# Lessons Learned Identifying and Controlling Fraudulent Participation in Online Randomized Trials

## TL;DR

This paper discusses how researchers identified and prevented fraudulent participation in online clinical trials using manual and automated methods.

## Contribution

The study introduces a manual checklist method to detect and prevent fraudulent enrollment in virtual clinical trials.

## Key findings

- Before detection, 10 fraudulent participants enrolled in the trials.
- After implementing new measures, 37 fraudulent participants were identified at the screening stage.
- Manual and automated methods together can detect evolving fraud patterns in online studies.

## Abstract

Virtually conducted clinical trials have become an important tool for improving access to research. Online research gives rise to new avenues for potentially fraudulent actors to participate in studies to achieve monetary gain. We describe our experience of uncovering and removing fraudulent participants from a virtual research study and our methods to prevent fraudulent participants in the future. Fraudulent participation in the 2 linked online clinical trials was first uncovered in 2023, prompting our investigation and identification of additional fraudulent participants (falsified identity or information to meet eligibility criteria) who successfully enrolled in these trials. Our study team categorized indicators of suspicious activity at prescreening, screening, and baseline stages of study participation and implemented a manual checklist method to prevent fraudulent participation. We evaluate the effectiveness of our fraud prevention methods 6 months after the initial breach of the trials. Before initial detection, 10 fraudulent participants successfully enrolled in our trials. Following the implementation of new fraud prevention measures, 37 individuals were identified as fraudulent at the screening stage, and no new fraudulent participants were enrolled. We provide a comprehensive list of suspicious behaviors that may suggest the virtual research intrusion of persons using fake identities. For online clinical studies, manual methods of fraud prevention, used in conjunction with automated prevention methods, can equip researchers to detect evolving patterns of attempted fraudulent enrollment.