AccScience Publishing / JCTR / Online First / DOI: 10.36922/JCTR025260032
SHORT COMMUNICATION

Prospective evaluation of the adapted Ontario Protocol Assessment Level score for predicting clinical research coordinator workload: An internal validation study

Kesley Holmes1* Muhammed Idris1 Jillian Harvey2 Leila Forney3 Daniel Brinton2 Jan Morgan Billingslea1 Priscilla Pemu1
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1 Clinical Research Center, Morehouse School of Medicine, Atlanta, Georgia, United States of America
2 Department of Healthcare Leadership and Management, College of Health Professions, Medical University of South Carolina, Charleston, South Carolina, United States of America
3 South Carolina Clinical and Translational Research Institute, College of Medicine, Medical University of South Carolina, Charleston, South Carolina, United States of America
Received: 28 June 2025 | Revised: 12 August 2025 | Accepted: 12 August 2025 | Published online: 25 August 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Background: The escalating complexity of clinical trial protocols has considerably increased the workload for research coordinators, exacerbating staffing shortages and contributing to operational inefficiencies. These challenges are particularly pronounced at under-resourced and minority-serving research institutions, where limited capacity may hinder the implementation of trials. Early and accurate estimation of research coordinator effort is essential for effective planning, resource management, and successful clinical trial conduct. Aim: This study assesses the accuracy of an adopted Ontario Protocol Assessment Level (OPAL) score in predicting coordinator workload to improve operational planning in clinical research. Methods: A prospective observational study was conducted over a 12-month period at a Historically Black College and University medical school. Seven coordinators recorded hours for seven actively enrolling interventional trials. Estimated workloads were calculated using a published, adapted OPAL reference table, and were compared with actual hours using descriptive statistics and paired t-tests. To ensure consistent benchmarking, workday equivalencies (7.5 h for institutional standards and 8 h for industry standards) were applied. Results: There was no statistically significant difference between estimated and actual hours, with an average difference of 24.1 h (p=0.761). The mean absolute error was 167.0 h, equivalent to roughly 1 month of full-time work. Conclusion: The adapted OPAL score provides a practical tool for estimating coordinator workload and aligning staffing with protocol complexity, including in under-resourced settings. However, broader multi-site validation is required to confirm its generalizability and to support its integration into feasibility planning. Relevance for patients: Accurate workload forecasting enhances trial efficiency, supporting timely, high-quality studies, and accelerating access to new treatments.

Graphical abstract
Keywords
Workload estimation
Ontario Protocol Assessment Level score
Clinical trial operations
Research coordinator workload
Protocol complexity
Implementation science
Workforce planning
Coordinator staffing models
Funding
This project was supported in part by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Numbers UL1TR002378, UL1 TR001450, and UM1 TR005294, and by the National Institute on Minority Health and Health Disparities under Award Number 1U24MD015970. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Conflict of interest
The authors declare that they have no competing interests.
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Journal of Clinical and Translational Research, Electronic ISSN: 2424-810X Print ISSN: 2382-6533, Published by AccScience Publishing