US, UK, Australia Confront Risks of Automated Care
AI is reshaping care decisions, but controversies in America and Australia show human oversight fails when professionals cannot override automated outcomes safely. (Stock Photo)
Artificial intelligence is increasingly influencing whether people receive healthcare, how much support they receive and how quickly providers are paid. Controversies in the United States and Australia, alongside proposed regulation in the United Kingdom, show why simply placing a human “in the loop” may not adequately protect older people.
US and Australian Cases Expose Accountability Gaps
In the US, the Centers for Medicare & Medicaid Services launched the Wasteful and Inappropriate Service Reduction, or WISeR, model in January 2026. The six-year pilot operates in six states and affects approximately 6.4 million Original Medicare beneficiaries.
Private contractors use AI and machine learning, together with clinical review, to determine whether selected treatments meet Medicare requirements. These include epidural steroid injections, cervical spinal fusion, implanted nerve stimulators and treatments for chronic wounds.
CMS expects standard authorization decisions within three calendar days and urgent decisions within two days. However, documents released through a freedom-of-information lawsuit reportedly revealed high rejection rates and delays. Some patients waited more than a month, while one request allegedly remained unanswered for 83 days.
Such delays can seriously affect older adults. Postponing pain treatment may reduce mobility and increase fall risk, while delayed treatment for a diabetic foot ulcer could lead to hospitalization.
Australia provides another warning. Its Integrated Assessment Tool uses information collected by assessors to classify older people and determine their funding under the Support at Home program.
Government officials had previously indicated that professional assessors could override the algorithm. However, internal documents reportedly showed that the Aged Care Rules 2025 provided no legal discretion for assessors to change its recommendation—even when they believed an older person had been allocated inadequate support.
Concerns emerged soon after implementation. By March 2026, 800 older Australians had requested assessment reviews, compared with 178 review requests during the previous financial year. In one reported case, an 87-year-old man with dementia initially received only 60% of his assessed care package, leaving insufficient support for a daily shower.
The controversy shows that human oversight is meaningless if professionals lack the legal and practical power to correct an automated decision. A bill restoring direct human override passed the Australian Senate in July, but further legislative action remained necessary.
UK proposes lifecycle regulation for healthcare AI
The UK is considering a more preventive approach. In September 2026, its National Commission into the Regulation of AI in Healthcare recommended supervising AI-enabled medical devices throughout their lifecycle.
Products could receive limited authorization before collecting more evidence through controlled clinical use. Regulators would continue monitoring safety, accuracy, bias and performance after deployment.
This matters because AI may perform differently across settings. A fall-risk tool trained with hospital data, for example, may be less accurate in nursing homes or home care.
Although the three cases involve different systems, they raise the same question: who is responsible when an algorithm influences access to care?
For elder-care providers, effective oversight requires trained professionals who can understand, challenge and reverse automated decisions. Technology companies must also provide real-world evidence and clear correction procedures. AI can support faster and more consistent care decisions—but it should never remove professional accountability.
Source: CMS, The Guardian, ABC
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