Quantifying workload activity is difficult for clinical research data managers and regulatory staff. A robust data collection tool is needed to appropriately assess and allocate workloads. The ideal effort-tracking tool should be objective, widely applicable, highly functional, low maintenance, and user-friendly. In a structured yet dynamic clinical research setting, the best practice is to incorporate tracking time spent per trial into a regular routine (daily or weekly).
Articles on workload management in a clinical research environment have described methods that are either too simplistic (e.g., based on accrual) or too subjective (protocol complexity grids). The NCI established a universal workload formula in which one full-time equivalency equals 40 credits, or 25 to 30 active patients and approximately 50 follow-up patients.1 However, this formula neglects to account for the complexity of trials and the resultant increase in workload burden.2 The NCI is currently working on a protocol complexity model with a representative number of those elements “deemed to involve increased effort at the participating sites.”3 The concept of burden is subjective in nature, however, and therefore a site lacking in research infrastructure may find even the simplest protocol burdensome.4
Various business models are used to provide clinical research services.1 In some organizations, research nurses and specialized support services, such as data management, regulatory, finance, and informatics, may be organized into a central office. In other organizations, a loose network of research coordinators may perform multiple functions and report to various individuals (investigator, program director, division administrator, or clinic manager). Still others may use a hybrid of centralized and decentralized structures. This is relevant to the issue of workload metrics because a tool designed for one site may not be applicable to another site if its business model is dissimilar.
The most efficient model allows staff to specialize in research activities. Focusing attention on “a small set of linked tasks” at the institution or departmental level correlates with improved operating performance.5 The University of Michigan Comprehensive Cancer Center (UMCCC) Clinical Trials Office (CTO) is a centralized office that uses specialized research personnel in multitiered roles and disease site–specific teams, serving as a shared resource.
The authors would like to thank Janet Tarolli, RN, BSN, CCRC, and Joy Stair, MS, BSN, for serving as editors.
Gwede C, Daniels S, Johnson D. Organization of clinical research services at investigative sites: implications for workload measurement. Drug Inf J 2001;35:695–705.
Pharmaceutical Research and Manufacturers of America. Pharmaceutical Industry Profile 2009. Washington, DC: Pharmaceutical Research and Manufacturers of America; 2009:38.
NCI Clinical Trials Working Group. Trial complexity elements and scoring model. Working document. Available at: http://ctep.cancer.gov/protocolDevelopment/docs/trial_complexity_elements_scoring.doc. Accessed April 21, 2009.
Stephenson H. Strategic Research: A Practical Handbook for Phase IIIB and Phase IV Clinical Studies. Chapter 8: Optimizing site performance. Journal of Clinical Research Best Practices 2008;4(2).
Huckman RS, Zinner DE. Does focus improve operational performance? Lessons from the management of clinical trials. Strategic Management Journal 2008;29:173–219.
James P, Bebee P, Beekman L. Effort tracking metrics provide data for optimal budgeting and workload management in therapeutic cancer clinical trials. J Natl Compr Cancer Netw, in press.