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 patient...
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Autor*in:	Moja, Lorenzo [verfasserIn] 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

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Computerized decision support systems Electronic health records Electronic patient records Evidence-based medicine Pragmatic trial Randomized controlled trial Reminder systems Oncology

Anmerkung:	© The Author(s). 2016

Übergeordnetes Werk:	Enthalten in: Implementation science - London : BioMed Central, 2006, 11(2016), 1 vom: 25. Nov.
Übergeordnetes Werk:	volume:11 ; year:2016 ; number:1 ; day:25 ; month:11

Links:	Volltext

DOI / URN:	10.1186/s13012-016-0514-3

Katalog-ID:	SPR029525799

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520			\|a 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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allfields	10.1186/s13012-016-0514-3 doi (DE-627)SPR029525799 (SPR)s13012-016-0514-3-e DE-627 ger DE-627 rakwb eng Moja, Lorenzo verfasserin (orcid)0000-0001-6680-6507 aut 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 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 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 Computerized decision support systems (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 Electronic patient records (dpeaa)DE-He213 Evidence-based medicine (dpeaa)DE-He213 Pragmatic trial (dpeaa)DE-He213 Randomized controlled trial (dpeaa)DE-He213 Reminder systems (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Passardi, Alessandro aut Capobussi, Matteo aut Banzi, Rita aut Ruggiero, Francesca aut Kwag, Koren aut Liberati, Elisa Giulia aut Mangia, Massimo aut Kunnamo, Ilkka aut Cinquini, Michela aut Vespignani, Roberto aut Colamartini, Americo aut Di Iorio, Valentina aut Massa, Ilaria aut González-Lorenzo, Marien aut Bertizzolo, Lorenzo aut Nyberg, Peter aut Grimshaw, Jeremy aut Bonovas, Stefanos aut Nanni, Oriana aut Enthalten in Implementation science London : BioMed Central, 2006 11(2016), 1 vom: 25. Nov. (DE-627)509006191 (DE-600)2225822-X 1748-5908 nnns volume:11 year:2016 number:1 day:25 month:11 https://dx.doi.org/10.1186/s13012-016-0514-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2016 1 25 11
spelling	10.1186/s13012-016-0514-3 doi (DE-627)SPR029525799 (SPR)s13012-016-0514-3-e DE-627 ger DE-627 rakwb eng Moja, Lorenzo verfasserin (orcid)0000-0001-6680-6507 aut 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 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 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 Computerized decision support systems (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 Electronic patient records (dpeaa)DE-He213 Evidence-based medicine (dpeaa)DE-He213 Pragmatic trial (dpeaa)DE-He213 Randomized controlled trial (dpeaa)DE-He213 Reminder systems (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Passardi, Alessandro aut Capobussi, Matteo aut Banzi, Rita aut Ruggiero, Francesca aut Kwag, Koren aut Liberati, Elisa Giulia aut Mangia, Massimo aut Kunnamo, Ilkka aut Cinquini, Michela aut Vespignani, Roberto aut Colamartini, Americo aut Di Iorio, Valentina aut Massa, Ilaria aut González-Lorenzo, Marien aut Bertizzolo, Lorenzo aut Nyberg, Peter aut Grimshaw, Jeremy aut Bonovas, Stefanos aut Nanni, Oriana aut Enthalten in Implementation science London : BioMed Central, 2006 11(2016), 1 vom: 25. Nov. (DE-627)509006191 (DE-600)2225822-X 1748-5908 nnns volume:11 year:2016 number:1 day:25 month:11 https://dx.doi.org/10.1186/s13012-016-0514-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2016 1 25 11
allfields_unstemmed	10.1186/s13012-016-0514-3 doi (DE-627)SPR029525799 (SPR)s13012-016-0514-3-e DE-627 ger DE-627 rakwb eng Moja, Lorenzo verfasserin (orcid)0000-0001-6680-6507 aut 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 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 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 Computerized decision support systems (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 Electronic patient records (dpeaa)DE-He213 Evidence-based medicine (dpeaa)DE-He213 Pragmatic trial (dpeaa)DE-He213 Randomized controlled trial (dpeaa)DE-He213 Reminder systems (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Passardi, Alessandro aut Capobussi, Matteo aut Banzi, Rita aut Ruggiero, Francesca aut Kwag, Koren aut Liberati, Elisa Giulia aut Mangia, Massimo aut Kunnamo, Ilkka aut Cinquini, Michela aut Vespignani, Roberto aut Colamartini, Americo aut Di Iorio, Valentina aut Massa, Ilaria aut González-Lorenzo, Marien aut Bertizzolo, Lorenzo aut Nyberg, Peter aut Grimshaw, Jeremy aut Bonovas, Stefanos aut Nanni, Oriana aut Enthalten in Implementation science London : BioMed Central, 2006 11(2016), 1 vom: 25. Nov. (DE-627)509006191 (DE-600)2225822-X 1748-5908 nnns volume:11 year:2016 number:1 day:25 month:11 https://dx.doi.org/10.1186/s13012-016-0514-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2016 1 25 11
allfieldsGer	10.1186/s13012-016-0514-3 doi (DE-627)SPR029525799 (SPR)s13012-016-0514-3-e DE-627 ger DE-627 rakwb eng Moja, Lorenzo verfasserin (orcid)0000-0001-6680-6507 aut 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 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 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 Computerized decision support systems (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 Electronic patient records (dpeaa)DE-He213 Evidence-based medicine (dpeaa)DE-He213 Pragmatic trial (dpeaa)DE-He213 Randomized controlled trial (dpeaa)DE-He213 Reminder systems (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Passardi, Alessandro aut Capobussi, Matteo aut Banzi, Rita aut Ruggiero, Francesca aut Kwag, Koren aut Liberati, Elisa Giulia aut Mangia, Massimo aut Kunnamo, Ilkka aut Cinquini, Michela aut Vespignani, Roberto aut Colamartini, Americo aut Di Iorio, Valentina aut Massa, Ilaria aut González-Lorenzo, Marien aut Bertizzolo, Lorenzo aut Nyberg, Peter aut Grimshaw, Jeremy aut Bonovas, Stefanos aut Nanni, Oriana aut Enthalten in Implementation science London : BioMed Central, 2006 11(2016), 1 vom: 25. Nov. (DE-627)509006191 (DE-600)2225822-X 1748-5908 nnns volume:11 year:2016 number:1 day:25 month:11 https://dx.doi.org/10.1186/s13012-016-0514-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2016 1 25 11
