The development of a mobile app‐focused deduplication strategy for the Apple Heart Study that informs recommendations for future digital trials

Abstract

An app‐based clinical trial enrolment process can contribute to duplicated records, carrying data management implications. Our objective was to identify duplicated records in real time in the Apple Heart Study (AHS). We leveraged personal identifiable information (PII) to develop a dissimilarity score (DS) using the Damerau–Levenshtein distance. For computational efficiency, we focused on four types of records at the highest risk of duplication. We used the receiver operating curve (ROC) and resampling methods to derive and validate a decision rule to classify duplicated records. We identified 16,398 (4%) duplicated participants, resulting in 419,297 unique participants out of a total of 438,435 possible. Our decision rule yielded a high positive predictive value (96%) with negligible impact on the trial's original findings. Our findings provide principled solutions for future digital trials. When establishing deduplication procedures for digital trials, we recommend collecting device identifiers in addition to participant identifiers; collecting and ensuring secure access to PII; conducting a pilot study to identify reasons for duplicated records; establishing an initial deduplication algorithm that can be refined; creating a data quality plan that informs refinement; and embedding the initial deduplication algorithm in the enrolment platform to ensure unique enrolment and linkage to previous records.

The evolving role of data & safety monitoring boards for real-world clinical trials

“…The integration of enormous amounts of data was further complicated by the devices. For example, duplicated records (e.g., due to downloading a new version of the app) led to challenges in knowing how many individuals were enrolled in the study and in longitudinally linking pieces of data back to the right participants [16]. These issues with data integrity affect key pieces of trial conduct, such as monitoring enrollment and follow-up, which fall under the purview of the DSMB [11].…”

“…In the Apple Heart Study, when duplicated records were discovered despite an initial deduplication scheme, the study team developed and evaluated performance of a refined deduplication algorithm while the study was ongoing. While enrollment was not interrupted, the study team continued to carefully assess the issue of duplicated records throughout the lifespan of the study [16]. Additionally, access to intensively sampled data – a feature that accompanies some real-world data – can be leveraged opportunistically to monitor key study activities in real-time.…”