Page 116 - JCTR-11-5

Journal of Clinical and
Translational Research Predicting coordinator workload with adapted OPAL

Further tool development could include integration barriers faced by similar sites, and future iterations could
with CTMS, allowing real-time updates to workload incorporate additional site-specific modifiers for broader
projections in response to evolving study demands. This applicability. Broader implementation of such models may
dynamic approach would improve operational agility help reduce disparities in site performance, build long-term
and allow research teams to respond proactively to mid- research capacity, and promote workforce sustainability,
study shifts, such as protocol amendments and accelerated particularly in settings vital to expanding clinical research
recruitment timelines. access to underserved populations.

In addition, the observed trend toward higher 5. Conclusion
coordinator burden in industry-sponsored trials, though
not statistically significant, aligns with findings from prior When applied at the outset of a clinical trial, the adapted
studies that suggest increased operational complexity in OPAL score offers a reliable, evidence-based method
commercially funded studies. These trials often include for forecasting coordinator workload and aligning
20
more rigorous documentation requirements, frequent staffing needs with protocol complexity. By translating
monitoring visits, and a higher frequency of protocol study requirements into projected full-time equivalent
amendments, all of which demand greater coordinator allocations, the tool supports more informed feasibility
time. These findings highlight the importance of adapting assessments, facilitates sponsor-site negotiations, and
workload estimations to sponsor characteristics during improves operational readiness. Early estimation of effort
site-level planning. also enables proactive staffing and budget forecasting,
which are critical elements of efficient and sustainable trial
Several limitations remain in this study, including execution.
the small sample size and single-site design, which limit
generalizability. The limited number of federally funded Importantly, no statistically significant difference was
trials in the sample (n = 2, one of which was behavioral) observed between the estimated and actual hours, thereby
created an imbalance in sponsor representation, supporting the adapted OPAL score’s accuracy. The MAE
constraining the ability to assess whether the adapted OPAL of 167.0 h (approximately 1 month of full-time work)
tool’s predictive accuracy differs meaningfully between provides a practical benchmark for staffing calibration
sponsor types. Future multi-site studies across diverse trial based on institutional norms. However, these results
portfolios are needed to further validate the tool and assess should be interpreted in the context of the study’s limited
its impact on trial performance metrics. With broader sample size and single-site design. Further validation across
institutions, trial phases, and therapeutic areas is needed to
validation, the adapted OPAL score could be integrated strengthen the generalizability and support integration of
into feasibility review workflows, budget justification the tool into feasibility planning workflows.
tools, and institutional staffing frameworks. Future
research should explore whether improved workload This study was conducted at a medical school of a
forecasting correlates with enhanced study outcomes, historically Black College and University, a community-
including faster recruitment, fewer protocol deviations, based, minority-serving, and under-resourced institution.
and improved data quality. A multi-site evaluation would The successful application of the adapted OPAL score in this
strengthen generalizability and enable the development of setting underscores its practicality and relevance for research
benchmarking tools to compare coordinator efforts across sites facing systemic barriers and operational constraints.
institutions. Broader adoption of this tool could help reduce disparities
in trial performance, improve infrastructure, and promote
Importantly, this study was conducted at a medical
school of a historically Black College and University—a workforce sustainability in underserved settings.
community-based, minority-serving, and under- With continued refinement and integration into CTMS,
resourced institution. As such, it provides critical insight the adapted OPAL score could serve as a standard tool for
into the operational realities of underrepresented research feasibility reviews, budget planning, and staffing models.
sites. These institutions often carry a disproportionate Its application may ultimately enhance trial efficiency,
operational burden and systemic barriers to trial support research staff, and promote equity in clinical
participation and sustainability. 21,22 The successful research.
application of the adapted OPAL score in this context
highlights its potential as an equitable, scalable tool for Acknowledgments
supporting workload planning and staffing decisions. The authors thank the research coordinators and
These adaptations were intentionally designed to address administrative staff whose contributions were vital to this
the disproportionate operational burden and systemic study.

Volume 11 Issue 5 (2025) 110 doi: 10.36922/JCTR025260032