The application of artificial intelligence technologies to health care delivery, coding and population management may profoundly alter the manner in which clinicians and others interact with patients, and seek reimbursement. While on one hand, AI may promote better treatment decisions and streamline onerous coding and claims submission, there are risks associated with unintended bias that may be lurking in the algorithms. AI is trained on data. To the extent that data encodes historical bias, that bias may cause unintended errors when applied to new patients. This can result in ...
Blog Editors
Recent Updates
- DOJ’s False Claims Act Recoveries Top $2.9 Billion in FY 2024, but Health Care Numbers Dip—What Could FY 2025 Hold for Health Care Enforcement?
- Recent Developments in Health Care Cybersecurity and Oversight: 2024 Wrap Up and 2025 Outlook
- Massachusetts Governor Maura Healey Signs into Law a Sweeping Health Care Market Oversight Bill
- Second Circuit Adopts “At Least One Purpose” Rule for False Claims Act Cases Premised on Anti-Kickback Statute Violations
- Supreme Court of Ohio Decides on a Peer-Review Privilege Issue in Stull v. Summa