Dr. Petra Jantzer’s Post

Last week we had both the #AIsafetysummit and the executive order from President Biden on AI. Both were interesting and showed how world leaders, and their countries, are positioning themselves around AI. This is a new frontier for everyone and there appears to be some positioning around who is leading. Biden’s AI Executive Order has had less press in the UK, and it is useful to reflect on what it specifically means for healthcare. As the article states, these appear to be the takeouts. AI Regulation and Priorities: The executive order outlines eight guiding principles for AI development, emphasizing safety, security, and adherence to “American” values, such as equity and civil rights. Healthcare Focus: Specifically for healthcare, the order mandates the Department of Health and Human Services (HHS) to establish a regulatory unit to oversee AI tools from development to post-market performance, aiming to stop harmful AI practices. The HHS is tasked with creating personalized health tools and improving health data quality and administrative processes. Notification Requirement: Companies must inform the federal government if they are developing AI models that pose national security or public health risks. The order targets any foundational model that could threaten security or health, necessitating the sharing of safety test results with the government before public deployment. Encouraging Innovation: Beyond controlling risks, the White House seeks to encourage AI's use in healthcare innovation, such as improving care access and developing new drugs. Industry Reaction: There's a mix of apprehension and support within the healthcare industry. Concerns exist that the regulation could stifle innovation and increase costs, especially in areas like deep learning, where algorithms constantly evolve. However, some view the clarification of regulations as beneficial, especially for startups in life sciences. Implementation Timeline: Federal agencies have been given a year to develop their regulatory plans for AI, indicating a rapid pace of change toward AI governance. #healthtech #airegulation #biden https://hubs.ly/Q0288XTQ0

I particularly support the idea of focusing on "meaningful use" and "explainable AI." Ensuring that AI systems are transparent and understandable for clinicians is essential for safe and effective integration into healthcare workflows. This approach not only enhances patient care but also builds trust among healthcare providers. https://lnkd.in/e-n_gMmq

This morning’s very special edition of Digital Health Wire gave us the chance to introduce the world to K Health’s new AI Knowledge Agent, a first-of-its-kind GenAI system purpose-built for the clinical setting. The AI Knowledge Agent looks and feels like a familiar medical chatbot, until you look under the hood and realize that LLMs have entered a new stage of clinical utility. Three major differentiators separate the AI Knowledge Agent from today’s standard AI apps: >It incorporates the patient’s medical history grounded by their EHR to provide highly tailored responses (a diabetic and a heart failure patient will see different answers to the same question, using their own history, potential adverse drug interactions, etc.). >It will be embedded into health systems to serve as a digital front door that intelligently routes patients to the right place to resolve their needs (reaches everything from primary care and specialists to labs and tests within the same interface). >It’s optimized for accuracy by using curated health sources, then leverages multiple specialized agents to verify the answer matches the sources and the EHR data is appropriate. Hats off to Allon Bloch Ran Shaul Ethan Fischer and the rest of the team, and make sure to check out our exclusive story for all the details ⚡ https://lnkd.in/gSG6Nqkj

How is AI transforming healthcare in 2024? We share four ways in which AI is impacting the provision of healthcare and how it’s affecting patient and provider experience. https://ow.ly/VJce50QBlBK #aiforhealthcare #generativeai #intelligentautomation ABBYY

AI is transforming healthcare, but it also raises new challenges and questions for lawmakers and regulators. Read more about this developing policy area on the CRD Associates blog "Eyes on AI," co-written by myself and CRD Partner Matt Dennis. 

Ensuring safety, transparency, privacy, and human oversight over AI technologies are just a few of the issues policy makers and regulators are reviewing. Read CRD Associates update on AI! #AI #HealthPolicy

Valuable insights in MobiHealthNews on how regulators should configure policy around AI use in healthcare from Amit Khanna, Senior Vice President and General Manager of Health at Salesforce, Dr. Michael Howell, chief clinical officer at Google, and #Welldoc’s CEO and President, Kevin McRaith. Read the article: https://lnkd.in/gRcTmuXn #DigitalHealth #HealthTech #AI #HealthcareAI

A pressing concern in healthcare: the balance between leveraging AI’s potential and ensuring clinicians don't become over-dependent on it. The approach of treating AI as a co-pilot, rather than a replacement, is particularly compelling. It underscores the need for transparency in AI processes, enabling clinicians to understand and trust the technology. This strategy not only maintains the primacy of human judgement in healthcare but also mitigates the risks of automation bias. The ongoing adaptation of AI, underscored by rigorous testing and ethical considerations, reflects a thoughtful integration of technology in healthcare, prioritising patient safety and care quality.

With consumers both optimistic and wary of AI accuracy in healthcare, building trust is crucial. What should healthcare organizations do? Engage clinicians, ensure transparency, and partner with trusted community groups. Learn ways to bridge the trust gap and unlock AI's full potential here: https://ow.ly/jcKF50StWeP

Making AI Models in Healthcare Transparent One Bite at a Time – Regulatory Talk Series | Healthcare IT Today - Healthcare IT Today #Introduction: The blog post discusses the importance of transparency in AI models in healthcare and how it can be achieved gradually. #Current Challenges in AI Transparency: The post highlights the challenges faced in ensuring transparency in AI models in healthcare. #Regulatory Requirements: It outlines the regulatory requirements that need to be met for AI models in healthcare to be transparent. #Strategies for Transparency: The blog post suggests strategies that can be implemented to make AI models in healthcare more transparent. #Benefits of Transparent AI Models: It discusses the benefits of having transparent AI models in healthcare. #Conclusion: The post concludes by emphasizing the significance of transparency in AI models in healthcare and the need for continuous efforts in this direction. ai.mediformatica.com #health #healthcare #healthit #algorithm #drfirst #technology #finalrule #transparency #ehrs #hti1 #innovation #data #digitalhealth #healthtech #healthcaretechnology @MediFormatica (https://buff.ly/435nMju)