Modern healthcare is a logistics machine that lost the patient in the process. John C. DeVora experienced it firsthand at Sutter Health: 200 rotating staff, checklists, and chatter about weekend plans while he lay paralyzed on the table. Medicine, he argues, has changed from a practice of judgment to a series of protocols.
This fragmented, clerical-heavy system is buckling. Doctors need 30 hours a day to complete required tasks, forcing them to prep charts during Sunday Night Football and type notes with their backs to patients. Shiv Rao, CEO of Abridge, sees AI agents as the only viable relief valve. They will handle the ‘all the jobs’ - intake for rashes, documentation, coding, and follow-up - freeing clinicians from the administrative burden that defines modern care.
The core shift isn't just efficiency; it's a fundamental reordering of access. When asked if a family member should see a lower-tier general practitioner or consult top AI models, Rao's answer was unambiguous.
Shiv Rao, This Week in AI:
- I would always do the models and then figure out who to see.
- Two choices: go to the lower third of a general practitioner's and get advice, or get it from the top 3 or 4 models.
This transition mirrors a broader pattern where innovation emerges from recognizing systemic failures. As Radiolab’s investigation into a 1,000-year-old MRSA remedy showed, when the market abandons a critical field - like antibiotic research - answers often come from unconventional, overlooked sources. The parallel is clear: when human-centric care collapses into a depersonalized conveyor belt, the solution emerges from non-human intelligence.
Regulatory actions, like New York’s ban on LLM medical advice, are not walls but signposts. They signal recognition that the model is changing. The human element DeVora found missing isn’t coming back through the old system. It’s being outsourced to algorithms designed to handle the logistics, so what remains of care can be human again.
