Russia

Woman dies after AI hospital delay

RT English · 2026-06-16

AI SUMMARY

• What happened: A 32-year-old Brazilian psychologist, Rebeca Cardoso Tenente Molina, died after a delay in receiving an intensive-care bed, which her family blames on an AI-powered hospital bed allocation system that misclassified her condition. • Why it matters: The incident raises significant concerns about the integration of AI in healthcare, particularly regarding patient safety and the potential for algorithmic misjudgments to impact critical care decisions. • What to watch next: The response from health authorities and potential legal challenges regarding the AI system's implementation, as well as broader discussions on the role of AI in medical settings and patient care protocols.

**Title: Woman Dies After AI Hospital Delay in Brazil**

The family of a 32-year-old Brazilian psychologist has expressed their grief and outrage following her death, which they attribute to delays caused by a newly implemented AI-powered hospital bed allocation system. Rebeca Cardoso Tenente Molina, from Minas Gerais, sought medical treatment earlier this month for what was initially suspected to be gallstones. However, her condition rapidly worsened, leading doctors to determine that she required urgent transfer to an intensive care unit (ICU).

Despite the urgency of her situation, the Core-MG bed-regulation platform, introduced by the state government just a month prior, reportedly classified Molina's condition as less critical than it was. This misclassification resulted in a significant delay in her transfer. Molina's family attempted to expedite her transfer through legal means, but it took nearly five days before a bed became available approximately 300 kilometers away. By the time she was transported via private plane, Molina had succumbed to septic shock just hours after arriving at the new facility.

Molina's twin sister, Samela Cardoso Tenente Furtado, who is also a lawyer, voiced her concerns about the AI system's impact on patient care. She criticized the platform for assigning Molina a severity score of 6.8, arguing that her condition warranted a score closer to the maximum of 10. Furtado highlighted that patients with scores of 8 or higher were prioritized over her sister, despite worsening test results that indicated a decline in Molina's health.

"My sister and other patients are not just numbers or protocols; they are human lives," Furtado stated, emphasizing the emotional toll of the situation.

The Core-MG system was designed to streamline bed allocation and improve transparency in patient classification based on severity. However, the Minas Gerais Health Department has defended the system, asserting that it did not adversely affect Molina's case. Officials stated that she was registered promptly and that the transfer process is contingent upon bed availability and clinical requirements. They also maintained that medical professionals continue to oversee the regulation process and that the AI system did not alter clinical criteria for bed allocation.

Despite the department's assurances, the rollout of the Core-MG platform has faced scrutiny and legal challenges from local authorities, who argue that the system has disrupted patient transfers and may have contributed to delays in critical care.

Molina's tragic case has raised broader questions about the integration of artificial intelligence in healthcare. Similar concerns have emerged in the United States, where insurers have been sued over algorithmic claim denials, and healthcare workers have expressed apprehension about the rapid deployment of AI tools without adequate input or oversight from medical professionals.

As the healthcare community grapples with the implications of AI technology, Molina's family is left mourning a preventable loss. They are calling for a reevaluation of how AI is utilized in medical settings, advocating for a system that prioritizes human judgment and patient welfare above algorithmic efficiency.

The incident serves as a poignant reminder of the potential risks associated with the increasing reliance on technology in healthcare, highlighting the need for a balanced approach that incorporates both advanced tools and the critical insights of healthcare providers.

Source: RT English
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