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Would You Trust AI With a Healthcare Decision? Or a Human? Let’s be honest — Healthcare is entering a phase where trust matters more than technology. And the real question isn’t just “AI vs Humans.” It’s this: Where do you draw the line when it comes to Decision Making? Most AI systems in healthcare don’t make fully autonomous decisions yet. They act in an advisory role—assisting, guiding, validating. The shift we see is: “AI that works” → to → “AI we can explain and trust.” 🔍 Explainable AI models 📋 Validated protocols 🧭 Full audit trails Why? Because a recommendation is only powerful when you understand why it was made. That’s how trust is built. That’s how AI becomes reliable. That’s how healthcare can move forward. Now I’m curious and I want your honest take: 👇 Where do you trust humans more than AI? 👇 And where do you trust AI more than humans in Healthcare? Your answer might surprise you… and everyone who is working with AI Check out this small clip from the podcast with Elizabeth Daley, MHA and her take

🎙️ NEW EPISODE - PART 2: The Ethics of AI in Healthcare: An Honest Conversation with Neil Mukherjee, a Director and Surgeon with Northwell Health In Part 2 of our conversation with Dr. Neil, we dive deep into one of the most critical discussions of our time: Who is responsible when AI makes medical errors? 🔑 Key Insights from Dr. Neil: Accountability Matters: AI companies must take responsibility for errors, just as traditional media has done for centuries. "If AI can solve problems and not take the responsibility of making errors, should it be a part of humanity?" Explainable AI is Non-Negotiable: Clinicians need to understand WHY they're making decisions. Without transparency in algorithms, we're asking physicians to work under duress. Personalization Over Generalization: AI has the potential to process vast amounts of medical knowledge instantly, but the focus must shift from general intelligence to personalized assistance. 70-80% of medical decisions today are based on pre-FDA algorithms and century-old statistics. AI could revolutionize this, but only with ethical guardrails. Dr. Neil reminds us that while AI will likely surpass human capabilities in processing information, the sacred physician-patient relationship must remain human-centered. A fool with a tool is still a fool—we need good doctors who use AI, not AI replacing good doctors. Listen to Part 2 of our conversation to understand why ethical AI in healthcare isn't just important—it's essential for humanity's future. 🎧 https://lnkd.in/gna658MX Host: Deepti Kalghatgi Here is a question to HIMSS, HIMSS North Carolina Chapter & also startups in healthcare Startups in healthcare community as well, Who is responsible when AI makes medical errors? #AIinHealthcare #HealthTech #MedicalAI #EthicalAI #DigitalHealth #HealthcareLeadership #FutureOfMedicine #podcast

Where is the AI investment in healthcare actually flowing? A surprising $1.4 billion has been spent, primarily focused on outpatient providers ($280 million) rather than payers (only 5%). AI adoption in healthcare is largely focused on ambient scribes and coding/billing automation to address the staff shortage and clinician burnout. These areas offer a clear ROI. Ambient clinical documentation reduces physician burnout, while coding and billing automation is substantial ($450 million). AI's biggest returns lie in addressing acute pain points and delivering tangible ROI. Follow us on: LinkedIn: https://lnkd.in/gbwPbVuA and YouTube https://lnkd.in/g-KqfyXB #HealthcareAI #AIinHealthcare #ClinicalDocumentation #BillingAutomation #HealthTech

Healthcare just shocked the tech world & beat Silicon Valley in AI Adoption While everyone was watching finance or other verticals, healthcare quietly became the FASTEST AI adopter in enterprise—deploying at 2.2X the rate of other industries. Our next IDAA Hub Podcast is a deep dive into the Menlo Ventures 2025: The State of AI in Healthcare The numbers from Menlo Ventures' 2025 report are stunning: 📊 22% adoption rate (7X increase in just 12 months) 💰 $1.4B in AI spending (tripled year-over-year) ⚡ 6.6-month buying cycles (down from 12-18 months) 🚀 85% captured by startups (not incumbents) 🎯 80% of market still untapped In this 20-minute analysis, I break down where the money is really flowing and what it means for anyone building, investing, or working in healthcare. Three insights that surprised me most: 1) Mayo Clinic, Cleveland Clinic, and Kaiser now prioritize AI "maturity" over customization—they want production-ready solutions they can deploy in weeks, not years. 2) Ambient clinical documentation hit $600M, but adoption is already plateating at 40% in large health systems for startups. The real opportunity? Prior authorization ($98B services market, only 3% software penetration). 3) Providers and payers are in an AI arms race. Providers automate prior auth and coding. Payers worry about claim floods. Both sides building AI agents to match each other. This tension will define the next 24 months. The report makes one thing clear: Healthcare's AI moment is NOW. Not coming. Not pilot-stage. NOW. If you're building, buying, or betting on healthcare AI, these 22 minutes will change how you see the market. Explore the full AI in Healthcare Pocast: https://lnkd.in/gZGiWP6g What's your take? Are you seeing this AI acceleration in your organization? #HealthcareAI #DigitalHealth #HealthTech #AIinHealthcare #HealthcareInnovation #ArtificialIntelligence #HealthIT #HealthcareLeadership

🎙️ New Podcast Release He owned a brewery. Then, in his 30s, he walked away from it to go to medical school. How many Physicians you know who did that? His training took him from Grenada to London to Kerala, where he met doctors whose bedside skills he’d never seen before. Now Dr. Lief Olson, M.D. is a physician building AI. So what does a former brewery owner turned doctor see that most health tech builders miss? 👀 🎧 Full episode link in the comments 👇 #IDAAHubPodcast #AIinHealthcare #HealthTech #PhysicianInnovators Arbimus

Health systems are spending millions on RCM AI with almost no independent peer reviews. Share your honest 2-minute review scored on the Stanford AIMI FURM Framework. $100 gift card for a qualified 1st reviewer and $25 for every 5th reviewer.