Recommendations for monitoring adherence and fidelity in pragmatic trials based on experience in the Pain Management Collaboratory.

OBJECTIVE: Most pragmatic trials follow the PRagmatic Explanatory Continuum Indicator Summary (PRECIS-2) criteria. The criteria specify unobtrusive measurement of participants' protocol adherence and practitioners' intervention fidelity but suggest no special monitoring strategies to assure trial integrity. We present experience with adherence/fidelity monitoring in the Pain Management Collaboratory (PMC) and provide recommendations for their monitoring in pragmatic trials to preserve inferences of treatment comparisons. METHODS: In November 2021, we surveyed 10 of 11 originally funded PMC pragmatic trials to determine the extent to which adherence and fidelity data were being monitored. RESULTS: Of the 10 PMC trials, 8 track adherence/fidelity. The electronic health record is the most frequent source for monitoring adherence (7/10) and fidelity (5/10). Most adherence data are used to monitor participant engagement with the trial intervention (4/10) and are reviewed by study teams (8/10) and often with a data and safety monitoring board (DSMB) (5/10). Half of the trials (5/10) reported using fidelity data for feedback/training; such data are not shared with a DSMB (0/10). Only 2 of 10 trials reported having prespecified guidance or rules around adherence/fidelity (eg, stopping rules or thresholds for corrective action, such as retraining). CONCLUSIONS: As a best practice for pragmatic trials, we recommend early and regular adherence/fidelity monitoring to determine whether intervention delivery is as intended. We propose a 2-stage process with thresholds for intervening and triggers for conducting a formal futility analysis if adherence and fidelity are not maintained. The level of monitoring should be unobtrusive for both participants and those delivering the intervention; resulting data should be reviewed by an independent DSMB.

Duke Scholars

Author Cynthia Jan Coffman Biostatistics & Bioinformatics, Division of Biostatistics