Nicoleta Economou’s Post

Top 25 hospitals for AI readiness Rochester, Minn.-based Mayo Clinic was named as the No.1 hospital leading in artificial intelligence readiness, according to a July 15 report from CB Insights.  To identify which health systems are best equipped for AI, CB Insights launched the "Hospital AI Readiness Index." This index ranks the top private-sector health systems in the U.S. by hospital count, assessing their preparedness in two key areas — innovation and execution.  The innovation scores are determined by the existence of an AI-focused research center and CB Insights data, which includes AI-related patents, acquisitions and deal-making activities since 2019. Execution scores are also determined by CB Insights data, which includes AI-related business relationships, product launch media mentions and earnings transcripts since 2019. Here are the 25 health systems most prepared for AI, according to CB Insights: Mayo Clinic (Rochester, Minn.) Intermountain Health (Salt Lake City) Cleveland Clinic  Kaiser Permanente (Oakland, Calif.) Mount Sinai (New York, N.Y.) Providence (Renton, Wash.) HCA Healthcare (Nashville) Mass General Brigham (Boston) Community Health Systems (Franklin, Tenn.) Johns Hopkins (Baltimore, M.D.) CommonSpirit Health (Chicago) Ascension (St. Louis) UPMC (Pittsburgh) Banner Health (Phoenix, Ariz.) AdventHealth (Altamonte Springs, Fla.) https://lnkd.in/ee3PdkN2

Where are the women? #Congress is beginning a series of hearings on artificial intelligence. Today's is “fact-finding mission on #AI in #healthcare.” This is a much needed step to understand the promise and risks of AI in health care. As conversations with experts continue in the Halls...more #women need to be included in these discussions, as well as #patients. We know that women make the majority of health care decisions for their families, and carry perspectives on this issue in a way that men will never experience. There are many in the field who can show up not just as experts, but as women running health care for their families and as people who experience health care differently than those on the witness stand today. Today's witnesses are all men: - Dr. Michael Schlosser, M.D., MBA, Senior Vice President of Care Transformation and Innovation, HCA Healthcare; - Dr. Benjamin Nguyen, Senior Product Manager, Transcarent; - Mr. Peter Shen, Head of Digital Health – North America, Siemens Healthineers; - Dr. Christopher Longhurst, M.D., Chief Medical Officer, Chief Digital Officer, and Association Dean, UC San Diego Health; and, - Dr. David Newman-Toker, M.D., Ph.D., Director, Division of Neuro-Visual and Vestibular Disorders, Department of Neurology, Professor of Neurology, Johns Hopkins University School of Medicine.

Some organizations are stepping up to the plate to implement generative A.I. and it's great to see. Healthcare as a whole will have a different look and feel in 10 years (or sooner). This should break some of the barriers and time sinks that healthcare workers currently have to endure. Of course, the proper oversight & risk mitigation must be in place, but this will surely continue to improve clinical accuracy and efficiency. Bravo to EHC!

🚀 ICYMI: the Emergency Medicine Journal have published our landmark study! The findings reveal reduced mortality by almost 50 per cent in elderly males in the two years following HN’s intervention. 👉 Today, we want to draw your attention to what our research means and share Joachim Werr and Steve Laitner's three key recommendations for policymakers: 1️⃣  Invest in research on AI prediction and risk stratification tools. More research is critically needed to validate predictive algorithms across diverse populations and care pathways. Policymakers should look to fund large-scale studies on risk stratification AI to build evidence for national implementation. 2️⃣ Develop incentives and reimbursements for preventative AI models. HN’s model – built by clinicians and undergone robust national trials to improve the allocation of preventative care resources, reducing costs and delivering better patient outcomes – is an important example. To catalyse adoption of solutions like the trial's AI screening and nursing interventions, policymakers must develop incentives and value-based reimbursements for proven preventative approaches. 3️⃣ Support infrastructure for data-driven population health. Policymakers should work with colleagues in health to invest in i) Integrated data systems spanning care settings, ii) Robust data security and privacy measures, and iii) Responsible governance that facilitates access to data while upholding security and ethical standards. Read in full: https://bit.ly/3S46MXl #proactivecare #rct #research #journal #emergencycare #hospital #ai #prediction #personalisedcare #harm #healthcare

