding confirmed by the small changes in clinical endpoints found in studies that reported them. A minority of studies achieved substantial increases in the delivery of recommended care, but predictors of these more meaningful improvements remain undefined. BMJ Publishing Group Ltd. 2020-09-17 /pmc/articles/PMC7495041/ /pubmed/32943437 http://dx.doi.org/10.1136/bmj.m3216 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Research
Kwan, Janice L
Lo, Lisha
Ferguson, Jacob
Goldberg, Hanna
Diaz-Martinez, Juan Pablo
Tomlinson, George
Grimshaw, Jeremy M
Shojania, Kaveh G
Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
title Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
title_full Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
title_fullStr Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
title_full_unstemmed Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
title_short Computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
title_sort computerised clinical decision support systems and absolute improvements in care: meta-analysis of controlled clinical trials
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495041/
https://www.ncbi.nlm.nih.gov/pubmed/32943437
http://dx.doi.org/10.1136/bmj.m3216
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