| | | | |  | | By Erin Schumaker, Daniel Payne and Ruth Reader | | | | | 
The WHO's got a bot of its own. | Fabrice Coffrini/AFP via Getty Images | For a cautionary tale on the dangers of health care by chatbot, look no further than the World Health Organization. The WHO’s bot, SARAH or Smart AI Resource Assistant for Health, is supposed to provide advice to the public on healthy living based on the WHO’s expert guidance. But a POLITICO review found SARAH wildly inconsistent. The bot was prompt, courteous and sometimes brilliant, but on other occasions, deeply unhelpful. How’s that? Hours of testing found SARAH often gives contradictory answers to the same queries. When POLITICO reported specific symptoms, such as chest pain, SARAH offered to help us find a list of local health care providers. But after it offered to share their contact details, it inexplicably returned to one of its favorite topics: the health benefits of quitting tobacco. When asked again to share the details of health care providers, SARAH not only failed to provide the list but said it couldn’t provide any specific contact information. SARAH’s shortcomings are most troubling when it comes to severe mental health crises and suicidal ideation. When asked about suicide, SARAH was prone to give the phone number of the U.S. National Suicide Prevention Lifeline, which isn’t much help to users outside of the United States. Even so: POLITICO observed that the more time spent with SARAH, the better and more reliable its answers became. But to its critics, SARAH just isn’t dependable enough to be useful. In a letter to the WHO, Health Action International, a Dutch advocacy group, said SARAH regularly dispenses poor-quality answers and broken links — and it wants the bot taken down. The WHO’s take: In an email to POLITICO, Alain Labrique, director of the WHO’s digital health and innovation department, responded: “We welcome all feedback about the SARAH tool, which could be used to improve and strengthen health promotion initiatives — and our understanding of the role of AI in these efforts.”
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Washington, D.C. | Shawn Zeller/POLITICO | This is where we explore the ideas and innovators shaping health care. Animals still have an evolutionary edge over robots, according to new research published in Science Robotics. "A wildebeest can migrate for thousands of kilometres over rough terrain, a mountain goat can climb up a literal cliff, finding footholds that don't even seem to be there, and cockroaches can lose a leg and not slow down," researcher Max Donelan said in a statement. “We have no robots capable of anything like this endurance, agility and robustness.” Share any thoughts, news, tips and feedback with Carmen Paun at cpaun@politico.com, Daniel Payne at dpayne@politico.com, Ruth Reader at rreader@politico.com or Erin Schumaker at eschumaker@politico.com. Send tips securely through SecureDrop, Signal, Telegram or WhatsApp.
| | |  Khan said doctors want to be freed from noncompete agreements. | Chip Somodevilla/Getty Images | Federal Trade Commission Chair Lina Khan and her Democratic colleagues stressed doctors’ support as they moved to ban noncompete agreements on Tuesday. But the reaction from doctors’ groups that followed was mixed, reflecting the reality that some doctors run large practices that use the contracts to stabilize their workforce, while other doctors are employees who’d like more freedom to quit. The split: An advocacy group representing large group practices said that banning noncompetes would make it more difficult to invest in the doctors they employ. “The future of health care is group practices and integrated systems of care,” said Darryl Drevna, senior director of regulatory affairs at the advocacy group, AMGA, in a statement. “AMGA members strive to be attractive employers, and part of that is the significant investment in training, facilities, and other members of the care team. The standard the FTC adopted dismisses those concerns entirely.” Close to half of doctors in group practices are bound by noncompetes, which typically bar them from leaving for rivals within driving distance. On the other side of the issue, Dr. Steven P. Furr, president of the American Academy of Family Physicians, praised the FTC’s decision. “This decision puts patients first and ensures family physicians can pursue opportunities that value their expertise and continue to provide high-quality care that their communities need,” he said in a statement. The American Medical Association, the most prominent physicians’ group, hasn’t yet commented on the new rule. As our Ben Leonard reported, the AMA's House of Delegates voted to oppose noncompetes for doctors at for-profit and nonprofit hospitals, hospital systems or who are employed by staffing firms. The AMA has noted that some doctors who are employers and own physician practices may support "reasonable noncompetes," while employed physicians might support banning the clauses. Why it matters: Doctors have told POLITICO that banning noncompetes would help restore the power balance between garden-variety doctors and the mega-groups — often owned by private equity firms — which have gobbled up and consolidated physicians practices in recent years. Without having to worry about retention, employers aren't motivated to improve workplace conditions or address concerns about burnout or patient safety, some said. But the large practices, like hospitals, say they need the contracts to retain talent, especially given the health worker shortages exacerbated by the pandemic. What’s next? The U.S. Chamber of Commerce and the Business Roundtable, both of which have hospitals that employ noncompete agreements among their members, sued on Wednesday in federal district court in Dallas, arguing that the FTC exceeded its authority in finalizing the rule.
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A microscopic image of cancer cells in the cervix. | American Cancer Society via Getty Images | Researchers at the National Institutes of Health are working on an artificial intelligence tool to help doctors more precisely match effective cancer drugs to patients. Why it matters: The standard method for matching involves bulk sequencing DNA and RNA using tumor cell averages. But tumors contain more than one type of cell, and different cell types and subpopulations don’t respond similarly to drugs — one explanation behind why certain medications don't help some patients. A newer method, single cell-RNA sequencing, can lead to higher-quality data and better drug responses, but it’s more expensive than bulk sequencing and not widely available. Now what? AI might help bridge that accessibility gap. A small, early-stage, proof-of-concept study, published in the journal Nature Cancer, suggests that single cell-RNA sequencing aided by AI might one day help doctors predict whether a person’s cancer cells will respond to a specific drug. The researchers tested whether transfer learning, or using an existing model on a new problem, would work for cancer-drug matching. They built AI models for 44 FDA-approved cancer drugs, which accurately predicted how individual cells would respond to single drugs and drug combinations. They then tested the method on published patient data and found that if even one subpopulation of cells were resistant to a drug, the patient wouldn’t respond to the medication. "Our hope is that being able to characterize the tumors on a single-cell resolution will enable us to treat and target potentially the most resistant and aggressive [cells], which are currently missed," Dr. Eytan Ruppin, study author and chief of the Cancer Data Science Laboratory at the National Cancer Institute, told Erin. What's next? The researchers believe the tool would be more accurate if single-cell RNA sequencing data became more widely available. They’ve made their model, PERsonalized Single-Cell Expression-based Planning for Treatments In Oncology, or PERCEPTION, and a user’s guide available on GitHub, a website where software developers share code. "Our hope is that our approach, which is a first of its kind, will pave the way for clinical trials that will test the ability to assign patients the treatments based on single-cell data," Ruppin said. | | | | Follow us on Twitter | | | | Follow us | | | | |