I was really fascinated by this paper, so I’m reposting it - this time I provide some key discussion points which I found interesting and helpful for those working on developing AI tools in healthcare (AIH) as well as potential end-users (patients and clinicians to mention few): ·      AIH must first and foremost directly benefit patients -> maximize the benefits and reduce the harm ·      The central criteria for use of AIH should be the same as for other medical technologies: better healthcare for all patients, including faster access (eg lower costs of delivering care and improved productivity) and support for the healthcare workforce ·      AI should be used as a complementary tool, supporting the clinicians and / or helping patients, rather than as a replacement (this may change in future) ·      AIH needs to be used responsibly – there are ongoing efforts around developing a code of conduct that will harmonize efforts into one framework, with a special emphasis on ethics, equity, and vigilance for errors that may emerge once the AI is in use. ·      Ideally, professionals and patient advocates will determine best clinical practices and convey them to regulators, rather than vice versa. And here is a set of important recommendations for AIH developers: 1.     Be transparent about your training data sets (this will foster trust and potentially faster adoption) - Super important! 2.     Diversity must be represented within training data sets to ensure AIH tools' applicability to underrepresented minorities. 3.     Tech companies must accept some portion of the legal liability if an AIH system leads to harm and it is at fault. 4.     Similarly, tech companies must move toward accepting some responsibility for outcomes when patients use AI directly, just as with any other direct-to-consumer health tool or resource. 5.     Bring patients, patient advocates, and clinicians into the process of designing the technology at every stage (this will also foster trust and potentially faster adoption) - 100% agree! 6. Regarding business models, the expert group favored subscription to AIH or up-front payment models rather than bill per use, based on previous experiences. In summary, all involved stakeholders (and it’s pretty much everyone) will need to be educated about the responsible use of AIH, while the developers think about their share of liability, bringing right stakeholders in the development process and staying transparent). This will all need to be followed by careful monitoring of the effects of implementing new AIH technologies, such as assessing its impact on aspects such as reduction of administrative costs, improving patient outcomes and other potential benefits. #aihealthcare

Every one of us will need medical services at some point – whether for regular check-ups or to treat a major condition. Deciphering health care jargon, reviewing test results or meeting with specialists can be daunting, no matter a patient's background. Sadly, education level is a factor in determining health outcomes and the disparities are stark: people without college degrees have 4x higher mortality rates than their college-educated peers. If someone doesn’t understand their risk factors, diagnosis or treatment options, how can they overcome that very real disadvantage and make informed health decisions? In my latest Forbes article, I share how we can leverage the power of AI to help more people access the care they need – regardless of education level – and ultimately, begin to close gaps in our health system. Check it out and tell me what you think in the comments. #healthequity #healthcare #AIinhealthcare #generativeAI #genAI #AI #chatgpt Deborah K., Jessica Shen, MD, MS, Ramnik Khangura, Franco Manna, Mike Polaha, Lauren Bookstaver, Bart Talloen, Lillian Shieh, Robert Ford, Atif Noori, Lisa Earnhardt, Andrew Trister, MD PhD, Sonita Lontoh, Cecilia Aviles, MBA, BSN, RN, Paula Pretlow, Shoshana Ungerleider, MD, Renee Ryan, Ashley McEvoy, Archana Dubey, MD, Joy Liu, Diana McKenzie, Dana Mendenhall, Jesús Mantas

Great piece in Newsweek about how AI is going beyond individual patients to revolutionize healthcare on a broader scale The article highlights the growing focus on AI for population health management. Hospital CEOs like @Dr Eric Larson of Ochsner Health see AI as a game-changer: "AI can analyze vast datasets to identify at-risk populations and tailor interventions." This could mean: Proactive public health measures: By analyzing population health data, AI can pinpoint areas with high disease risks, allowing for targeted public health campaigns and preventative measures. Personalized healthcare at scale: AI can identify individuals most likely to benefit from specific interventions, enabling a more personalized approach to preventive care. #AI #HealthcareAI #populationhealth https://lnkd.in/dr-mGxJr

