Marjorie J Good1, Patricia Hurley2, Kaitlin M Woo2, Connie Szczepanek2, Teresa Stewart2, Nicholas Robert2, Alan Lyss2, Mithat Gönen2, Rogerio Lilenbaum2. 1. National Cancer Institute, Rockville, MD; American Society of Clinical Oncology, Alexandria; Virginia Cancer Specialists/US Oncology, Fairfax, VA; Memorial Sloan-Kettering Cancer Center, New York, NY; Cancer Research Consortium of West Michigan NCI Community Oncology Research Program, Grand Rapids, MI; University of New Mexico Minority/Underserved NCI Community Oncology Research Program, Albuquerque, NM; Heartland NCI Community Oncology Research Program, Missouri Baptist Medical Center, St Louis, MO; and Yale Cancer Center/Smilow Cancer Hospital, New Haven, CT marge.good@nih.gov. 2. National Cancer Institute, Rockville, MD; American Society of Clinical Oncology, Alexandria; Virginia Cancer Specialists/US Oncology, Fairfax, VA; Memorial Sloan-Kettering Cancer Center, New York, NY; Cancer Research Consortium of West Michigan NCI Community Oncology Research Program, Grand Rapids, MI; University of New Mexico Minority/Underserved NCI Community Oncology Research Program, Albuquerque, NM; Heartland NCI Community Oncology Research Program, Missouri Baptist Medical Center, St Louis, MO; and Yale Cancer Center/Smilow Cancer Hospital, New Haven, CT.
Abstract
PURPOSE: Clinical research program managers are regularly faced with the quandary of determining how much of a workload research staff members can manage while they balance clinical practice and still achieve clinical trial accrual goals, maintain data quality and protocol compliance, and stay within budget. A tool was developed to measure clinical trial-associated workload, to apply objective metrics toward documentation of work, and to provide clearer insight to better meet clinical research program challenges and aid in balancing staff workloads. A project was conducted to assess the feasibility and utility of using this tool in diverse research settings. METHODS: Community-based research programs were recruited to collect and enter clinical trial-associated monthly workload data into a web-based tool for 6 consecutive months. Descriptive statistics were computed for self-reported program characteristics and workload data, including staff acuity scores and number of patient encounters. RESULTS: Fifty-one research programs that represented 30 states participated. Median staff acuity scores were highest for staff with patients enrolled in studies and receiving treatment, relative to staff with patients in follow-up status. Treatment trials typically resulted in higher median staff acuity, relative to cancer control, observational/registry, and prevention trials. Industry trials exhibited higher median staff acuity scores than trials sponsored by the National Institutes of Health/National Cancer Institute, academic institutions, or others. CONCLUSION: The results from this project demonstrate that trial-specific acuity measurement is a better measure of workload than simply counting the number of patients. The tool was shown to be feasible and useable in diverse community-based research settings.
PURPOSE: Clinical research program managers are regularly faced with the quandary of determining how much of a workload research staff members can manage while they balance clinical practice and still achieve clinical trial accrual goals, maintain data quality and protocol compliance, and stay within budget. A tool was developed to measure clinical trial-associated workload, to apply objective metrics toward documentation of work, and to provide clearer insight to better meet clinical research program challenges and aid in balancing staff workloads. A project was conducted to assess the feasibility and utility of using this tool in diverse research settings. METHODS: Community-based research programs were recruited to collect and enter clinical trial-associated monthly workload data into a web-based tool for 6 consecutive months. Descriptive statistics were computed for self-reported program characteristics and workload data, including staff acuity scores and number of patient encounters. RESULTS: Fifty-one research programs that represented 30 states participated. Median staff acuity scores were highest for staff with patients enrolled in studies and receiving treatment, relative to staff with patients in follow-up status. Treatment trials typically resulted in higher median staff acuity, relative to cancer control, observational/registry, and prevention trials. Industry trials exhibited higher median staff acuity scores than trials sponsored by the National Institutes of Health/National Cancer Institute, academic institutions, or others. CONCLUSION: The results from this project demonstrate that trial-specific acuity measurement is a better measure of workload than simply counting the number of patients. The tool was shown to be feasible and useable in diverse community-based research settings.
Authors: Lowell Anthony; George Atweh; Ravi Bhatia; Lisa A Carey; Jenny C Chang; Martin J Edelman; Philip W Kantoff; Merry Jennifer Markham; Wells Messersmith; Edward L Nelson; Kurt Oettel; Ruth O'Regan; Claire F Verschraegen; Julie M Vose Journal: JCO Oncol Pract Date: 2020-09-30
Authors: Tamara P Miller; Melissa Z Marx; Christopher Henchen; Nicholas P DeGroote; Sally Jones; Jenny Weiland; Beth Fisher; Adam J Esbenshade; Richard Aplenc; Christopher C Dvorak; Brian T Fisher Journal: J Patient Saf Date: 2022-04-01 Impact factor: 2.844
Authors: Arthur E Frankel; Keith T Flaherty; George J Weiner; Robert Chen; Nilofer S Azad; Michael J Pishvaian; John A Thompson; Matthew H Taylor; Daruka Mahadevan; A Craig Lockhart; Ulka N Vaishampayan; Jordan D Berlin; David C Smith; John Sarantopoulos; Matthew Riese; Mansoor N Saleh; Chul Ahn; Eugene P Frenkel Journal: Oncologist Date: 2017-03-17