A maturity model for Clinical Trials Management Ecosystem
Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices...
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Published in | Journal of clinical and translational science Vol. 9; no. 1; p. e28 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Cambridge University Press
2025
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Subjects | |
Online Access | Get full text |
ISSN | 2059-8661 2059-8661 |
DOI | 10.1017/cts.2024.1168 |
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Abstract | Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities.
A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model's statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members.
We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature.
The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth. |
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AbstractList | Abstract Introduction: Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities. Methods: A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model’s statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members. Results: We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature. Conclusion: The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth. Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities.IntroductionManaging clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities.A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model's statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members.MethodsA working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model's statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members.We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature.ResultsWe developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature.The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth.ConclusionThe CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth. Introduction:Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities.Methods:A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model’s statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members.Results:We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature.Conclusion:The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth. Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities. A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model's statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members. We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature. The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth. |
ArticleNumber | e28 |
Author | Wilcox, Adam Craven, Catherine K. Pua, E. Chris Sehgal, Shruti Rojevsky, Svetlana Talbert, Jeffery C. Starren, Justin Fehrmann, Joshua Knosp, Boyd M. Becich, Michael J. |
AuthorAffiliation | 9 University of Texas Health Science Center San Antonio , San Antonio , TX , USA 5 Clinical and Translational Science Institute, University of Minnesota , USA 10 University of Arizona , Tucson , AZ , USA 4 Department of Biomedical Informatics, School of Medicine, University of Pittsburgh , PA , USA 7 Institute for Informatics, Data Science and Biostatistics, Department of Medicine, Washington University in St Louis , St Louis , MO , USA 3 Tufts Clinical and Translational Science Institute, Tufts University , Boston , MA , USA 1 Northwestern University Feinberg School of Medicine , Chicago , IL , USA 2 Vanderbilt Institute for Clinical and Translational Research , Vanderbilt University Medical Center, Nashville , TN , USA 6 Roy, J. and Lucille A. Carver College of Medicine and the Institute for Clinical & Translational Science, University of Iowa , Iowa City , IA , USA 8 Institute for Biomedical Informatics, University of Kentucky , Lexington , KY , USA |
AuthorAffiliation_xml | – name: 1 Northwestern University Feinberg School of Medicine , Chicago , IL , USA – name: 10 University of Arizona , Tucson , AZ , USA – name: 4 Department of Biomedical Informatics, School of Medicine, University of Pittsburgh , PA , USA – name: 6 Roy, J. and Lucille A. Carver College of Medicine and the Institute for Clinical & Translational Science, University of Iowa , Iowa City , IA , USA – name: 2 Vanderbilt Institute for Clinical and Translational Research , Vanderbilt University Medical Center, Nashville , TN , USA – name: 8 Institute for Biomedical Informatics, University of Kentucky , Lexington , KY , USA – name: 9 University of Texas Health Science Center San Antonio , San Antonio , TX , USA – name: 3 Tufts Clinical and Translational Science Institute, Tufts University , Boston , MA , USA – name: 5 Clinical and Translational Science Institute, University of Minnesota , USA – name: 7 Institute for Informatics, Data Science and Biostatistics, Department of Medicine, Washington University in St Louis , St Louis , MO , USA |
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Snippet | Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with... Introduction:Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We... Abstract Introduction: Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for... |
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SubjectTerms | clinical and translational research Clinical trials Clinical Trials Management Ecosystem Collaboration Consortia Ecosystem management Ecosystems Electronic health records Informatics Information sharing Leadership Maturity maturity models Self evaluation Software Surveys Working groups |
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Title | A maturity model for Clinical Trials Management Ecosystem |
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