| | | It’s been years since AI proponents started promising big returns on healthcare providers’ investments in the technology. The results have yet to catch up with the pitches. What’s the holdup? Analysts at McKinsey & Company may have the answer. “Organizations are caught between the excitement to quickly seize the opportunity and a lack of alignment on where to start, alongside general caution given the potential risks related to deploying AI,” they write in a report released Nov. 15. To help accelerate the use of AI in upgrading the consumer experience—while also boosting providers’ bottom lines—the authors propose five steps. Here are key excerpts. 1. Tackle the 70% problem of data readiness.Delivering tangible value for healthcare consumers through AI requires integrated data ready for consumption—a “challenging task that represents, on average, 70% percent of the work when developing AI-based solutions,” the McKinsey subject-matter experts write. More: ‘To surface meaningful insights, AI adopters can complement their clinical and patient data with information on social determinants of health, patient-reported outcomes, retail purchases and wellness trackers.’
2. Zero in on consumer experience priorities to ensure AI success.This is a critical step to avoid trying to do too much at once, which can limit meaningful progress, the authors point out. “To prioritize areas of focus, it is imperative to engage cross-functional leaders in the organization,” they add. ‘Clinical leadership in particular has firsthand insight on patients’ pain points and what exactly isn’t working in care delivery and consumer experience.’
3. Optimize real-time insights for AI-powered interventions. By analyzing details such as a patient’s appointment preferences and how or when they have responded to outreach, McKinsey notes, AI can tailor the timing, frequency and message themes to provide recommendations most likely to resonate. More: ‘Gen AI can further enhance the effectiveness of these timed interventions with hyperpersonalized message content.’
4. Map AI risks in healthcare and develop mitigation plans.Besides data-use transparency, organizations “can provide consumers with clear logs and documentation on AI systems, including bias mitigation strategies and training protocols such as details on the population profiles used.” More: ‘Mature, integrated data repositories built to power AI can become valuable targets for cyberattacks: 2023 broke the record for healthcare data breaches, logging some 725 breaches of 500 or more records, more than twice what was reported in 2017.’
5. Level up your team’s AI capabilities.“One way to increase the likelihood of success in AI implementation is to employ a copilot model, where employees work alongside AI tools to make incremental process improvements,” the McKinsey analysts write. “This capitalizes on AI’s speed and capacity with the checks and balances of human skill and intuition to mitigate errors and risks.” More: ‘Importantly, this process includes periods of capability testing and learnings collection within a small set of users prior to scaling across the enterprise. Such a test-and-learn tactic allows organizations to de-risk scaling and to measure impact and adoption within existing workflows.’
Read the whole thing. |
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| | | Nabla Joins the Coalition for Health AI (CHAI) to Advance AI Governance in Healthcare - Nabla is joining forces with the Coalition for Health AI (CHAI), a diverse consortium of more than 3,000 organizations, including health systems, technology developers, patient advocates, and academic institutions, dedicated to promoting responsible AI practices in healthcare. |
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| | | Buzzworthy developments of the past few days. - An influential industry group really likes President-Elect Trump’s choice of Dr. Oz for CMS administrator. And the thumbs-up of the group, AdvaMed, has much to do with emerging technologies. Mehmet Oz, MD, MBA—who is, after all, not only a TV personality but also a professor emeritus of cardiothoracic surgery at Columbia University—“has firsthand experience with medical technology and as a result understands the incredible impact these technologies can have in the lives of patients in need,” enthuses AdvaMed CEO Scott Whitaker. “And as a practitioner, he has also seen firsthand the negative impact a lack of access to these technologies can have on these same patients.” Other thought leaders aren’t convinced. “Not since the Wizard of Oz himself has there been a bigger fraud than this guy,” fumes Brad Woodhouse, executive director of Protect Our Care, a Washington-based nonprofit. MedPage Today has a reaction roundup.
