Among the recommendations of a value-based care task force of the American Medical Group Association (AMGA) is that CMS should establish a total-cost-of-care model for end-of-life care. The value-based care task force noted that “the current landscape of end-of-life care is influenced by Medicare Hospice Benefit’s per diem reimbursement and six-month prognosis criteria, which is based on hospice’s traditional focus on cancer patients. This focus, however, is shifting due to changing patient demographics, as hospice patients are increasingly diagnosed with non-cancer conditions,” the AMGA report says, encouraging CMS to develop a comprehensive framework that encompasses all aspects of care delivery and reimbursement to address the holistic needs of patients.

AI Won’t Replace Clinical Trial Teams, But It Fixes the Bottlenecks That Keep Patients Out

Clinical trials don’t fail because patients aren’t willing to participate. They fail because we never find most of the people who could. Despite decades of investment in recruitment vendors, site networks, and outreach programs, enrollment remains one of the most persistent bottlenecks in clinical research. Timelines stretch. Protocols stall. Entire studies are delayed or redesigned, not because the science is wrong, but because the right patients were never identified in the first place.  This is a workflow problem that AI is positioned to fix. Modern AI systems can analyze large volumes of unstructured clinical data far faster than any human team, flagging potential eligibility patterns that would otherwise go unnoticed.