Harmonizing Protocol Complexity with Resource Management and Capacity Planning at Clinical Research Sites

Area of Science:

• Clinical research operations
• Healthcare management
• Workforce productivity

Background:

• Clinical research sites manage trials with varying complexities and workloads.
• Principal investigators (PIs) depend on clinical research coordinators (CRCs) for trial success and adherence to Good Clinical Practice (GCP) guidelines.
• Effective workload management for CRCs handling multiple concurrent studies is challenging.

Purpose of the Study:

• To introduce a novel approach for assessing the impact of protocol complexity on CRC productivity.
• To enable site managers to understand and improve workload allocation and staff performance.
• To provide metrics for assessing CRC performance based on study assignments.

Main Methods:

• Developed a novel approach to determine the effects of protocol complexity on CRC productivity.
• This method does not require effort tracking.
• It allows for the assessment of how CRC performance is affected by the number and complexity of assigned studies.

Main Results:

• An algorithmic approach can be utilized by site managers to enhance performance by understanding workload allocation effects on CRC productivity and capacity.
• This process considers factors both within and outside the site manager's control.
• Analytics can measure CRC adaptation to study complexity and cumulative workloads over time.

Conclusions:

• Sites can benefit from analytics to measure CRC adaptation to study complexity and cumulative workloads.
• Optimizing productivity involves adhering to GCP guidelines and preventing staff burnout.
• Site managers require tools to manage increasing study complexity and balance workloads effectively.