From Health 201AI Med Risk

What happenedRebeca Cardoso Tenente Molina, a 32-year-old psychologist, was hospitalized June 2, 2026 in São João Nepomuceno, Brazil for suspected gallstones. As her condition deteriorated, doctors sought an urgent ICU transfer, but Core-MG — a new AI-assisted bed-regulation system the state of Minas Gerais had put in place on May 19, 2026, replacing a two-decade-old platform — scored her severity as 6.8, which her family and treating doctors say should have been rated a 10. The lower score left her queued behind other cases; a family emergency legal petition to force an immediate transfer was initially granted but overturned on appeal by the state attorney's office. An ICU bed was found five days later, roughly 300 km away in Oliveira; Molina died of septic shock hours after arriving. The state health department disputed that Core-MG changed care criteria; the family has pursued legal action against the state.

Failure modeAn algorithmic severity score, not a treating clinician, effectively gated a time-critical ICU transfer, and doctors reported losing the authority to override the system's assessment even as lab results showed clear deterioration — collapsing a life-or-death triage decision into a single unchallenged number.

What might have helpedRetaining a fast, unambiguous override to bypass an algorithmic severity score when bedside findings or trending labs contradict it could have supported time-critical transfers. Running any new triage or bed-allocation system in shadow mode alongside the prior process before cutover, with real-time monitoring for score drift on deteriorating patients, might have provided a safer transition. An independent audit of severity-scoring logic before statewide rollout represents one safeguard that could have been implemented.