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"Artificial intelligence has the potential to change the way we discover new medicines and treatments, the way doctors make clinical decisions, and the way patients understand and engage with their health care. But, of course, there's also novel risks, especially in the areas of data privacy, bias, and patient safety. So for good or ill, the ultimate impact of AI in healthcare will in large part depend upon the health policies that regulate and incentivize its use." ― Rory Thompson, 2023-25 Stanford Biodesign Policy Fellow The Stanford Biodesign Health Technology Innovation Policy Conference 2024 of course included a session on artificial intelligence. With AI evolving rapidly even as many questions remain about its potential impact on patient care, moderator Rohini Kosoglu, together with panelists Ramin Bastani, Robin Strongin, Russell Wald, and Lana Feng, Ph.D.,, addressed the concerns patients have and how innovators can earn their trust, as well as the ways in which government, academia, and industry can best collaborate to ensure the good of human health. Watch the replay here if you missed it https://lnkd.in/ewmxErjC #healthpolicy #healthtech #SBDHealthtechInnovationPolicy #AI

Discover the new #Microsoft #data and #AI solutions for #Healthcare. Learn how the next-generation AI and digital tools helped providers like Kry, Mount Sinai Health System and Santeon unlock insights and improve patient & clinician experiences. 👉 Download our 2-pages whitepaper to learn more: https://lnkd.in/duAS8iKz #msftadvocate #digitaltransformation #artificialintelligence

Health Systems Prioritize Artificial Intelligence Governance, Oversight Can learn from them... Health systems are increasingly prioritizing the development of artificial intelligence (AI) oversight efforts as they continue to navigate the potential promise and pitfalls of these tools in healthcare, according to a report published today and shared with HealthITAnalytics by the Center for Connected Medicine (CCM) at the University of Pittsburgh Medical Center (UPMC). [Health IT Analytics] The report, “How Health Systems are Navigating the Complexities of AI,” surveyed executives from almost three dozen health systems on their approaches to overseeing the technology. As AI rapidly advances, healthcare organizations continue to investigate how these tools can help automate administrative tasks and reduce clinical documentation burdens, among other use cases. However, this increased interest and swift development makes the pros and cons of AI in healthcare challenging to balance, as stakeholders have raised a plethora of concerns around data privacy, clinician over-reliance, patient trust, and more. More> https://lnkd.in/ewpHj6ZA #artificialintelligence #publichealth #socialchange #populationhealth #communityhealth #medicine #healthcare

According to a recent Harvard Business Review research report: ☑️ 94% of respondents agree that data-driven health care creates new opportunities for patients and doctors to benefit from more personalized healthcare approaches. ☑️ 64% of respondents agree that digital technologies for healthcare have made data integration easier. ☑️ 43% of respondents say one of the greatest inhibitors of becoming more data driven is disconnected or incompatible systems/data. At nference, we proudly partner with premier academic medical centers and health systems to unlock insights from complex healthcare data. Utilizing #FederatedAI, we de-identify and harmonize data from our partners, enabling a clearer and more comprehensive understanding of diseases and therapeutic responses. Our AI algorithms are designed to integrate and analyze diverse, multimodal, and longitudinal data across healthcare systems, addressing the challenge of disconnected or incompatible data -- and laying the groundwork for a future where healthcare is predictive rather than reactive. https://bit.ly/3YtT017 #data #Healthcare #AI #HealthTech #ClinicalTrials #MedicalAffairs #LifecycleManagement #FederatedAI #HBR

Value Based Healthcare is a dynamic concept with various models in practice. Data analytics can play a crucial role in optimizing these models. By analyzing real-world data on patient outcomes, resource utilization, and program effectiveness, healthcare providers can identify areas for improvement and refine their VBHC approaches. This data-driven approach ensures VBHC models continue to deliver high-quality, cost-effective care that meets the evolving needs of patients and the healthcare system. Interested in exploring Value-Based Healthcare? See how Actu-Real can help: https://lnkd.in/g3EAYbkF Follow Actu-Real for more insightful posts on #healthcare, AI, machine learning, health economics, outcomes research, and real-world data. #ActuReal #Healthcare #ValueBasedCare #ValueBasedHealthcare #VBH

