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P211: BYOD Versus Provisioned Devices: A Cross-Study Exploration of Factors Influencing Patient Compliance

Poster Presenter

Lindsay Hughes

Principal, Patient Experience Solutions and Patient Centered Solutions
IQVIA
United States

Objectives

Patients’ ability to submit Patient Reported Outcomes (ePRO) using their own smartphones (BYOD) has the potential to reduce burden and has expanded the reach of hybrid and decentralized trials. While there is consensus on device equivalency, impact on patient compliance is not well understood.

Method

A retrospective analysis was conducted using electronic Clinical Outcome Assessment (eCOA) compliance data from 129 clinical trials with handheld data collection from 2018-2021. We examined patterns by device type (provisioned or BYOD using an app on the subject’s smartphone) from 4.5m submissions.

Results

Two-thirds of the assessments were submitted using provisioned devices, with the remaining 32.7% on BYOD. Submissions were analyzed by Form Status, which was broken into four categories: Non-Compliant (i.e., form not completed); Compliant (i.e., form submitted); Likely Compliant (i.e., form completion in progress); and N/A (i.e., form not required). Across the sample, 15.8% (n=707,102) were Non-Compliant. While a majority of Non-Compliant cases came from provisioned devices (n=427,661; 60%), this was due to the greater prevalence of provisioned devices in the sample. A comparison between device types showed that Non-Compliant assessments represented only 14% of all submissions from provisioned devices, compared to 19% (n=279,441) of all BYOD cases (N=1,466,092). Compliance was higher among users of provisioned devices (77%) than BYOD (70%). A greater proportion of BYOD cases were “Likely Compliant” (7% vs 2%) which may be related to the type of assessments typically deployed via BYOD, such as diaries with longer completion windows. Further investigation is needed to understand factors influencing compliance, disaggregating by Therapeutic Area and Indication, order of assessment deployment, and sample anonymized demographic/user profiles. This investigation is ongoing, and will be included in the final version of material for presentation.

Conclusion

Current literature on the appropriateness of BYOD in clinical trials is limited to pilot data or anecdotal information. This case study contributes empirical evidence drawn from real-world data to the collection of electronic clinical outcomes assessments from patients across a range of therapeutic areas and indications, and adds insights about their compliance to the evidence base. The granular exploratory analysis will provide key insights on considerations for future studies and direct the formation of generalizable research questions and hypotheses. This poster will document on-going exploratory analyses to showcase the identification of individual and group behavioral patterns and the development of hypothesis on how they may impact compliance and success in clinical research. This poster will provide groundwork for future research utilizing a data-driven approach to the determination of whether a BYOD solution is appropriate for a given protocol.