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Healthcare AI News 8/2/23

August 2, 2023 Healthcare AI News No Comments

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Duke Health will create an AI Innovation Lab and Center for Excellence in partnership with Microsoft, with one of its research topics being the reliability and safety of generative AI in healthcare. Duke Health will use Azure and its OpenAI Service.

The British Standards Institution issues guidance for using AI in healthcare that includes criteria for evaluating products for clinical benefit, performance standards, safe integration into clinical environments, ethical considerations, and equitable social outcomes.

The Australian Medical Association, which previously warned doctors to stop using ChatGPT to write medical notes because it does not protect patient confidentiality, says that Australia lags other countries in regulating AI. It calls for clinicians to always make final decisions and to obtain patient consent before using AI for their treatment or diagnosis.


Business

Using synthetic patient data for research – applying AI to convert real medical records to broader sets of realistic but artificial data that involves no privacy issues – is appealing, but the industry is challenged to create those data sets while preserving many relevant variables so that the results reflect real-life situations. The WSJ article also notes that most of the data vendor markets are young startups, as big cloud providers that might be a more comfortable choice for customers haven’t shown an interest in that market so far.

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Forbes profiles OpenEvidence, which collects current medical data before answering questions, an “open book” approach that works around the expensive problem of constantly retraining AI models, potentially competing with human-edited reference databases such as Wolters Kluwer UpToDate. OpenEvidence analyzes 31,000 peer-reviewed journals from the National Library of Medicine, weighted by impact factor, and places their content into the company’s retrieval database within 24 hours. Physicians who register can test the system by asking their own questions. The founder’s previous company developed an AI-powered tool that analyzes the stock market to identify arbitrage opportunities. OpenEvidence is a Mayo Clinic Platform Accelerate company.

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Healthcare talent software and staffing company Aya Healthcare acquires two AI software companies whose tools forecast patient demand and staffing needs.


Other

Venture capital firm Andreessen Horowitz says that AI’s biggest impact will be in healthcare, predicting that the industry will jump from fax machines straight to AI similar to how the developing world skipped credit cards in going from cash to mobile payments. It says that any new technology must be 10 times better than whatever it displaces since marginal improvements aren’t worth the effort, noting that while enterprise software failed to clear that 10x bar in healthcare, AI does so easily. It predicts that AI can’t fail because it can help address clinician shortages and reduce costs while saving lives.

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Former FDA Commissioner Scott Gottlieb, MD says that AI will perform some of the activities of doctors “sooner than we think.” He sees four areas of AI usage: (1) processing claims or creating and analyzing medical records, such as Amazon HealthScribe; (2) analyzing medical images and ECGs; (3) providing clinical decision support using patient-specific data; and (4) AI operating as an independent tool to diagnose and prescribe, although he admits that is unlikely any time soon given regulatory caution. He says that using AI in a clinician-supporting role won’t lower costs because healthcare is a people-centric business where workers are paid increasingly more despite no change in their productivity (the Baumol effect), with no cost improvement unless AI replaces doctors completely.

A NEJM perspective piece says that medical educators should take an activist approach to integrating AI into physician training, because if they don’t, external forces that are motivated by efficiency and profits will do it for them. The authors question the role of cognitive apprenticeship when medical students will likely use AI-powered chatbots on their first day of training and how lifelong learning fits with using AI to  immediately and reliably answer questions at the point of care.


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