Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.

Detalhes bibliográficos
Autor(a) principal: Roshanov, Pavel S.
Data de Publicação: 2013
Outros Autores: Fernandes, Natasha, Wilczynski, Jeff M., Hemens, Brian J., You, John J., Handler, Steven M., Nieuwlaat, Robby, Souza, Nathan Mendes, Beyene, Joseph, Spall, Harriette G. C. Van, Garg, Amit X.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFOP
Texto Completo: http://www.repositorio.ufop.br/handle/123456789/5514
https://doi.org/10.1136/bmj.f657
Resumo: Objectives To identify factors that differentiate between effective and ineffective computerised clinical decision support systems in terms of improvements in the process of care or in patient outcomes. Design Meta-regression analysis of randomised controlled trials. Data sources A database of features and effects of these support systems derived from 162 randomised controlled trials identified in a recent systematic review. Trialists were contacted to confirm the accuracy of data and to help prioritise features for testing. Main outcome measures “Effective” systems were defined as those systems that improved primary (or 50% of secondary) reported outcomes of process of care or patient health. Simple and multiple logistic regression models were used to test characteristics for association with system effectiveness with several sensitivity analyses. Results Systems that presented advice in electronic charting or order entry system interfaces were less likely to be effective (odds ratio 0.37, 95% confidence interval 0.17 to 0.80). Systems more likely to succeed provided advice for patients in addition to practitioners (2.77, 1.07 to 7.17), required practitioners to supply a reason for over-riding advice (11.23, 1.98 to 63.72), or were evaluated by their developers (4.35, 1.66 to 11.44). These findings were robust across different statistical methods, in internal validation, and after adjustment for other potentially important factors. Conclusions We identified several factors that could partially explain why some systems succeed and others fail. Presenting decision support within electronic charting or order entry systems are associated with failure compared with other ways of delivering advice. Odds of success were greater for systems that required practitioners to provide reasons when over-riding advice than for systems that did not. Odds of success were also better for systems that provided advice concurrently to patients and practitioners. Finally, most systems were evaluated by their own developers and such evaluations were more likely to show benefit than those conducted by a third party.
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spelling Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.Objectives To identify factors that differentiate between effective and ineffective computerised clinical decision support systems in terms of improvements in the process of care or in patient outcomes. Design Meta-regression analysis of randomised controlled trials. Data sources A database of features and effects of these support systems derived from 162 randomised controlled trials identified in a recent systematic review. Trialists were contacted to confirm the accuracy of data and to help prioritise features for testing. Main outcome measures “Effective” systems were defined as those systems that improved primary (or 50% of secondary) reported outcomes of process of care or patient health. Simple and multiple logistic regression models were used to test characteristics for association with system effectiveness with several sensitivity analyses. Results Systems that presented advice in electronic charting or order entry system interfaces were less likely to be effective (odds ratio 0.37, 95% confidence interval 0.17 to 0.80). Systems more likely to succeed provided advice for patients in addition to practitioners (2.77, 1.07 to 7.17), required practitioners to supply a reason for over-riding advice (11.23, 1.98 to 63.72), or were evaluated by their developers (4.35, 1.66 to 11.44). These findings were robust across different statistical methods, in internal validation, and after adjustment for other potentially important factors. Conclusions We identified several factors that could partially explain why some systems succeed and others fail. Presenting decision support within electronic charting or order entry systems are associated with failure compared with other ways of delivering advice. Odds of success were greater for systems that required practitioners to provide reasons when over-riding advice than for systems that did not. Odds of success were also better for systems that provided advice concurrently to patients and practitioners. Finally, most systems were evaluated by their own developers and such evaluations were more likely to show benefit than those conducted by a third party.2015-05-26T18:29:15Z2015-05-26T18:29:15Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfROSHANOV, P. S. et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ (International Edition), v. 346, p. f657-f657, 2013. Disponível em: <http://www.bmj.com/content/bmj/346/bmj.f657.full.pdf>. Acesso em: 22 mai. 2015.2044-6055http://www.repositorio.ufop.br/handle/123456789/5514https://doi.org/10.1136/bmj.f657This article is Open Access, published under the terms of a Creative Commons licence. Articles published under CC-BY-NC permit non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. Fonte: o próprio artigo.info:eu-repo/semantics/openAccessRoshanov, Pavel S.Fernandes, NatashaWilczynski, Jeff M.Hemens, Brian J.You, John J.Handler, Steven M.Nieuwlaat, RobbySouza, Nathan MendesBeyene, JosephSpall, Harriette G. C. VanGarg, Amit X.engreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOP2019-07-26T14:58:18Zoai:repositorio.ufop.br:123456789/5514Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332019-07-26T14:58:18Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false
dc.title.none.fl_str_mv Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
title Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
spellingShingle Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
Roshanov, Pavel S.
