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Implementing an innovative consent form: the PREDICT experience

BACKGROUND: In the setting of coronary angiography, generic consent forms permit highly variable communication between patients and physicians. Even with the existence of multiple risk models, clinicians have been unable to readily access them and thus provide patients with vague estimations regardi...

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Autores principales: Decker, Carole, Arnold, Suzanne V, Olabiyi, Olawale, Ahmad, Homaa, Gialde, Elizabeth, Luark, Jamie, Riggs, Lisa, DeJaynes, Terry, Soto, Gabriel E, Spertus, John A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2621244/
https://www.ncbi.nlm.nih.gov/pubmed/19117513
http://dx.doi.org/10.1186/1748-5908-3-58
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author Decker, Carole
Arnold, Suzanne V
Olabiyi, Olawale
Ahmad, Homaa
Gialde, Elizabeth
Luark, Jamie
Riggs, Lisa
DeJaynes, Terry
Soto, Gabriel E
Spertus, John A
author_facet Decker, Carole
Arnold, Suzanne V
Olabiyi, Olawale
Ahmad, Homaa
Gialde, Elizabeth
Luark, Jamie
Riggs, Lisa
DeJaynes, Terry
Soto, Gabriel E
Spertus, John A
author_sort Decker, Carole
collection PubMed
description BACKGROUND: In the setting of coronary angiography, generic consent forms permit highly variable communication between patients and physicians. Even with the existence of multiple risk models, clinicians have been unable to readily access them and thus provide patients with vague estimations regarding risks of the procedure. METHODS: We created a web-based vehicle, PREDICT, for embedding patient-specific estimates of risk from validated multivariable models into individualized consent documents at the point-of-care. Beginning August 2006, outpatients undergoing coronary angiography at the Mid America Heart Institute received individualized consent documents generated by PREDICT. In February 2007 this approach was expanded to all patients undergoing coronary angiography within the four Kansas City hospitals of the Saint Luke's Health System. Qualitative research methods were used to identify the implementation challenges and successes with incorporating PREDICT-enhanced consent documents into routine clinical care from multiple perspectives: administration, information systems, nurses, physicians, and patients. RESULTS: Most clinicians found usefulness in the tool (providing clarity and educational value for patients) and satisfaction with the altered processes of care, although a few cardiologists cited delayed patient flow and excessive patient questions. The responses from administration and patients were uniformly positive. The key barrier was related to informatics. CONCLUSION: This preliminary experience suggests that successful change in clinical processes and organizational culture can be accomplished through multidisciplinary collaboration. A randomized trial of PREDICT consent, leveraging the accumulated knowledge from this first experience, is needed to further evaluate its impact on medical decision-making, patient compliance, and clinical outcomes.
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spelling pubmed-26212442009-01-13 Implementing an innovative consent form: the PREDICT experience Decker, Carole Arnold, Suzanne V Olabiyi, Olawale Ahmad, Homaa Gialde, Elizabeth Luark, Jamie Riggs, Lisa DeJaynes, Terry Soto, Gabriel E Spertus, John A Implement Sci Research Article BACKGROUND: In the setting of coronary angiography, generic consent forms permit highly variable communication between patients and physicians. Even with the existence of multiple risk models, clinicians have been unable to readily access them and thus provide patients with vague estimations regarding risks of the procedure. METHODS: We created a web-based vehicle, PREDICT, for embedding patient-specific estimates of risk from validated multivariable models into individualized consent documents at the point-of-care. Beginning August 2006, outpatients undergoing coronary angiography at the Mid America Heart Institute received individualized consent documents generated by PREDICT. In February 2007 this approach was expanded to all patients undergoing coronary angiography within the four Kansas City hospitals of the Saint Luke's Health System. Qualitative research methods were used to identify the implementation challenges and successes with incorporating PREDICT-enhanced consent documents into routine clinical care from multiple perspectives: administration, information systems, nurses, physicians, and patients. RESULTS: Most clinicians found usefulness in the tool (providing clarity and educational value for patients) and satisfaction with the altered processes of care, although a few cardiologists cited delayed patient flow and excessive patient questions. The responses from administration and patients were uniformly positive. The key barrier was related to informatics. CONCLUSION: This preliminary experience suggests that successful change in clinical processes and organizational culture can be accomplished through multidisciplinary collaboration. A randomized trial of PREDICT consent, leveraging the accumulated knowledge from this first experience, is needed to further evaluate its impact on medical decision-making, patient compliance, and clinical outcomes. BioMed Central 2008-12-31 /pmc/articles/PMC2621244/ /pubmed/19117513 http://dx.doi.org/10.1186/1748-5908-3-58 Text en Copyright © 2008 Decker et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Decker, Carole
Arnold, Suzanne V
Olabiyi, Olawale
Ahmad, Homaa
Gialde, Elizabeth
Luark, Jamie
Riggs, Lisa
DeJaynes, Terry
Soto, Gabriel E
Spertus, John A
Implementing an innovative consent form: the PREDICT experience
title Implementing an innovative consent form: the PREDICT experience
title_full Implementing an innovative consent form: the PREDICT experience
title_fullStr Implementing an innovative consent form: the PREDICT experience
title_full_unstemmed Implementing an innovative consent form: the PREDICT experience
title_short Implementing an innovative consent form: the PREDICT experience
title_sort implementing an innovative consent form: the predict experience
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2621244/
https://www.ncbi.nlm.nih.gov/pubmed/19117513
http://dx.doi.org/10.1186/1748-5908-3-58
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