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Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient
Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient
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Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient
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Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient
Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient

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Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient
Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient
Journal Article

Assessing Participation Burden in Clinical Trials: Introducing the Patient Friction Coefficient

2020
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Overview
Protocol design complexity, and associated study volunteer burden, negatively impact patient recruitment and retention as well as overall research and development productivity. Complex protocols reduce the willingness of potential clinical trial participants to enroll and reduce retention rates. There have been few systematic assessments of protocol design characteristics to determine the burden placed on study volunteers, although such an assessment would offer a compelling opportunity to optimize trial designs and improve recruitment and retention performance. To be useful, an assessment would need to be patient-centric, and focused on the factors that influence participation throughout the clinical trial. Such an assessment would also need to accommodate the unique cost-value trade-off compared with current treatment patterns that each participant makes when choosing to participate and remain in a clinical trial. This article proposes a new methodology to quantify patient burden: the clinical trial patient friction coefficient (PFC). A case example is provided to illustrate the utility of the PFC. A number of applications for the PFC are envisioned: standardizing patient burden assessment to evaluate clinical trial design feasibility, shedding light on the impact of patient burden on clinical trial economics and performance, and conducting sensitivity analyses to identify factors that most reduce patient burden and improve the performance and efficiency of clinical trials.