Digital Health | AI | Proof Check This seems an absolute promising and relevant step by #CoalitionforHealthAI https://lnkd.in/dP49fbSe

🔥 📅 Thrilled to be chairing the upcoming one-day AI in Health Readiness Forum 2023 powered by the Informa Australia 📅 When: 25th October 2023 📌 Where: Ivy Sunroom, Sydney 💻 👩💻 ⚕The AI in Health Readiness Forum is a highly specialised event designed to explore the important considerations around AI adoption in healthcare and weigh the readiness in different contexts and clinical settings. 🏥⚕The event will explore the readiness of the workforce, health services, and workflows. What are the applications for AI in health which are ready? How is it being used effectively and what have been the learnings which can be translated across other areas of health and medicine? Join me in the amazing line up of speakers including: OPENING ADDRESS | What is possible? The real-life application of AI within Clinical Settings 🎙Dr Simon Kos - CMO Microsoft ANZ PANEL | Good Clinical Governance: why is this critical when deploying an AI algorithm 🎙Dr Kean Kuan - Victorian Institute of Forensic Medicine 🎙Dr Emily Kirkpatrick - Calvary Health Care / Medibank JV 🎙Phil O'Sullivan - Allens 🎙Angie Corbo - Roche Current Regulatory Approach to AI 🎙Val Theisz KEYNOTE | Improving healthcare for Australians from the coalface up 🎙Prof Steve Robson, President Australian Medical Association PANEL | Patient Safety: The good, the bad and the important considerations of AI 🎙Dana Mouwad, Western Sydney Local Health District 🎙Nathan Moore FAIDH CHIA, Western Sydney LHD 🎙Prof Farah Magrabi, Australian Institute of Health Innovation 🎙Michelle Barakat-Johnson Moderator: Andrew Hallahan, Sydney LHD IN COVERSATION | Good data governance = successful integration of AI 🎙Mazeta Hamilton, Queensland Health 🎙Phil O'Sullivan, Allens 🎙Melissa Tinsley, NSW Health 🎙Moderator: Marc Pelusi, Sydney LHD CASE STUDY | Pick your player AI or Human 🎙Jacky Hung, Queensland Health PANEL | Prepping your roadmap: building the basis to transform care 🎙Anthony Porter, Royal Adelaide Hospital 🎙Todd Tobin - Calvary Health Care 🎙Moderator: A/Prof Tam Nguyen, St Vincent's Hospital Melbourne PANEL | Creating a workforce for the imminent future: digital first 🎙Prof Ian Scott, Princess Alexandra Hospital 🎙Dr Emily Kirkpatrick, Calvary-Medibank JV 🎙Mitch Burger - Sydney Local Health District 🎙Moderator: A/Prof Tam Nguyen, St Vincent's Hospital Melbourne ♻Share, 🔖Tag, 👍Like and ⌨Comment #artificialintelligence #aiinhealthcare #bigdata #digitalhealth #medicalAI #AIinHealth St Vincent's Hospital Melbourne, Acclime Australia, Horizon 3 Healthcare 11.ix.2023

Coalition for Health AI (CHAI) Talk is cheap and very pervasive and U.S. Healthcare System Broken - 93% of Americans say their healthcare is not worth what it costs https://lnkd.in/gTvw_yNm  - Medical systems are in the 'sick care' business to put people on drugs, not take them off - Social determinants of health drive 80% to 90% of health outcomes would improve the health of individuals and communities. It would also decrease the pressure on doctors to treat medical conditions stemming from unhealthy environments that we can't change. - The Innovation #HealthCare Really Needs is Help People Manage Their Own Health with Prevention-as-a-Service and wellness to live healthier, happier life  Cheers....Steve AI startup advisor 'force multiplier' https://lnkd.in/g38mWcs