Winners of COVID-19 Research Accelerator Grants Announced
Congratulations to the 15 winners of the first Research Accelerator grants, funded by the Bill & Melinda Gates Foundation! We are very proud to support this initiative, and we look forward to seeing the research outputs.
The Accelerator Program has received hundreds of applications from every corner of the globe. The awardees will find evidence for policies that mitigate the effects of the current pandemic and strengthen future disaster preparedness. The projects will leverage the COVID-19 Research Database with more than 250 million unique patients and 85 billion records. The Database is the largest HIPAA-compliant, de-identified, and limited patient-level data sets of real-world data. Read more: Winners of COVID-19 Research Accelerator Grants Announced (globenewswire.com)
What They Didn’t Teach You About Expert Determination and HIPAA
Register for our upcoming free webinar with Datavant on HIPAA Expert Determination and learn how you can achieve high levels of privacy for individuals while maximizing data utility to allow for innovation, efficiency, and development in health care.
Date: 28 APR 2021, 1 PM EST
We will discuss why Expert Determination is a critical step in using and connecting health data, and we will provide you with an overview of common pitfalls and delays in joining de-identified data across organizations. Furthermore, we will give you some ideas on overcoming these issues and maximizing data utility under HIPAA regulation.
Join Datavant and Mirador to learn about:
Don’t miss the free webinar! There will be a live Q&A at the conclusion of the presentation.
Participation in patient support forums may put rare disease patient data at risk of re-identification
Rare disease patients often struggle to find both medical advice and emotional support for their diagnosis. Consequently, many rare disease patient support forums have appeared on hospital webpages, social media sites, and on rare disease foundation sites. However, we argue that engagement in these groups may pose a healthcare data privacy threat to many participants, since it makes a series of patient indirect identifiers ‘readily available’ in combination with rare disease conditions. This information produces a risk of re-identification because it may allow a motivated attacker to use the unique combination of a patient’s identifiers and disease condition to re-identify them in anonymized data.
To assess this risk of re-identification, patient direct and indirect identifiers were mined from patient support forums for 80 patients across eight rare diseases. This data mining consisted of scanning patient testimonials, social media sites, and public records for the collection of identifiers linked to a rare disease patient. The number of people in the United States that may share each patient’s combination of marital status, 3-digit ZIP code, age, and sex, as well as their rare disease condition, was then estimated, as such information is commonly found in health records which have undergone de-identification by HIPAA’s ‘Safe Harbor.’ The study showed that by these estimations, nearly 75% of patients could be at high risk for re-identification in healthcare datasets in which they appear, due to their unique combination of identifiers. Read more >>
Source: Orphanet Journal of Rare Diseases: https://ojrd.biomedcentral.com/articles/10.1186/s13023-020-01497-3
Authors: James Gow, Colin Moffatt, & Jamie Blackport of Mirador Analytics