A new study found that there is a big difference in the adoption of AI scribes across medical specialties: It was highest in community internal medicine (67%), community general pediatrics (69%), and academic neurology (53%), and lowest in academic general surgery (16%), obstetrics and gynecology (18%), and psychiatry (19%).  But what could be the reason for that? 1. Conversational vs procedural medicine AI scribes (designed to convert conversations into clinical documentation) may offer greater value when history-taking and counseling dominate an encounter, rather than physical procedures and examinations. 2. Documentation burden vs sensitivity For example, psychiatry is an extremely conversation-intensive specialty, so one might expect exceptionally high adoption. However, the very conversations that could make scribes useful are also highly sensitive.  The more suitable a clinical encounter is for transcription, the less suitable it may sometimes be for recording. 3. Community vs academic medicine Community clinicians may have more standardized, high-volume outpatient encounters and greater incentives to reduce repetitive documentation. All in all, it's great to see more evidence piling up behind AI scribes. The study: nature.com/articles/s41746-0…

I really admire figures that can describe a concept better than long manuscripts. This image is from an excellent paper in Nature by Vivek Subbiah about the future of evidence-based medicine and the design of clinical trials, all inspired by the rise of artificial intelligence. This is the era of the next generation of 'deep' medicine. "Current paradigms must be continuously challenged by emerging technology and by all stakeholders (the new generations of scientists, physicians, the pharma industry, regulatory authorities and, most importantly, patients). Disruptive innovation should lead to every clinical site being a research site, with all necessary quality checks and research as part of the standard of care. My personal view is that every major disease needs a ‘Moonshot’ program and every rare disease should have an ‘Operation Warp Speed’—both with clearly identified, sustainable goals to improve population health and address equity, diversity and global access to therapies. Methodological advances and future AI-based analyses of all data will provide deep evidence to realize the goal of personalized medicine— that is, to offer the right treatment to the right patient at the right time." The paper: nature.com/articles/s41591-0…

A bold regulatory move from Utah policy-makers as they just allowed 3 healthcare technology companies to test how their AI systems can safely prescribe and refill medications, and provide AI-augmented physical therapy plans for specific health conditions. This is a sandbox regulatory approach. The regulator allows the companies to use their technology in a sandbox-like ecosystem while they are being watched, but before being allowed to enter the market in the regular pathways. "The AI pilot agreements establish phased testing requirements, clinical oversight, escalation procedures and regulatory reporting aimed at helping Utah evaluate the safety and effectiveness of the technologies. The agreements also require the pilot companies to implement "reasonable cybersecurity protections against data leaks to minimize the risk of breach of confidential information," including best practices to address emerging threats and vulnerabilities." You will see this sandbox approach across the whole medical regulatory landscape soon. Source: bankinfosecurity.com/utah-ok…

I've been saying for years that medications will be sold with a digital companion app simply because this package increases compliance. When patients see their own data, it's easier to follow a treatment. Now the FDA issues final guidance on prescription drug apps and software. "The guidance addresses three key questions for industry: when app content is treated as FDA-required labeling versus promotional labeling, when an app should be referenced in a drug’s official prescribing information, and what companies should submit to FDA when they distribute app content to users." I hope pharma companies will see this as an opportunity to join the digital race. Here is the guidance: fda.gov/news-events/press-an…

BREAKING NEWS! The FDA just updated its list of FDA-approved/cleared AI-based medical technologies. Now they list over 1614 devices! As always, I analyzed them for you. 1) Medical specialty still has a clear winner. Radiology 1230 Cardiovascular 154 Neurology 76 Anesthesiology 30 Gastroenterology-Urology 27 Hematology 22 2) Type of submission 510(k) 1553 Premarket approval 21 De novo pathway 40 Check it out: fda.gov/medical-devices/soft…