allfieldsSound	10.1186/s13012-016-0514-3 doi (DE-627)SPR029525799 (SPR)s13012-016-0514-3-e DE-627 ger DE-627 rakwb eng Moja, Lorenzo verfasserin (orcid)0000-0001-6680-6507 aut 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 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 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 Computerized decision support systems (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 Electronic patient records (dpeaa)DE-He213 Evidence-based medicine (dpeaa)DE-He213 Pragmatic trial (dpeaa)DE-He213 Randomized controlled trial (dpeaa)DE-He213 Reminder systems (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Passardi, Alessandro aut Capobussi, Matteo aut Banzi, Rita aut Ruggiero, Francesca aut Kwag, Koren aut Liberati, Elisa Giulia aut Mangia, Massimo aut Kunnamo, Ilkka aut Cinquini, Michela aut Vespignani, Roberto aut Colamartini, Americo aut Di Iorio, Valentina aut Massa, Ilaria aut González-Lorenzo, Marien aut Bertizzolo, Lorenzo aut Nyberg, Peter aut Grimshaw, Jeremy aut Bonovas, Stefanos aut Nanni, Oriana aut Enthalten in Implementation science London : BioMed Central, 2006 11(2016), 1 vom: 25. Nov. (DE-627)509006191 (DE-600)2225822-X 1748-5908 nnns volume:11 year:2016 number:1 day:25 month:11 https://dx.doi.org/10.1186/s13012-016-0514-3 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2016 1 25 11
language	English
source	Enthalten in Implementation science 11(2016), 1 vom: 25. Nov. volume:11 year:2016 number:1 day:25 month:11
sourceStr	Enthalten in Implementation science 11(2016), 1 vom: 25. Nov. volume:11 year:2016 number:1 day:25 month:11
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Computerized decision support systems Electronic health records Electronic patient records Evidence-based medicine Pragmatic trial Randomized controlled trial Reminder systems Oncology
isfreeaccess_bool	true
container_title	Implementation science
authorswithroles_txt_mv	Moja, Lorenzo @@aut@@ Passardi, Alessandro @@aut@@ Capobussi, Matteo @@aut@@ Banzi, Rita @@aut@@ Ruggiero, Francesca @@aut@@ Kwag, Koren @@aut@@ Liberati, Elisa Giulia @@aut@@ Mangia, Massimo @@aut@@ Kunnamo, Ilkka @@aut@@ Cinquini, Michela @@aut@@ Vespignani, Roberto @@aut@@ Colamartini, Americo @@aut@@ Di Iorio, Valentina @@aut@@ Massa, Ilaria @@aut@@ González-Lorenzo, Marien @@aut@@ Bertizzolo, Lorenzo @@aut@@ Nyberg, Peter @@aut@@ Grimshaw, Jeremy @@aut@@ Bonovas, Stefanos @@aut@@ Nanni, Oriana @@aut@@
publishDateDaySort_date	2016-11-25T00:00:00Z
hierarchy_top_id	509006191
id	SPR029525799
language_de	englisch
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author	Moja, Lorenzo
spellingShingle	Moja, Lorenzo misc Computerized decision support systems misc Electronic health records misc Electronic patient records misc Evidence-based medicine misc Pragmatic trial misc Randomized controlled trial misc Reminder systems misc Oncology 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
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topic_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 Computerized decision support systems (dpeaa)DE-He213 Electronic health records (dpeaa)DE-He213 Electronic patient records (dpeaa)DE-He213 Evidence-based medicine (dpeaa)DE-He213 Pragmatic trial (dpeaa)DE-He213 Randomized controlled trial (dpeaa)DE-He213 Reminder systems (dpeaa)DE-He213 Oncology (dpeaa)DE-He213
topic	misc Computerized decision support systems misc Electronic health records misc Electronic patient records misc Evidence-based medicine misc Pragmatic trial misc Randomized controlled trial misc Reminder systems misc Oncology
topic_unstemmed	misc Computerized decision support systems misc Electronic health records misc Electronic patient records misc Evidence-based medicine misc Pragmatic trial misc Randomized controlled trial misc Reminder systems misc Oncology
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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
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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
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author_browse	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
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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
title_auth	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
abstract	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 © The Author(s). 2016
abstractGer	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 © The Author(s). 2016
abstract_unstemmed	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 © The Author(s). 2016
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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
url	https://dx.doi.org/10.1186/s13012-016-0514-3
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author2	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
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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

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