🚀 The Tipping Point: Navigating AI’s Untapped Potentials in Healthcare As I immersed myself in the latest innovations and developments in the health tech sphere, one thing became glaringly evident: we are standing on the brink of a seismic shift. A shift powered by Artificial Intelligence (AI) that’s not just revolutionary but evolutionary. But here’s the catch - we’re at a tipping point. AI in healthcare isn’t a glimpse into the future; it’s a reality that’s transforming patient care, diagnosis, and treatment as we speak. We’ve made leaps, from AI-driven diagnostic precision to personalized treatment protocols. But are we harnessing its full potential? Not yet. We’re witnessing AI make strides in enhancing diagnostic accuracy, reducing the workload on healthcare professionals, and optimizing hospital resource allocation. It's promising and exciting. Yet, a vast expanse of untapped potentials still lies in wait. A treasure trove of innovation that promises not just enhanced efficiency but a reimagined patient care paradigm. Metaverse, AI and Web intertwined. NEWS: Microsoft announces new AI tools to help doctors deliver better care Dive Deeper with Me, Myself and Deep-Tech: Navigating the Nexus: How, AI, Metaverse, Omnivores and Quantum Computing forging the Path To Precision Health https://lnkd.in/dUbfEuW9 🔍 Navigating Challenges: The Road to AI Integration Yet, as with any technological leap, challenges are innate. Trust, bias, data security, integration into clinical workflows - these aren’t just challenges but opportunities. Opportunities to refine, enhance, and elevate AI’s role in healthcare, ensuring not just efficacy but ethics. ✨ The Future Awaits: AI’s Unleashed Potency AI’s transformative power in healthcare is relatively low but still, on the cusp of its full bloom. Every challenge surmounted, every innovation adopted, and every protocol refined, paves the way for a healthcare landscape where technology and human ingenuity converge. As professionals at the intersection of healthcare, technology, and policy, we’re not just witnesses but catalysts. Every conversation, collaboration, and innovation is a step toward unveiling AI’s untapped potentials. Robots like Sophia are helping elderly. The use of ChatGTP and generative AI to become your doctor? Source interactive map: World Economic Forum. #AI #healthcare #future #innovation

A recent Harvard Business Review research report focused on the value of data for healthcare systems! “You can’t run a profitable healthcare organization without leveraging data in novel ways. You can’t see patients you need to see without leveraging the data of the past to find care journeys that are optimal for patients in the future. And you can’t reduce burnout in your clinicians unless you are looking at the data to determine what clinician needs to see what patients," said John Halamka, M.D., M.S., president of Mayo Clinic Platform. We are proud to collaborate with premier healthcare systems like Mayo Clinic in our federated network, which provides access to the most extensive multimodal, longitudinal healthcare data available across all therapeutic areas. https://bit.ly/3YtT017 #data #Healthcare #AI #HealthTech #ClinicalTrials #MedicalAffairs #LifecycleManagement #FederatedAI

🌍 Rgulatory Consideration on Artificial Intelligence for Health 🏥 The World Health Organization (WHO) is on a mission to promote health, ensure global safety, and serve the vulnerable. At the core of their strategy lies the ambitious goal of improving health worldwide. Their strategy, spanning 2020-2025, focuses on accelerating the development and adoption of accessible, affordable, and scalable digital health solutions. These innovations are designed to prevent, detect, and respond to epidemics and pandemics, ultimately helping nations utilize health data to achieve the United Nations' Sustainable Development Goals and WHO's Thirteenth General Programme of Work. But WHO isn't alone in this endeavor. Numerous international and regional organizations, such as the International Medical Device Regulators Forum (IMDRF), the Global Harmonization Working Party (GHWP), and the International Coalition of Medicines Regulatory Authorities (ICMRA), are actively engaged. They're joined by the International Organization for Standardization (ISO), the Organisation for Economic Co-operation and Development (OECD), and the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH). Together, they're striving for a common goal. The digital transformation of healthcare, including the integration of Artificial Intelligence (AI), holds incredible potential. AI, defined as a branch of computer science, statistics, and engineering, leverages algorithms and models to make decisions and predictions. Machine Learning (ML), a subset of AI, enables computers to learn from data without explicit programming, opening up possibilities in medical diagnosis, digital therapeutics, clinical trials, self-care, and evidence-based knowledge. With the increasing availability of healthcare data and the rapid progress in analytics techniques, AI is poised to revolutionize the healthcare sector, one of the most critical areas for societies and economies worldwide. Let's join hands in this global effort to harness the power of digital health and AI, making healthcare more accessible and effective for everyone, everywhere. 🌟 #DigitalHealth #AIinHealthcare #WHO #GlobalHealthcare #SustainableDevelopmentGoals #AI

Healthtech is evolving rapidly, but the tug-of-war between data availability and patient privacy continues. There are some real pressing issues surrounding real vs. synthetic data in healthcare algorithms. 1. Real Data: The Gold Standard - The authenticity of actual patient data is unmatched. - Yet, sourcing this data is fraught with challenges, primarily due to privacy concerns. 2. Synthetic Data: A Necessary Compromise? - As real-world data remains elusive, synthetic data or "digital twins" have been the go-to. - While a statistical approximation, it's essential to acknowledge the inherent errors they bring. 3. Enter De-identification Tools: A Game Changer - These tools anonymize real patient data, allowing for its use in algorithm training sans identity concerns. - They ensure that health tech algorithms are well-rounded, trained on diverse data, and ready for real-world application. 4. Why This Matters: - De-identification tools are poised to be pivotal in the healthcare tech landscape. - They democratize the digital health market, making it accessible for all players irrespective of their size. - Most importantly, they're a potent weapon against AI biases, pushing us closer to an equitable digital health world. #HealthTech #DataInHealthcare #DigitalHealth https://hubs.ly/Q022Gp1X0