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Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial

BACKGROUND: Computerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patien...

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Autores principales: Moja, Lorenzo, Passardi, Alessandro, Capobussi, Matteo, Banzi, Rita, Ruggiero, Francesca, Kwag, Koren, Liberati, Elisa Giulia, Mangia, Massimo, Kunnamo, Ilkka, Cinquini, Michela, Vespignani, Roberto, Colamartini, Americo, Di Iorio, Valentina, Massa, Ilaria, González-Lorenzo, Marien, Bertizzolo, Lorenzo, Nyberg, Peter, Grimshaw, Jeremy, Bonovas, Stefanos, Nanni, Oriana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123241/
https://www.ncbi.nlm.nih.gov/pubmed/27884165
http://dx.doi.org/10.1186/s13012-016-0514-3
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author Moja, Lorenzo
Passardi, Alessandro
Capobussi, Matteo
Banzi, Rita
Ruggiero, Francesca
Kwag, Koren
Liberati, Elisa Giulia
Mangia, Massimo
Kunnamo, Ilkka
Cinquini, Michela
Vespignani, Roberto
Colamartini, Americo
Di Iorio, Valentina
Massa, Ilaria
González-Lorenzo, Marien
Bertizzolo, Lorenzo
Nyberg, Peter
Grimshaw, Jeremy
Bonovas, Stefanos
Nanni, Oriana
author_facet Moja, Lorenzo
Passardi, Alessandro
Capobussi, Matteo
Banzi, Rita
Ruggiero, Francesca
Kwag, Koren
Liberati, Elisa Giulia
Mangia, Massimo
Kunnamo, Ilkka
Cinquini, Michela
Vespignani, Roberto
Colamartini, Americo
Di Iorio, Valentina
Massa, Ilaria
González-Lorenzo, Marien
Bertizzolo, Lorenzo
Nyberg, Peter
Grimshaw, Jeremy
Bonovas, Stefanos
Nanni, Oriana
author_sort Moja, Lorenzo
collection PubMed
description BACKGROUND: Computerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge. METHODS/DESIGN: The Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle. DISCUSSION: The results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02645357
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spelling pubmed-51232412016-12-06 Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial Moja, Lorenzo Passardi, Alessandro Capobussi, Matteo Banzi, Rita Ruggiero, Francesca Kwag, Koren Liberati, Elisa Giulia Mangia, Massimo Kunnamo, Ilkka Cinquini, Michela Vespignani, Roberto Colamartini, Americo Di Iorio, Valentina Massa, Ilaria González-Lorenzo, Marien Bertizzolo, Lorenzo Nyberg, Peter Grimshaw, Jeremy Bonovas, Stefanos Nanni, Oriana Implement Sci Study Protocol BACKGROUND: Computerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge. METHODS/DESIGN: The Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle. DISCUSSION: The results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02645357 BioMed Central 2016-11-25 /pmc/articles/PMC5123241/ /pubmed/27884165 http://dx.doi.org/10.1186/s13012-016-0514-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Study Protocol
Moja, Lorenzo
Passardi, Alessandro
Capobussi, Matteo
Banzi, Rita
Ruggiero, Francesca
Kwag, Koren
Liberati, Elisa Giulia
Mangia, Massimo
Kunnamo, Ilkka
Cinquini, Michela
Vespignani, Roberto
Colamartini, Americo
Di Iorio, Valentina
Massa, Ilaria
González-Lorenzo, Marien
Bertizzolo, Lorenzo
Nyberg, Peter
Grimshaw, Jeremy
Bonovas, Stefanos
Nanni, Oriana
Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial
title Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial
title_full Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial
title_fullStr Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial
title_full_unstemmed Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial
title_short Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial
title_sort implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the onco-codes study protocol for a randomized controlled trial
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5123241/
https://www.ncbi.nlm.nih.gov/pubmed/27884165
http://dx.doi.org/10.1186/s13012-016-0514-3
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