Abstract

Effective management of staffing levels and a deep understanding of study complexity are critical for the operational success of clinical trials and in fostering a sustainable profession for research administrators. This project introduces an innovative approach to assess clinical trial complexity and to translate these assessments into actionable, sustainable staffing strategies. By developing criteria to classify trials into low, medium, or high complexity—considering elements like protocol type, number of study arms, and procedural volume—we align complexity scores with necessary staff hours. We also account for variables such as non-working days and administrative demands to ensure a realistic assessment of available working time.
Our model, which focuses on clinical research billing compliance and budgeting, offers broad applicability across various facets of clinical research workforce management. A retrospective analysis of staff productivity relative to capacity provided insights into operational demands across different trial complexities, underscoring the need for flexible staffing strategies to manage unpredictable work volumes and prevent staff burnout. This flexibility ensures operational continuity and maintains high work quality standards.
The strategic planning of resource allocation is further enhanced through a flexible staffing model demonstrated to manage workload fluctuations effectively, improve study activation timelines, and boost staff well-being. By integrating a predictive analytics framework, we can forecast staffing needs to meet future workload changes and aggressive clinical trial activation timelines.
This presentation will detail our methodology, implementation, and the impactful outcomes of our model. Attendees will gain insights into how strategic staffing, aligned with the complexity of clinical trials, can create a more sustainable and efficient work environment, showcasing the practical benefits and broad applicability of our approach in research administration.