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

Kesley Holmes, Muhammed Idris, Jillian Harvey, Leila Forney, Daniel Brinton, Jan Morgan Billingslea, Priscilla Pemu
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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.

预测临床研究协调员工作量的安大略省方案评估水平评分的前瞻性评价:一项内部验证研究。
背景:临床试验方案日益复杂,大大增加了研究协调员的工作量,加剧了人员短缺,并导致操作效率低下。这些挑战在资源不足和为少数群体服务的研究机构尤其明显,在这些机构,有限的能力可能阻碍试验的实施。对研究协调员的工作进行早期和准确的评估对于有效的计划、资源管理和成功的临床试验进行至关重要。目的:本研究评估采用安大略协议评估水平(OPAL)评分预测协调员工作量的准确性,以改善临床研究的操作计划。方法:在一所历史悠久的黑人学院和大学医学院进行了一项为期12个月的前瞻性观察研究。七名协调员记录了七项积极参与的干预性试验的小时数。使用已发布的经过调整的OPAL参考表计算估计的工作负载,并使用描述性统计和配对t检验将其与实际工作时间进行比较。为了确保一致的基准,采用了工作日等效(机构标准为7.5小时,行业标准为8小时)。结果:估计小时数与实际小时数比较,差异无统计学意义,平均差24.1小时(p=0.761)。平均绝对误差为167.0小时,大约相当于1个月的全职工作。结论:调整后的OPAL评分提供了一个实用的工具,用于估计协调者的工作量,并根据协议复杂性调整人员配置,包括在资源不足的情况下。然而,需要更广泛的多地点验证,以确认其普遍性,并支持其纳入可行性规划。与患者的相关性:准确的工作量预测可提高试验效率,支持及时、高质量的研究,并加速获得新疗法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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