title_short Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
title_full Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
title_fullStr Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
title_full_unstemmed Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
title_sort Features of effective computerised clinical decision support systems : meta-regression of 162 randomised trials.
author Roshanov, Pavel S.
author_facet Roshanov, Pavel S.
Fernandes, Natasha
Wilczynski, Jeff M.
Hemens, Brian J.
You, John J.
Handler, Steven M.
Nieuwlaat, Robby
Souza, Nathan Mendes
Beyene, Joseph
Spall, Harriette G. C. Van
Garg, Amit X.
author_role author
author2 Fernandes, Natasha
Wilczynski, Jeff M.
Hemens, Brian J.
You, John J.
Handler, Steven M.
Nieuwlaat, Robby
Souza, Nathan Mendes
Beyene, Joseph
Spall, Harriette G. C. Van
Garg, Amit X.
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Roshanov, Pavel S.
Fernandes, Natasha
Wilczynski, Jeff M.
Hemens, Brian J.
You, John J.
Handler, Steven M.
Nieuwlaat, Robby
Souza, Nathan Mendes
Beyene, Joseph
Spall, Harriette G. C. Van
Garg, Amit X.
description Objectives To identify factors that differentiate between effective and ineffective computerised clinical decision support systems in terms of improvements in the process of care or in patient outcomes. Design Meta-regression analysis of randomised controlled trials. Data sources A database of features and effects of these support systems derived from 162 randomised controlled trials identified in a recent systematic review. Trialists were contacted to confirm the accuracy of data and to help prioritise features for testing. Main outcome measures “Effective” systems were defined as those systems that improved primary (or 50% of secondary) reported outcomes of process of care or patient health. Simple and multiple logistic regression models were used to test characteristics for association with system effectiveness with several sensitivity analyses. Results Systems that presented advice in electronic charting or order entry system interfaces were less likely to be effective (odds ratio 0.37, 95% confidence interval 0.17 to 0.80). Systems more likely to succeed provided advice for patients in addition to practitioners (2.77, 1.07 to 7.17), required practitioners to supply a reason for over-riding advice (11.23, 1.98 to 63.72), or were evaluated by their developers (4.35, 1.66 to 11.44). These findings were robust across different statistical methods, in internal validation, and after adjustment for other potentially important factors. Conclusions We identified several factors that could partially explain why some systems succeed and others fail. Presenting decision support within electronic charting or order entry systems are associated with failure compared with other ways of delivering advice. Odds of success were greater for systems that required practitioners to provide reasons when over-riding advice than for systems that did not. Odds of success were also better for systems that provided advice concurrently to patients and practitioners. Finally, most systems were evaluated by their own developers and such evaluations were more likely to show benefit than those conducted by a third party.
publishDate 2013
dc.date.none.fl_str_mv 2013
2015-05-26T18:29:15Z
2015-05-26T18:29:15Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv ROSHANOV, P. S. et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ (International Edition), v. 346, p. f657-f657, 2013. Disponível em: <http://www.bmj.com/content/bmj/346/bmj.f657.full.pdf>. Acesso em: 22 mai. 2015.
2044-6055
http://www.repositorio.ufop.br/handle/123456789/5514
https://doi.org/10.1136/bmj.f657
identifier_str_mv ROSHANOV, P. S. et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ (International Edition), v. 346, p. f657-f657, 2013. Disponível em: <http://www.bmj.com/content/bmj/346/bmj.f657.full.pdf>. Acesso em: 22 mai. 2015.
2044-6055
url http://www.repositorio.ufop.br/handle/123456789/5514
https://doi.org/10.1136/bmj.f657
dc.language.iso.fl_str_mv eng
language eng
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dc.source.none.fl_str_mv reponame:Repositório Institucional da UFOP
instname:Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
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institution UFOP
reponame_str Repositório Institucional da UFOP
collection Repositório Institucional da UFOP
repository.name.fl_str_mv Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)
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