Harry W Severance, MD’s Post

Across the globe, nearly 50% of doctors and nurses are gearing up to harness the power of generative AI to bolster their clinical decisions. The 'Clinician of the Future 2023' report from Elsevier Health revealed:- - The Tech-Ready Clinician - A whopping 73% of healthcare professionals believe that expertise in digital health technologies will be paramount in the coming years. - A Real Need - With clinician shortages being a red flag in North America and Europe, 54% of respondents point towards an acute shortage of nurses and 45% highlight doctor shortages. This puts into perspective why tech solutions, like generative AI, are much in demand. - Generative AI & Decision Making - From a mere 11% today, about 48% of clinicians anticipate generative AI assisting clinical decisions within the next 2-3 years. - Global Disparities - Clinicians from China are most bullish about AI, with 53% rooting for generative AI tech, in contrast to 42% from the US and 34% from the UK. As healthcare pivots to a digital-centric paradigm, this report underscores that the global medical workforce is not only receptive to technologies like generative AI but also identifies them as catalysts to transform patient care now and in the foreseeable future. #healthtech #aiinhealthcare https://hubs.ly/Q022sQDl0

The American College of Physicians (ACP) has issued a policy position paper with 10 recommendations on the use of AI and machine learning in healthcare applications like clinical documentation, diagnostic imaging, and clinical decision support. The ACP states that AI should complement, not replace, clinicians' decision-making. It advocates for transparency when AI is used, prioritizing patient privacy and data confidentiality, and ensuring clinical safety, effectiveness, and health equity. The ACP recommends implementing a continuous improvement process with real-world testing and peer-reviewed research. It also suggests using AI to reduce clinician burden in tasks like patient intake and scheduling. Overall, the ACP aims to provide oversight and regulation for the increasing use of AI tools in medicine. https://lnkd.in/e_MyJRew #healthcare #healthcareinnovation #healthcareit #healthcareai #ai #genai #generativeai

Discover how AI and ML are revolutionizing healthcare! Our latest blog delves into the integration of advanced technologies in clinical practices, enhancing diagnostic accuracy and patient management. Read more: The Future of Healthcare https://lnkd.in/ghUzDUiY #HealthTech #AI #MachineLearning #HealthcareInnovation

Healthcare is complex, expensive, and high stakes. The adoption of high-technology in healthcare is often done with the goal of making healthcare simpler, cheaper, and less risky. However, for any substantive technological intervention, the benefits are often delayed while disruption in existing work processes and the unintended consequences sour the short-term experience (think EMR/EHR adoption post HITECH act). Will Generative AI in healthcare be different? Healthcare executive and emergency physician, Zayed Yasin, has written a series of very interesting Substack articles on how to think about this question. Over the next few posts, I will briefly comment on Zayed's articles. I read these articles in 2023 and am revisiting them as Zayed Yasin will be giving a talk at University of Pittsburgh Katz Graduate School of Business in our Gen AI industry expert series. In the first article in the series, "Why Healthcare GenAI is not your father's AI," Zayed makes the assertion that traditional predictive AI had limited success in healthcare as it focused primarily on facilitating clinical decisions with limited precision and poor explainability. Generative AI, he argues, is different as it "does work" for the physician, unburdening them from "low-value scut work that drive burnout, cost, and poor quality care." Please read the article here: https://lnkd.in/e7bCBWYf

Speaking on use-cases and their strategic AI focus, Stanford Health Care CIO, Michael Pfeffer, MD, notes in this interview with Beckers: 1) AI/EHR integration for better efficiency in clinician administration. "...we want to deliver predictive AI through our electronic health record platform, easing the administrative burden on our clinicians." 2) AI education initiatives. "We also want to deliver knowledge through our business functions to our end users via our IT service management platform..." 3) AI patient education, engagement, and guidance. "...we've added numerous patient journeys, with the latest being "procedures" that guide patients throughout their perioperative experience." 4) Clinical trial efficiency. "Streamlining and automating aspects of our clinical trials management life cycle is another area we're focused on..." 5) Medical education and content development. "...we're looking to develop and implement new opportunities for medical education using AI and sophisticated content development." Bonus) Developing the compute infrastructure necessary to keep up with AI. "we're working on really ensuring that our researchers have the necessary foundational compute and storage needs for the cutting-edge health and life sciences discoveries that are being accelerated with new AI capabilities." Read the full interview, where Dr. Pfeffer also speaks about the AI regulatory environment an how they piloted generative AI chatbots to respond to patient messages. VVV

English version Artificial Intelligence (AI) in Medicine: Study Reveals Concerns and Perspectives of Healthcare Professionals Recently, a study involving 1,353 doctors was released as part of the Corporate Responsibility Program of Fine Research Latin America, focusing on the views of medical professionals from Latin America and Spain regarding AI. While the link is provided below, here are some highlighted findings: - 53% of doctors are familiar with AI in medical practice; - Of those familiar, 50% have interacted with chatbots or virtual assistants; - Perceptions about AI remained consistent between Spain and Latin America. Emerging Concerns include: - Interference in the Doctor-Patient Relationship: Doctors expressed fears that AI might distance the human connection; - Risk of Self-diagnosis: Concerns about patients interpreting diagnoses without medical supervision; - AI Reliability: Worries include diagnostic errors, accountability, and data security; - Inequality in Access: Fears of widening inequality in medical care. Overall: - 80% predict that AI will revolutionize their specialties, but 53% of them view this with apprehension; - 63% feel uncomfortable with the current AI tools; - 47% prefer to wait for more information before adopting the technology in their practices. So, what do you think?? #innovation #artificialintelligence #telehealth #digitalhealth #chatgpt #openai #digitalhealth

