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 inJournal of clinical and translational science Vol. 9; no. 1; p. e28
Main Authors Sehgal, Shruti, Pua, E. Chris, Rojevsky, Svetlana, Becich, Michael J., Fehrmann, Joshua, Knosp, Boyd M., Wilcox, Adam, Talbert, Jeffery C., Craven, Catherine K., Starren, Justin
Format Journal Article
LanguageEnglish
Published England Cambridge University Press 2025
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ISSN2059-8661
2059-8661
DOI10.1017/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.
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
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Keywords clinical and translational research
Clinical Trials Management Ecosystem
clinical trials
informatics
maturity models
Language English
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– ident: S2059866124011683_ref3
  doi: 10.1145/362280.362284
– ident: S2059866124011683_ref22
– ident: S2059866124011683_ref5
  doi: 10.1049/ic.2012.0036
– ident: S2059866124011683_ref13
  doi: 10.1093/jamia/ocab256
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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
URI https://www.ncbi.nlm.nih.gov/pubmed/40052053
https://www.proquest.com/docview/3163311337
https://www.proquest.com/docview/3174819291
https://pubmed.ncbi.nlm.nih.gov/PMC11883580
https://doaj.org/article/f59634aeb01d435c8540c123bae61ca3
Volume 9
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