Creating an Effort Tracking Tool to Improve Therapeutic Cancer Clinical Trials Workload Management and Budgeting

Abstract

Quantifying data management and regulatory workload for clinical research is a difficult task that would benefit from a robust tool to assess and allocate effort. As in most clinical research environments, The University of Michigan Comprehensive Cancer Center (UMCCC) Clinical Trials Office (CTO) struggled to effectively allocate data management and regulatory time with frequently inaccurate estimates of how much time was required to complete the specific tasks performed by each role. In a dynamic clinical research environment in which volume and intensity of work ebbs and flows, determining requisite effort to meet study objectives was challenging. In addition, a data-driven understanding of how much staff time was required to complete a clinical trial was desired to ensure accurate trial budget development and effective cost recovery. Accordingly, the UMCCC CTO developed and implemented a Web-based effort-tracking application with the goal of determining the true costs of data management and regulatory staff effort in clinical trials. This tool was developed, implemented, and refined over a 3-year period. This article describes the process improvement and subsequent leveling of workload within data management and regulatory that enhanced the efficiency of UMCCC's clinical trials operation.

Developing a model to predict accrual to cancer clinical trials: Data from an NCI designated cancer center

“…Such issues highlight the importance of having a sound strategic plan when opening clinical trials so that trials can accrue quickly and efficiently. Effort tracking systems may be able to help improve the resource allocation but can be cumbersome to implement in practice [11].…”

Patient Acuity Related to Clinical Research: Concept Clarification and Literature Review

“…Three studies were published as a series of articles published within the same year on the same topic and are counted once for the purposes of the review, with all articles included in the reference list (Cusack, Jones-Wells, & Chisholm, 2004a, 2004b; Gwede, Johnson, & Trotti, 2000a, 2000b; James et al, 2011a, 2011b; Jones, Cusack, & Chisholm, 2004). For level of evidence, six used instrument development methods (Berridge, Coffey, Lyddiard, & Briggs, 2010; Briggs, 2008; Good, Lubejko, Humphries, & Medders, 2013; Hancock, Wiland, Brown, Kerner-Slemons, & Brown, 1995; James et al, 2011a, 2011b; Moore & Hastings, 2006). Two were prospective studies (Coffey, Berridge, Lyddiard, & Briggs, 2011; Penberthy, Dahman, Petkov, & DeShazo, 2012).…”

“…Finally, one was a quality improvement study (Cusack et al, 2004a(Cusack et al, , 2000bJones et al, 2004) and two were expert opinion or commentary (Cassidy & Macfarlane, 1991;Smuck et al, 2011). In relation to psychometric assessments, eight had no reliability and validity data reported (Berridge et al, 2010;Ellis et al, 2012;Good et al, 2013;Gwede et al, 2000aGwede et al, , 2000bJames et al, 2011aJames et al, , 2011bMcCarthy, 1997;Roche et al, 2002;Smuck et al, 2011). Five studies mentioned reliability and validity but no data were presented (Briggs, 2008;Coffey et al, 2011;Cusack et al, 2004aCusack et al, , 2000bJones et al, 2004;Oddone et al, 1995;Penberthy et al, 2012).…”

Measuring Clinical Trial–Associated Workload in a Community Clinical Oncology Program

“…In addition, many of the other tools employ complex scoring formulas or ratings that include measurements of time associated with individual trial-related tasks and/or rankings similar to the WPAT but with more detailed ranking options. [8][9][10][11][12] The WPAT was developed with an emphasis on simplicity, reproducibility, and long-term usability.…”