Unlocking Value in Health Data: Truveta’s Data Monetization Strategy Carries Big Risks and Responsibilities

MobiHealthNews

Alaap B. Shah and Nivedita B. Patel, attorneys in the Health Care & Life Sciences practice, in the firm’s Washington, DC, office, co-authored an article in MobiHealthNews, titled “Unlocking Value in Health Data: Truveta’s Data Monetization Strategy Carries Big Risks and Responsibilities.”

Following is an excerpt:

In today’s world, data is power. Healthcare providers have massive amounts of rich health data at their fingertips. Yet historically, third-party vendors to healthcare providers often have derived financial benefits from secondary use of this data through aggregating and brokering de-identified data to downstream customers.

That is beginning to change as healthcare providers are taking back control of their data assets.

Truveta, Inc., a new startup led by 14 of the largest health systems in the U.S., has formed to pool together their vast and diverse data in order to take back control over how their patients’ de-identified data is shared and used. Truveta’s goal is to leverage patient data to improve patient care, address health inequity, accelerate the development of treatments and reduce the time to make a diagnosis.

The company will have access to de-identified data representing approximately 13% of patient records in the U.S. This amalgamation of data will result in more diversified data sets varying by diagnosis, geography and demographics. The process can significantly expand the opportunities for that data's secondary analytics uses.

The success of such a massive undertaking with so many stakeholders requires good data stewardship central to the endeavor. As healthcare providers begin to leverage their data to derive knowledge and ultimately gain wisdom about how better to care for their patients, they will bear a greater responsibility to ensure the privacy and security of the health data their patients trust them to safeguard.

Failure to afford the appropriate safeguards in terms of how data is collected, aggregated, de-identified, shared and ultimately utilized could result in the demise of this sort of big data collaboration.