A new editorial by the New England Journal of Medicine attracted a lot of attention earlier this month when a group of researchers argued that science is moving too hastily towards open data. The International Consortium of Investigators for Fairness in Trial Data Sharing predicts the rush for open data initiatives will slow progress and jeopardize human health. This editorial is in response to a recent proposal by the International Committee of Medical Journal Editors requiring data from any randomized controlled trial be made available within six months of publication.
This editorial had a polarizing effect – some people agreed that yes, it hurt researchers. Others were adamant that it was not in the best interest of research efforts to limit access to data. Whatever position you take on this issue, we should all agree that retaining the granularity of the data being made available post trial – whenever that may be – merits attention, too. Open data should be responsible data.
When adding sensitive trials data to these initiatives, consideration must be placed on de-identification practices. While the Safe Harbor standard of de-identification is used, often in conjunction with a statistician, risk could remain. When measures are taken to manage the risk under Safe Harbor, the quality of the data can become useless for future research efforts. Forget when data should be made available post publication. It’s the quality and utility of data being released into open data initiatives that matters.
A risk-based approach is the best way to protect patients while preserving data quality. This is the same method for which the Institute of Medicine, EMA, PhUSE and HITRUST Alliance advocate in various published de-identification standards and guidelines. By uncovering the amount of risk contained in the data based on its intended use, you can more accurately gauge the level of privacy protections and data granularity required from your de-identification efforts.
These issues and more will be discussed at the upcoming symposium, Experiences and Methods Sharing Clinical Trials Data. Register today for the October 24 event in Philadelphia, PA.
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