Data-Sharing Collaboration Aims to Advance Cancer Prevention

The University of Texas (UT) Southwestern Medical Center and the UT Health Science Center at San Antonio launched a partnership with healthcare data privacy startup TripleBlind to study the impact of collaborative, data-driven insights on cancer care quality, according to a press release shared with HealthITAnalytics.

The collaboration aims to enhance data-sharing capabilities and improve health outcomes as part of a grant from the Cancer Prevention and Research Institute of Texas (CPRIT). CRPIT recently awarded over $90 million in funding to support more than 40 cancer prevention research efforts across the state.

UT Southwestern Medical Center was awarded over $13 million, and UT Health Science Center at San Antonio received nearly $4 million to fund a wide range of projects aimed at bolstering cancer prevention, improving cancer care, and recruiting cancer researchers.

The work with TripleBlind centers around the “Screen, Treat, or Prevent (STOP) Hepatocellular Cancer-Hepatitis C (HCC-HCV): Expansion to All Adults” project, which is designed to enhance vaccination, screening, and treatment for hepatitis C and hepatitis B in individuals from low-income South Texas communities.

Hepatitis C infection can cause advanced hepatic fibrosis and cirrhosis if not addressed, which significantly increases a patient’s risk for hepatocellular carcinoma (HCC), according to research published in the Journal of Clinical and Translational Hepatology. Researchers estimate that HCC is responsible for 80 to 90 percent of all primary liver cancer cases. In the US, the disease is the fastest-growing cause of cancer deaths and the third most common cause of cancer deaths globally.

Hepatitis C is largely treatable, but barriers such as access to care, care quality, and technological limitations make tackling the condition difficult.

The press release states that another limitation to treatment is the use of EHRs, which have insufficient reporting, tracking, and analysis capabilities because of patient privacy concerns.

“It’s a classic Catch-22: Patient privacy is of the utmost importance, but data sharing is critical because researchers use and analyze data to improve patient health,” said Riddhiman Das, co-founder and CEO of TripleBlind, in the press release.

To overcome this, UT researchers are leveraging TripleBlind’s automated de-identification and privacy software to help support their work while maintaining patient privacy and HIPAA compliance. Using the tool, the research team will study how such software can help support quality of care delivery and monitoring in multiple South Texas federally qualified health centers (FQHCs).

The research aims to demonstrate how privacy-enhancing software solutions can promote more direct data interactions between collaborating institutions for healthcare research and improve health outcomes.

“We are excited to work with TripleBlind to study the potential impact of software in accelerating evidence-based quality improvement, thereby addressing the needs of minority, low-income populations who have a disproportionate need for better Hepatitis C screening, diagnosis, and treatment,” said Mamta Jain, MD, professor in the Department of Internal Medicine, Division of Infectious Diseases and Geographic Medicine at UT Southwestern Medical Center, and the team’s principal investigator, in the press release. “This is a major step in the right direction as more and more hospitals and research organizations are determining the best way to work with data and drive value for patients.”

The collaboration highlights how some healthcare organizations are turning to technology to help protect patient privacy while supporting data-driven research.

Earlier this month, Suraj Kapa, MD, a cardiac electrophysiologist with Mayo Clinic and chief medical officer at TripleBlind, discussed the nuances of data de-identification in various aspects of healthcare, including HIPAA compliance, the use of connected devices, and the role of artificial intelligence (AI), in an interview with HealthITAnalytics.