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Assessing Clinical Trial-Associated Workload in Community-Based Research Programs Using the ASCO Clinical Trial
Marjorie J Good1, Patricia Hurley2, Kaitlin M Woo2
1National 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.
A new tool measures clinical trial workload using staff acuity, proving more effective than patient counts. This method is feasible and useful across various research settings for better workload management.
Area of Science:
- Clinical research operations
- Healthcare management
- Health services research
Background:
- Clinical research program managers face challenges in balancing staff workload with clinical practice.
- Achieving clinical trial accrual goals, data quality, protocol compliance, and budget adherence are key management concerns.
- Accurate workload assessment is crucial for effective resource allocation and staff support.
Purpose of the Study:
- To develop and assess a tool for measuring clinical trial-associated workload.
- To apply objective metrics for documenting research staff work.
- To provide insights for managing clinical research program challenges and balancing workloads.
Main Methods:
- Community-based research programs collected monthly workload data for six months using a web-based tool.
- Data included staff acuity scores and patient encounter numbers.
- Descriptive statistics were used to analyze program characteristics and workload data.
Main Results:
- Fifty-one research programs across 30 states participated in the study.
- Staff acuity scores were highest for patients undergoing treatment compared to those in follow-up.
- Industry-sponsored trials showed higher median staff acuity than other trial types.
Conclusions:
- Trial-specific acuity measurement is a superior indicator of workload compared to patient counts.
- The developed tool demonstrated feasibility and usability in diverse community-based research settings.
- This tool can aid in optimizing staff workload and improving clinical research operations.
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