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Tag: Health Tech

  • STAT+: The rise of the AI-native radiology practice

    STAT+: The rise of the AI-native radiology practice

    Mario covers technology in health care, including FDA regulation of artificial intelligence; how Medicare pays for health tech; the use of AI in clinical care; mental health chatbots; and consumer wearables. He’s also the co-author of the free, twice weekly STAT Health Tech newsletter. You can reach Mario on Signal at mariojoze.13.

    Good morning health tech readers!

    It’s gonna be a great day. 

    Reach me: [email protected]

    The Medicare RPM backlash

    Medicare’s plan to rein in spending on remote patient monitoring has prompted surprising pushback from insurers. Under these billing codes, Medicare pays health care providers to track and manage the health of their patients using connected devices like blood pressure cuffs.

    As I report in a new story, UnitedHealth Group, CVS Health, and Kaiser Permanente all wrote letters opposing a medicare proposal that such remote-monitoring services be rendered directly by employees of the provider billing for it. Currently much of RPM is delivered by vendors working under the supervision of the billing providers.

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  • STAT+: In radiology, AI is blurring the line between technology development and clinical practice

    STAT+: In radiology, AI is blurring the line between technology development and clinical practice

    Katie covers the impact of health technology on patients, clinicians, and businesses. Her stories explore the price tag of clinical AI, digital health at the FDA, and the boom in direct-to-consumer telehealth. Confidential tips can be sent on Signal at palmer.01.

    A decade ago, machine learning scientist and Nobel laureate Geoffrey Hinton made a proclamation that still puts radiologists on edge.

    “If you work as a radiologist,” the so-called godfather of artificial intelligence said at a conference, “you’re like a coyote that’s already over the edge of the cliff, but hasn’t yet looked down.” Deep learning was getting so good, so fast, said Hinton, that “people should stop training radiologists now.” In five years — ten, max — AI would do better than radiologists, he predicted. 

    The clock has run out on that prediction. But the field of radiology isn’t just staring at its shoes, waiting to see how technology upends the profession. Instead, a growing number of radiology practices, in particular outpatient and teleradiology groups, are aggressively embracing AI: developing and acquiring their own tech, deploying it in-house, and marketing their “AI-native” capabilities to radiologist employees and hospital customers alike. 

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  • STAT+: AI doomerism: Here’s how to make sense of it

    STAT+: AI doomerism: Here’s how to make sense of it

    This is the web edition of STAT’s AI Prognosis newsletter, our guide to artificial intelligence in health care and medicine. Sign up to get it delivered in your inbox every Wednesday. 

    *Bernie Sanders voice* I am once again asking you to … forward this email to a friend! Non-subscribers can now sign up to get (a truncated version of) AI Prognosis. Tell ya buddies and coworkers!

    Also, tell your buddies about this essay from our new trust-in-science reporter, Nick Florko. Faced with health problems, he’s tried diets, supplements, and peptides — he understands the allure of non-scientifically backed treatments, and wants to listen to skeptics as he writes about doubt, misinformation, and distrust.

    Making sense of AI doomerism

    Over the last couple weeks, the fervor about whether AI will kill us all and needs to be slowed has continued on at a rolling boil.

    At STAT, we’ve discussed whether we need to write about it. But I have qualms: Firstly, the kind of nefarious AI that could potentially lead to human extinction is so far removed from still-error-prone health care AI that it’s almost impossible to talk about both at the same time.

    Then: Is this all marketing, as Anthropic and OpenAI prepare to go public? Are all of the recently disclosed AI safety incidents actually just examples of AI companies’ basic incompetence at cybersecurity and infrastructure skills, packaged to make the AI look impossibly smart?

    And then there’s the matter of finding someone who knows enough about AI to talk about it knowledgeably, but who also doesn’t have any incentive to frame it one way or another. (More on that in the next section.)

    In today’s issue, I’ll refer you to a few good reads in a few different areas (general AI, health care, and biology) to help make sense of this.

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  • STAT+: UnitedHealth, CVS push back on Medicare plan to curb remote patient monitoring

    STAT+: UnitedHealth, CVS push back on Medicare plan to curb remote patient monitoring

    Mario covers technology in health care, including FDA regulation of artificial intelligence; how Medicare pays for health tech; the use of AI in clinical care; mental health chatbots; and consumer wearables. He’s also the co-author of the free, twice weekly STAT Health Tech newsletter. You can reach Mario on Signal at mariojoze.13.

    Major insurers are pushing back on a Medicare proposal that would significantly disrupt how many doctors bill for tracking the health of patients using devices like connected blood pressure cuffs, scales, and blood glucose meters. These remote monitoring services help patients manage a range of medical conditions, including hypertension, diabetes, and heart failure.

    UnitedHealth Group, CVS Health, and Kaiser Permanente all wrote letters to the Centers for Medicare and Medicaid Services opposing a proposal that would require that remote patient monitoring care be delivered by direct employees of the practice that is billing for them — effectively banning providers from using contractors for the care. All of these groups operate both insurers and care organizations.

    The opposition from UnitedHealth Group is notable in particular because the company’s insurance subsidiary, UnitedHealthcare, recently attempted to stop paying for most remote patient monitoring “due to insufficient evidence of efficacy.”

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