{"id":21712,"date":"2026-04-24T09:31:13","date_gmt":"2026-04-24T09:31:13","guid":{"rendered":"https:\/\/ideainthebox.com\/index.php\/2026\/04\/24\/health-care-ai-dont-know-actually-helps-patients\/"},"modified":"2026-04-24T09:31:13","modified_gmt":"2026-04-24T09:31:13","slug":"health-care-ai-dont-know-actually-helps-patients","status":"publish","type":"post","link":"https:\/\/ideainthebox.com\/index.php\/2026\/04\/24\/health-care-ai-dont-know-actually-helps-patients\/","title":{"rendered":"Health-care AI is here. We don\u2019t know if it actually helps patients."},"content":{"rendered":"
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I don\u2019t need to tell you that\u00a0AI is everywhere<\/a>.<\/p>\n

Or that it is being used, increasingly, in hospitals. Doctors are using AI to help them with notetaking. AI-based tools are trawling through patient records, flagging people who may require certain support or treatments. They are also used to interpret medical exam results and X-rays.<\/p>\n

A growing number of studies suggest that many of these tools can deliver accurate results. But there\u2019s a bigger question here: Does using them actually translate into better health outcomes for patients?<\/p>\n

We don\u2019t yet have a good answer.<\/p>\n

That\u2019s what Jenna Wiens, a computer scientist at the University of Michigan, and Anna Goldenberg of the University of Toronto, argue in a paper<\/a> published in the journal Nature Medicine<\/em> this week.<\/p>\n

Wiens tells me she has spent years investigating how AI might benefit health care. For the first decade of her career she tried to pitch the technology to clinicians. Over the last few years, she says, it\u2019s as though \u201ca switch flipped.\u201d Health-care providers not only appear much more interested in the promise of these technologies, they have also begun rapidly deploying them.<\/p>\n

The problem is that many providers aren\u2019t rigorously assessing how well they actually work.<\/strong><\/p>\n

Take \u201cambient AI\u201d tools, for example. Also known as AI scribes, they \u201clisten\u201d to conversations between doctors and patients, then transcribe and summarize them. Multiple tools are available, and they are\u00a0already being widely adopted<\/a> by health-care providers.<\/p>\n

A few months ago, a staffer at a major New York medical center who develops AI tools for doctors told me that, anecdotally, medics are \u201coverjoyed\u201d by the technology\u2014it allows them to focus all their attention on their patients during appointments, and it saves them from a lot of time-consuming paperwork.\u00a0Early studies support these anecdotes<\/a> and suggest that the tools can reduce clinician burnout.<\/p>\n

That\u2019s all well and good. But what about patient health outcomes? \u201c[Researchers] have evaluated provider or clinician and patient satisfaction, but not really how these tools are affecting clinical decision-making,\u201d says Wiens. \u201cWe just don\u2019t know.\u201d<\/p>\n

The same holds true for other AI-based technologies used in health-care settings.<\/strong> Some are used to predict patients\u2019 health trajectories, others to recommend treatments. They are designed to make health care more effective and efficient.<\/p>\n

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 <\/strong>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<\/em> or no AI<\/em>,\u201d she says. \u201cIt\u2019s somewhere in between.\u201d<\/p>\n

This article first appeared in The Checkup,\u00a0<\/em>MIT Technology Review\u2019s\u00a0weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,\u00a0<\/em>sign up here<\/em><\/a>.<\/em>
\u00a0<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

I don\u2019t need to tell you that\u00a0AI is everywhere. Or […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[226],"tags":[],"class_list":["post-21712","post","type-post","status-publish","format-standard","hentry","category-technology"],"acf":[],"_links":{"self":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts\/21712","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/comments?post=21712"}],"version-history":[{"count":0,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/posts\/21712\/revisions"}],"wp:attachment":[{"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/media?parent=21712"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/categories?post=21712"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ideainthebox.com\/index.php\/wp-json\/wp\/v2\/tags?post=21712"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}