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Resource management and capacity planning for clinical trial sites
Kesley Tyson1, Jillian Harvey2, Leila Forney3
1Clinical Research Center, Morehouse School of Medicine, Atlanta, Georgia, United States of America.
Background:
Since 2020, the number of registered clinical trials has surged by over 30%, significantly increasing the demand for skilled coordinators. Despite this growth, a national shortage of qualified coordinators remains, driven by escalating responsibilities and workloads. Effective resource management is crucial for retention. While the Ontario Protocol Assessment Level (OPAL) helps quantify trial complexity, it overlooks key factors such as organizational structure and budget constraints that impact coordinator productivity. This project aims to refine the OPAL score by integrating it with longitudinal coordinator effort data, improving resource allocation, operational efficiency, and job satisfaction, thereby reducing burnout and turnover.
Aim:
The aim of this study was to reduce burnout and turnover, ultimately contributing to the overall success of clinical trials.
Methods:
Actively enrolling interventional studies with corresponding coordinator effort tracking from June 1, 2022, to December 1, 2022, were included in the database. Protocols were graded using an adapted protocol assessment tool. Descriptive statistics compared protocol characteristics to the adapted assessment score and tracked coordinator hours, while Student's t-test and univariate analysis evaluated differences in continuous variables. Linear regression analysis assessed the association between the adapted score and the coordinator effort.
Results:
Seven protocols were analyzed: five (71%) were federally funded, two (29%) were industry-sponsored; four (57%) were behavioral interventions, and three (43%) were drug studies. Significant differences were observed between industry-sponsored and federally funded studies (7.25 ± 1.77 vs. 6.45 ± 1.65; P < 0.0001) and between behavioral interventions and drug studies (6.88 ± 1.56 vs. 6.42 ± 1.91; P < 0.0001). Linear regression revealed the adapted OPAL score significantly predicted coordinator hours (β = 77.22; P = 0.01; R 2 = 0.78).
Conclusion:
The adapted protocol complexity scores predict coordinator effort, aiding in capacity assessment and objective project distribution.
Relevance For Patients:
The findings from this project can inform more precise resource allocation, potentially leading to higher-quality studies and enhanced participant safety.
Insights
An adapted protocol complexity score predicts clinical trial coordinator effort, improving resource allocation and reducing burnout. This helps manage workloads and enhance job satisfaction in clinical research.
Area of Science:
- Clinical research operations
- Healthcare management
- Clinical trial coordination
Background:
- Clinical trial coordination is critical, with a 30% surge in trials since 2020 increasing demand.
- A national shortage of qualified coordinators persists due to rising workloads and responsibilities.
- Current tools like the Ontario Protocol Assessment Level (OPAL) do not fully capture factors affecting coordinator productivity.
Purpose of the Study:
- To refine the OPAL score by integrating coordinator effort data.
- To improve resource allocation and operational efficiency in clinical trials.
- To enhance job satisfaction and reduce burnout and turnover among clinical trial coordinators.
Main Methods:
- Analyzed actively enrolling interventional studies with coordinator effort tracking (June 2022-December 2022).
- Utilized an adapted protocol assessment tool to grade protocol complexity.
- Employed descriptive statistics, Student's t-test, univariate analysis, and linear regression to analyze data.
Main Results:
- Seven protocols were analyzed: 5 (71%) federally funded, 2 (29%) industry-sponsored; 4 (57%) behavioral, 3 (43%) drug studies.
- Significant differences in complexity scores were found between industry-funded vs. federally funded studies (P < 0.0001) and behavioral vs. drug studies (P < 0.0001).
- The adapted OPAL score significantly predicted coordinator hours (R² = 0.78, P = 0.01).
Conclusions:
- Adapted protocol complexity scores effectively predict coordinator effort.
- This tool aids in objective capacity assessment and project distribution.
- Findings support more precise resource allocation for higher-quality studies and improved patient safety.
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