| | | | |  | | By Erin Schumaker, Daniel Payne, Carmen Paun and Ruth Reader | | Presented by |  | | | | | | | 
Psychedelic therapy could be a growth industry judging by a new training program. | AFP via Getty Images | Social workers are prepping for the psychedelic revolution. The Food and Drug Administration has set a target date of Aug. 11 for a decision on the first drug application for talk therapy combined with MDMA, commonly called ecstasy, as a treatment for post-traumatic stress disorder. Should the FDA approve Lykos Therapeutics’ application, universities that train social workers, psychologists and psychiatrists want to be ready. The Columbia University School of Social Work is rolling out a 25-person psychedelic-assisted training program this fall, which includes 120 hours of classroom coursework and 600 hours of clinical experience in a ketamine clinic. Unlike independent training programs, which can run thousands of dollars per course, Columbia isn’t charging its masters’ students extra, said Heidi Allen, the school’s associate dean for research. Why it matters: There’s already a lack of mental health providers, with half of the U.S. population living in areas that have a shortage, according to a report by the National Center for Health Workforce Analysis. “Without addressing the fundamental drivers of access to care, innovative new treatments simply widen existing disparities,” Allen told Erin. Wide angle: Last month, the nonprofit mental health advocacy group BrainFutures hosted a roundtable in New York that brought together representatives from disciplines like nursing, psychiatry and psychology from 10 universities, including Columbia, to share the models and curricula they’re developing for psychedelic-assisted therapy and to learn from one another. Even so: There’s no guarantee the FDA will approve the therapy/MDMA application. The Institute for Clinical and Economic Review, an independent, nonpartisan expert review panel, painted a negative picture of Lykos’ application in a draft report released in March. However, the group said the draft shouldn’t be interpreted as a final assessment of the treatment as it still has more evidence to review. Flags raised by the report included safety, ethical and cost concerns. The report also projected difficulty in widely implementing the treatment.
| | A message from The Michael J. Fox Foundation for Parkinson's Research: Help create a world without Parkinson's. Learn more. | | | | | | | THE GOLD STANDARD OF HEALTHCARE POLICY REPORTING & INTELLIGENCE: POLITICO has more than 500 journalists delivering unrivaled reporting and illuminating the policy and regulatory landscape for those who need to know what’s next. Throughout the election and the legislative and regulatory pushes that will follow, POLITICO Pro is indispensable to those who need to make informed decisions fast. The Pro platform dives deeper into critical and quickly evolving sectors and industries, like healthcare, equipping policymakers and those who shape legislation and regulation with essential news and intelligence from the world’s best politics and policy journalists.
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Brooklyn, N.Y. | Erin Schumaker/POLITICO | This is where we explore the ideas and innovators shaping health care. If you don’t get to do much exercise, climb the stairs. People who climb stairs regularly had a nearly 40 percent lower likelihood of dying from heart disease, compared to those who didn't, according to an analysis presented at a European Society of Cardiology conference, NPR reports. 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.
| | | | A message from The Michael J. Fox Foundation for Parkinson's Research:   | | | | | | |  AI may offer new hope to those suffering from genetic disorders, a study found. | Getty Images | | Artificial intelligence can help diagnose genetic disorders, improving the accuracy of traditional diagnostic methods, according to new research published in NEJM AI. How so? Researchers from Texas Children’s Hospital and Baylor University used a machine-learning program trained on 3.5 million variants from diagnosed cases. The system identified 57 percent of diagnosable cases, the authors found, with a 98 percent precision rate. (The current diagnostic accuracy rate for genetic disorders is estimated at 30-40 percent.) Even so: The system has limitations: It can’t analyze certain types of genetic variations. That could change if it’s integrated with other language-focused AI systems, the authors suggest. Why it matters: The program offers hope to patients whose diseases haven’t been diagnosed through traditional methods and could help scientists identify new disease-causing genes.
| | A message from The Michael J. Fox Foundation for Parkinson's Research: We can see a future without Parkinson's. Help get us closer this Parkinson's Awareness Month. Learn more. | | | | | | |  When it comes to coding medical bills, a human better remain in the loop for now, researchers found. | Getty Images | Health providers are enthusiastic about advanced artificial intelligence’s potential to tabulate their work so they can bill insurers more efficiently. But a new study in NEJM AI suggests caution about AI’s usefulness in clinical coding. The researchers found the AI models they tested were prone to making big mistakes. How so? Researchers at the Icahn School of Medicine at Mount Sinai in New York City, Tel Aviv University and Sheba Medical Center in Israel found that the models — OpenAI’s GPT-3.5 and GPT-4, Google’s Gemini Pro and Meta’s LLaMa2-70b Chat — miscoded work regularly. GPT-4’s coding was more accurate than the other models, but even so, its codes were incorrect in most cases. Depending on the coding system, GPT-4 chose the correct code between 30 percent and 50 percent of the time. All the systems were prone to creating nonexistent codes. The researchers said the large-language models shouldn’t be used for medical coding without further research and improvements. Even so: Some companies are developing systems tailored to work in a medical environment with hopes they could be more reliable than the offerings in the study. And some AI and health researchers have suggested that problems could be resolved relatively quickly.
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