HiLabs and Harvard Researchers Partner to Study Ghost Networks in Medicare Advantage

July 06, 2026
HiLabs has announced a multi-year research collaboration with Dr. Thomas Tsai of Harvard University to analyze ghost networks and access to care for 35 million Medicare Advantage enrollees.

HiLabs and Dr. Thomas Tsai of Harvard University have begun a multi-year collaboration to examine provider network adequacy and ghost networks within Medicare Advantage plans, announced in a press release.

The research will measure access to care and identify gaps between listed and accessible providers across the 35 million Americans enrolled in Medicare Advantage. HiLabs will contribute real world provider data and its AI powered ghost network detection to support this work.

Dr. Tsai, a faculty member at the Harvard T.H. Chan School of Public Health and Harvard Medical School, will lead studies assessing network adequacy, provider availability, and the impact of inaccurate directories on patient outcomes.

HiLabs delivers data intelligence tools that help health plans meet federal network and directory accuracy standards. The collaboration’s findings will inform regulators and health plan leaders about where provider access gaps are most severe and how to improve network reliability nationwide.

We hope you enjoyed this article.

Subscribe to Life AI Weekly

Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.

Whitepaper

Stanford HAI’s 2025 AI Index Reveals Record Growth in AI Capabilities, Investment, and Regulation

The 2025 AI Index by Stanford HAI provides a comprehensive overview of the global state of artificial intelligence, highlighting significant advancements in AI capabilities, investment, and regulation. The report details improvements in AI performance, increased adoption in various sectors, and the growing global optimism towards AI, despite ongoing challenges in reasoning and trust. It serves as a critical resource for policymakers, researchers, and industry leaders to understand AI's rapid evolution and its implications.

Read more