Resource Center

Patient matching is critical to improving patient outcomes. Discover how patient health data is linked across the health data ecosystem, providing a holistic view of the patient journey through time.

Clinical trials are central to making health advancements. Clinical trial tokenization and real-world data enable improved insights into the patient journey.

Using Datavant to link and de-identify employee health data, employers can better understand their employee needs and offer the right benefits for improved wellness and cost optimization.

Health data ecosystem leaders reveal 4 key health data exchange challenges to be solved in 2023 and how to work together to solve them.

Making the right health and wellbeing decisions requires complete employee data, but that data is fragmented across dozens of organizations.

I compare it to the Compounding Effect in finance. I’ve written about this since 2018. I think personal growth is very similar to compound interest: it tends to be exponential. A lot of people in the first half of their career journey have the capacity to increase their personal skills at a rate of 2 or 3 times a year.

Datavant’s mission is to connect the world’s healthcare data to improve patient outcomes while maintaining patient privacy. HIPAA has a list of 18 pieces of identifying information that must be removed in order to satisfy the Safe Harbor method of de-identification, and offers further guidance on how parts of patient data can be included in a record while still qualifying as “de-identified.”

Privacy Hub by Datavant offers industry-leading, independent HIPAA disclosure risk assessment and expert determination products and services, incorporating a breadth of analytical technologies and leveraging decades of experience of the world’s leading experts from across the field.

This is the first of a two-part post discussing some of the research behind our recently launched Datavant Trials, a web-based trial tokenization solution that helps bridge the gap between clinical trials and real-world data (RWD) to accelerate research-grade evidence generation. In this post, we outline our interest in and approaches to computing overlap between datasets that play a significant role in our trial tokenization product.