The Critical Need for a Chief Health AI Officer: Bridging Clinical Medicine and Artificial Intelligence Navigating the AI Revolution in Healthcare AI, particularly generative AI (genAI) systems like ChatGPT, is reshaping healthcare by streamlining operations, enhancing clinical decision-making, and improving patient outcomes. The number of FDA-approved AI-enabled medical devices surged by 30% in 2023, highlighting the growing impact of AI in healthcare. However, the integration of AI into healthcare systems is fraught with challenges. These include ensuring the reliability, ethical use, and security of AI tools, as well as maintaining compliance with rapidly evolving regulations. The Role of the Chief Health AI Officer The CHAIO is tasked with developing a comprehensive AI strategy aligned with the organization's goals, identifying high-impact use cases, and ensuring effective implementation. This role requires a deep understanding of both clinical medicine and the latest advancements in AI, machine learning, and data science technologies. The CHAIO must work closely with leaders in clinical informatics, data management, bioethics, and hospital operations to ensure the seamless integration of AI into existing health informatics streams. Strategic Leadership and Cross-Functional Collaboration One of the CHAIO’s primary responsibilities is to guide the organization in achieving a return on AI investments by identifying high-impact use cases and recommending technologies that are fit for purpose. Collaboration with AI companies, research institutions, and healthcare organizations is crucial for accessing state-of-the-art technology and expertise. Governance and Ethical Application The CHAIO must establish and expand governance structures and policies to ensure the responsible application of AI-enabled technologies. This involves rigorous testing and validation processes, continuous safety monitoring, and staying abreast of regulatory changes and standards. Ensuring the trustworthiness of AI tools, whether procured from a vendor or internally developed, is essential for maintaining patient safety and delivering value. The Future of AI in Healthcare As AI continues to advance, the CHAIO’s role will become increasingly critical. Treating AI as merely another technology tool risks squandering resources and even causing patient harm. Therefore, healthcare organizations must formulate a clear AI strategy encompassing data infrastructure, talent development, technology selection, safe practices. Conclusion The establishment of the CHAIO role is a crucial step toward data-driven and AI-optimized healthcare systems.The CHAIO, with their deep understanding of clinical medicine and AI, is uniquely positioned to lead this transformation, ensuring that AI's benefits are harnessed while mitigating its risks. #AI #healthcare #newhorizons Credit: NEJM AI ( https://lnkd.in/gPeu4dD4)

How Does AI Work For Medical Note Taking and Risk Scoring? (Augmedix, HDAI) — Faces of digital health - Faces of Digital Health #AI in Medical Note Taking and Risk Scoring Augmedix, in collaboration with HDAI, is using artificial intelligence (AI) to revolutionize medical note taking and risk scoring in healthcare. By leveraging AI technology, healthcare providers can improve efficiency, accuracy, and patient outcomes. #The Role of AI in Medical Note Taking AI-powered medical note taking systems, such as Augmedix, use natural language processing (NLP) algorithms to transcribe and summarize patient encounters in real-time. This technology allows healthcare providers to focus more on patient care instead of spending excessive time on documentation. #Benefits of AI in Medical Note Taking The use of AI in medical note taking offers several advantages. It reduces administrative burden, improves accuracy, enhances ai.mediformatica.com #data #model #augmedix #health #medical #healthcare #risk #documentation #naibchamoun #prediction #this #training #digitalhealth #healthit #healthtech #healthcaretechnology @MediFormatica (https://buff.ly/49jaiTT)

AI is set to redefine healthcare 🏥, causing quite a stir. I'm talking about Large Language Models (LLMs) that can potentially: 1. Answer complex medical queries. 2. Give clinicians a break on tedious tasks that take up valuable time. But let's not pop the champagne 🍾 just yet. LLMs still have learning to do. It is essential to be aware of their limitations and to take steps to keep them updated with new knowledge📘 to ensure that they are accurate and reliable. I would also add that LLMs are still under development, and there is no one-size-fits-all solution for updating them with new knowledge. The best approach will vary depending on the specific LLM and its intended use case. What if AI brains 🧠 and clinicians 👩🏽⚕️ joined forces? Intriguing. Find out more in this captivating discussion between Kirsten Bibbins-Domingo, PhD, MD, MAS of JAMA, and Google Health's Chief Clinical Officer Michael Howell, MD, MPH. https://lnkd.in/g9SQTxJU

Google DeepMind has introduced a new AI model called AMIE (Articulate Medical Intelligence Explorer) with the potential to transform the patient-doctor relationship and healthcare in general. This AI aims to assist both patients and physicians by providing clear explanations of medical conditions during wellness visits. AMIE is not designed to replace human doctors but can serve as a valuable aid. It can help individuals better understand symptoms, simplify medical explanations, and offer a second opinion, enhancing the diagnostic process. However, experts emphasize that AI will support doctors rather than replace them. Trained physicians' expertise remains crucial for final diagnoses and treatment plans. To train AMIE, Google's team fed it real-world medical texts, physician-patient dialogues, summaries of ICU notes, and medical reasoning questions. They also used a simulated diagnostic environment where AMIE learned from its own mistakes through self-play loops. Although no substitute for human experience, AMIE's continuous learning and exposure to diverse cases could lead to "superhuman diagnostic performance." In a trial against human physicians, AMIE demonstrated greater diagnostic accuracy and performance, albeit in a text-based chat format. The future may see AMIE expanding its capabilities, including video chats, and addressing issues of equity and ethics. Medical schools are encouraged to incorporate AI literacy into their curriculum to prepare future doctors for responsible AI integration in clinical practice. #ai #healthcare