- Legally speaking, healthcare is a ‘particularly devilish’ setting for AI that goes wrong or gets used improperly. Stanford Law School health policy expert Michelle Mello, JD, PhD, uses those words in a podcast posted this week. Mello backs up her point by describing a recent case that featured nurses changing shifts, using different EMR fields for the same patient and, in the process, causing key clinical notes to get missed by the algorithm. Some nurses “like to type out words instead of clicking structured boxes, so the tool was missing a lot of important information,” Mello explains before quipping: “If you’ve seen one hospital, you’ve seen one hospital.” Also sharing insights is Neel Guha, a Stanford JD/PhD candidate in computer science. He suggests healthcare AI lawsuits are starting to split into those that accuse the physician, those that target the hospital, those that blame the software developer—and those that go after any two or all three of the above at once. Audio and transcript here.
- The homeless need healthcare too. Along some of the heavily tented streets of Los Angeles, AI is helping a fortunate few gain access. The technology “is really pushing us to be that provider we were supposed to be when we were taking histories in med school,” says primary care provider and addiction medicine specialist Steven Hochman, MD. “When I’m talking to patients in the field, the tech does a phenomenal job of providing me with accurate documentation of what we talked about, which allows me to focus on my job.” Hochman works closely with Akido Labs, a healthtech company that uses AI to, among other aims, help the poor. Fast Company has the story.
- AI is the killer app for high-performance computing in healthcare. The holder of that notion has a vested interest in persuading others to see things his way, but that doesn’t mean he’s not right. “[H]ow do we improve the computer itself to be able to run not [just] the algorithms that we have now but [also] the algorithms that are yet to come?” says Camilo Buscaron, founder and CEO of Alafia AI, which recently introduced an AI supercomputer designed specifically for healthcare applications. “We have to design a computer from the ground up, with the best technology that we have in our hands today, just to support that next movement of technology.” Silicon Angle has the news plus a video interview.
- AI comes home to homecare. Innovators in the U.K. are using AI in patients’ homes as well as assisted living facilities to watch for facial expressions of pain, uneasy nights of sleeplessness, unusually frequent trips to the bathroom and all manner of possible warning signs. Others in the region are working with devices that predict and prevent falls, adjust air quality, detect when someone with dementia is dangerously confused and, yes, snitch on healthcare workers who fail to wash their hands. The Times of London looks at the spread of machines into such settings and asks: “Could smart tech save a failing system—or is it a dangerous shortcut to cutting staff numbers?”
- Healthcare is now leading generative AI adoption with $500 million in enterprise spend. That puts our sector comfortably ahead of legal services ($350M), financial services ($100M) and media/entertainment ($100M). The figures are from a report by Menlo Ventures, an early-stage venture capital firm. Menlo’s research shows enterprise spending on generative AI skyrocketed in 2024, rising from $2.3 billion to $13.8 billion, as “businesses made a decisive shift from AI experimentation to implementation.” The firm arrived at this conclusion after surveying around 600 enterprise IT decisionmakers. The authors note that optimism around the transformative potential for generative AI is high—72% of decision-makers expect broader adoption in the near term—but “enterprises remain focused on identifying high-value use cases, signaling we are still in the early stages of a large-scale transformation.”
- It would take a lot of guts for a new-ish company to battle Google in the browser market. OpenAI might have just the innards for the job. Maybe Sam Altman’s brainchild sees an opening in the wake of the U.S. Department of Justice’s argument that Google ought to halt its monopolization of online search by selling its Chrome browser. Or maybe OpenAI is feeling feisty after entering the search market with SearchGPT. (It’s unclear whether they’re sticking with that name.) In any case, the potential for a browser battle royale has a lot of people talking.
- Energy-intensive infrastructure. Electronic waste. Resource depletion. Increased consumption. Four good reasons healthcare needs to get busy reducing its environmental footprint, in the opinion of Rubin Pillay, MD, PhD, MBA, chief innovation officer and assistant dean of medicine at the University of Alabama-Birmingham. As healthcare continues to innovate with AI and digital health, Pillay puts forth in a Nov. 21 Substack post, “we must expand our understanding of ‘do no harm’ to encompass not just individual patients but [also] the health of our entire planet.”
- Recent research in the news:
- Notable FDA Approvals:
- Funding news of note:
- From AIin.Healthcare’s news partners:
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