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

Le résumé fourni par la source

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.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.