A survey on UK researchers’ views regarding their experiences with the de-identification, anonymisation, release methods and re-identification risk estimation for clinical trials datasets

Background: There are increasing pressures for anonymised datasets from clinical trials to be shared across the scientific community. However, there is no standardised set of recommendations on how to anonymise and prepare clinical trials datasets for sharing, whilst an ever-increasing number of anonymised datasets are becoming available for secondary research. Our ‎aim was to explore the current views and experiences of researchers in the UK about de-identification, anonymisation, release methods and re-identification risk estimation for clinical trials datasets.

Methods: We used an online exploratory cross-sectional descriptive survey that consisted of both open-ended and closed questions.

Results: We had 38 responses to invitation from June 2022 to October 2022. 35 participants (92%) used internal documentation and/or published guidance to de-identify/anonymise clinical trials datasets. De-identification followed by anonymisation and then fulfilling data holders’ requirements before access was granted (controlled access) was the most common process for releasing the datasets as reported by 18 (47%) participants. Eleven participants (29%) had previous knowledge of re-identification risk estimation, but they did not use any of the methodologies. Experiences in the process of de-identifying/anonymising the datasets and maintaining such datasets were mostly negative, the main reported issues were: lack of resources, guidance, and training.

Conclusions: The majority of responders reported using documented processes for de-identification and anonymization. However, our survey results clearly indicate that there are still gaps in the areas of guidance, resources and training to fulfil sharing requests of de-identified/anonymised datasets, and that re-identification risk estimation is an underdeveloped area.