What is it about?

The clinical research staff has to successfully manage multiple studies with varying complexities, timelines, and workloads while protecting subject safety and data integrity. Failure may occur when a staff member's workload is too low or excessive. Finding the optimal workload requires metrics that display the percentage of time spent on paid and uncompensated work efforts. This article reveals a novel and simple approach that does not place an additional workload on the staff under review. It also uses an algorithm to determine which coordinator is best suited to take on a new research study.

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Why is it important?

Measuring the productivity of research staff with concomitant workloads is essential to running a successful study and site. The traditional methods do not consider the hard or soft skill sets of research staff, the environment within which they work, or their concomitant studies' impact. Failing to optimize workload over time will lead to regulatory non-compliance, subject safety or data issues, or staff burnout. This article provides site managers with the tools they need to perform resource management and capacity planning efficiently.


I've been a clinical research investigator for over thirty years. I came up with this process to determine if a research coordinator was productive or merely busy. Using metrics to solve that question required a new way of thinking and abandoning the traditional method of manual effort tracking or projecting workloads based on some antiquated formulas. The premises in the report are validated both empirically and logically. The reader may consider referring to an earlier article I wrote on the "Use of Proxy Variables to Determine the Impact of Protocol Complexity on Productivity," first published in DIA's journal in April of 2018 (Therapeutic Innovation and Regulatory Sciences) and republished by TransCellerate BioPharma. That article provides more background on the technology I developed. I hope you find these articles useful in understanding workload allocation and translating that into running a highly efficient research site while maintaining a harmonious workforce. Please feel free to contact me. A 'read-only' copy of the article is available at no charge via this link: https://rdcu.be/b6BhV

David Morin
Holston Medical Group

Read the Original

This page is a summary of: Harmonizing Protocol Complexity with Resource Management and Capacity Planning at Clinical Research Sites, Therapeutic Innovation & Regulatory Science, January 2020, Springer Science + Business Media,
DOI: 10.1007/s43441-020-00120-8.
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