Design and refinement of a clinical trial staffing model within the evolving landscape of oncology clinical trials

Quantifying workload for clinical trial staff represents an ongoing challenge for healthcare facilities conducting cancer clinical trials. We developed and evaluated a staffing model designed to meet this need.

To address individual protocol acuity, the model's algorithms include metrics to account for visit frequency, and the quantity, and types of research-related procedures. Since implementation in 2012, the model has been used to justify clinical research team resource needs and to establish metrics for leadership to reference when reviewing replacement positions; particularly useful to justify resources at the institutional level during the COVID-19 pandemic.In recent years, we identified a gap between predicted and actual staff workload. This precipitated a comprehensive review in 2021 of all aspects of scoring within the model including a comparison to modern protocols to ensure accounting for all types of protocol-related procedures and tests.

Further investigation identified increasing complexity of trial screening, which had not been accounted for in the initial model. Specifically, screening-related activities accounted for up to 25% of coordinator effort. We incorporated this work into the model and demonstrated a statistically significant change in average protocol acuity (P = 0.002) following refinement of scoring to include study-specific screening complexity.

Over the past decade, cancer clinical trial screening has increased in complexity and duration. Planning a cancer center's clinical trial workforce requires consideration of screening-related staff effort. For any effort model to be successful, ongoing examination and malleability are critical in this evolving landscape of clinical trials.