{"id":548471,"date":"2026-04-24T15:18:09","date_gmt":"2026-04-24T15:18:09","guid":{"rendered":"https:\/\/www.newsbeep.com\/uk\/548471\/"},"modified":"2026-04-24T15:18:09","modified_gmt":"2026-04-24T15:18:09","slug":"health-care-ai-is-here-we-dont-know-if-it-actually-helps-patients","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/uk\/548471\/","title":{"rendered":"Health-care AI is here. We don\u2019t know if it actually helps patients."},"content":{"rendered":"

But even a tool that is \u201caccurate\u201d won\u2019t necessarily improve health outcomes. AI might\u00a0speed up the interpretation of a chest X-ray<\/a>, for example. But how much will a doctor rely on its analysis? How will that tool affect the way a doctor interacts with patients or recommends treatment? And ultimately: What will this mean for those patients?<\/p>\n

The answers to those questions might vary between hospitals or departments and could depend on clinical workflows, says Wiens. They might also differ between doctors at various stages of their careers.<\/p>\n

Take the AI scribes, as another example. Some research on AI use in education<\/a> suggests that such tools can impact the way people cognitively process information. Could they affect the way a doctor processes a patient\u2019s information? Will the tools affect the way medical students think about patient data in a way that impacts care? These questions need to be explored, says Wiens. \u201cWe like things that save us time, but we have to think about the unintended consequences of this,\u201d she says.<\/p>\n

In\u00a0a study published in January 2025<\/a>, Paige Nong at the University of Minnesota and her colleagues found that around 65% of US hospitals used AI-assisted predictive tools. Only two-thirds of those hospitals evaluated their accuracy. Even fewer assessed them for bias.<\/p>\n

The number of hospitals using these tools has probably increased since then, says Wiens. Those hospitals, or entities other than the companies developing the tools, need to evaluate how much they help in specific settings. There\u2019s a possibility that they could leave patients worse off, although it\u2019s more likely that AI tools just aren\u2019t as beneficial as health-care providers might assume they are, says Wiens.<\/p>\n

\u201cI do believe in the potential of AI to really improve clinical care,\u201d says Wiens, who stresses that she doesn\u2019t want to stop the adoption of AI tools in health care. She just wants more information about how they are affecting people. \u201cI have to believe that in the future it\u2019s not all AI or no AI,\u201d she says. \u201cIt\u2019s somewhere in between.\u201d<\/p>\n

This article first appeared in The Checkup,\u00a0MIT Technology Review\u2019s\u00a0weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,\u00a0sign up here<\/a>.
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