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Healthcare AI News 4/3/24

April 3, 2024 Healthcare AI News 1 Comment


Plastic surgeon Robert Pearl, MD, who was executive director and CEO of The Permanente Medical Group through 2017, predicts that ChatGPT’s eventual ability to remember and use information across multiple chat sessions — its “context window” — will be significant in healthcare. He says that while its current capacity won’t hold an average medical record, generative AI systems are expected to become 30 times more powerful in the next few years, which along with GPTs, will allow records from multiple providers to be consolidated to provide patients with diagnosis and treatment suggestions. He also expects the extended memory to improve patient monitoring with its capability to look back into historical clinical status and to issue real-time alerts when established best practices are not followed.


The World Health Organization launches Sarah, an AI-powered health information avatar for consumers. Sarah replaces a previous WHO non-AI tool called Florence that provided public health information. Sarah is available online.

Epic is developing an AI validation suite to help health systems evaluate and monitor the performance of AI models, both third party and self developed.

OpenAI offers access to ChatGPT 3.5 without requiring registration, although functionality is limited and content safeguards are expanded over the paid version.


A new KLAS report looks at early use of healthcare AI, concluding that:

  • ClosedLoop’s predictive modeling leads the market in performance, especially with ACO and health plan users.
  • Customers of second-place Epic are expanding beyond clinical use cases into operational and financial areas, with good employee adoption because of integration with EHR workflows. Some customers complained about Epic’s pricing and its subpar ability to incorporate outside data.
  • Oracle Health customers were split. Satisfaction was good with the company’s cloud plans and its use of clinical data, but some customers complain that support quality and nickel-and-diming has gotten worse since Oracle acquired Cerner.
  • Health Catalyst customers say the product is robust, but half of them believe that the product fails to deliver on its potential because of insufficient training and support.



Amazon ends its Just Walk Out checkout-free experience at its Amazon Fresh grocery stores, which will be replaced by in-cart scanners that customers use themselves. A report by The Information says that while the Just Walk Out system seemed automated and AI powered, 1,000 offshore workers served as low-paid remote cashiers in monitoring shoppers via video camera and manually ringing up items. Social media wags labeled the failed experiment as API – A Person in India. Amazon rolled the system out to hospitals in January 2024 for cashier-less employee purchases, with St. Joseph’s / Candler as its first customer.


Healthcare AI company John Snow Labs releases a no-code solution that allows healthcare domain experts to train, tune, test, and share models without help from data scientists. The company says that creating small, task-specific models can be used to train other models, are cheaper to run, and can operate behind an organization’s firewall. They can also include human-in-the-loop oversight.


FDA grants marketing clearance to the sepsis detection tool of Prenosis, which applies AI to biomarker and EHR clinical data to assess sepsis risk.



Penn researchers find that AI analysis of Facebook postings is three times less likely to accurately predict depression among black American users as compared to white. The model uses prior findings that white people who have higher levels of depression use more first-person singular pronouns — along with words that suggest isolation, self-criticism, worthlessness, anxious-outsider, and despair — but the model performed poorly when analyzing posts from people who are black. The authors note that their study illustrates the need for caution when applying AI in mental health settings.


HFMA notes the “battle of the bots” as hospitals that have been outgunned by payers that used technology to deny or delay payment are implementing AI to beef up revenue cycle management. Examples of provider use of AI:

  • Using robotic process automation to ensure that claims are clean and to manage work queues (Luminis Health).
  • Reducing RCM headcount by 30 FTEs by using AI bots (Mayo Clinic).
  • Reducing authorization-related denials by using bots to notify payers when patients are admitted (Care New England).
  • Increasing administrative efficiency by using Copilot for Microsoft 365 and using RPA to save labor in authorization, registration, credentialing, and billing workflows (Corewell Health).


Mr. H, Lorre, Jenn, Dr. Jayne.
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Currently there is "1 comment" on this Article:

  1. The capabilities mentioned as future capabilities of LLMs, such as chat GPT, are available today.

    There is no need to wait for GPT to catch up and provide a non-transparent medical data analysis when Quippe, a Medicomp product, is currently doing a fully transparent model.

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