Healthcare

Saudi Arabia built the world's largest virtual hospital, and we haven't even heard of it. It connects 224 hospitals and treats 400,000 patients a year without a single physical bed. It's called Seha Virtual Hospital in Riyadh, and it just earned a Guinness World Record for being the largest virtual healthcare provider in the world. But how can a hospital be “virtual”? How does it work? → Imagine you live in a small town with only a basic local hospital. → It has doctors and equipment. But if you need a cardiologist or neurologist, you travel 6+ to a bigger city. In urgent situations, people lose lives. → With Seha, specialists treat you remotely through your local hospital - reviewing scans, diagnosing conditions, prescribing treatment - while local staff execute it. That's the model. Specialist expertise delivered through existing hospitals. And here's what makes it work: ▶️ AI prioritizes urgent cases - analyzes CT scans and imaging to rank who needs immediate intervention ▶️ IoT monitors patients remotely - heart failure patients wear devices that alert doctors before hospitalization is needed ▶️ Integrated health records - manages prescriptions and reports across all 224 hospitals in real-time The results? - ICU patients now stay an average of 4 days instead of weeks.  - Stroke patients get CT scans within 25 minutes of arrival. - Treatment starts in 28 minutes.  - Radiology reports in 2 hours. This isn't telemedicine where you video-call a doctor from home. This is expertise delivered through your local hospital without the specialist being physically there. It proves you don't need cardiologists and neurologists in every town. You just need good internet and hospitals willing to collaborate. Do you think virtual hospitals could solve specialist shortages in rural areas? #Entrepreneurship #healthtech #innovation

Surgical robots cost $2 million. Beijing just built one for $200,000. Watch it peel a quail egg: Shell removed. Inner membrane intact. Submillimeter accuracy that matches da Vinci at 90% less cost. Think about that. Most hospitals can't afford surgical robots. Rural clinics? Forget it. Patients travel hundreds of miles for robotic surgery or settle for traditional operations with higher risks. Beijing's Surgerii Robotics just broke that equation. Traditional Surgical Robotics: ↳ $2 million purchase price ↳ $200,000 annual maintenance ↳ Only major hospitals qualify ↳ Patients travel or wait Chinese Innovation Reality: ↳ $200,000 total cost ↳ Same precision standards ↳ Reaches district hospitals ↳ Surgery comes to patients But here's what stopped me cold: Professor Samuel Au left da Vinci to build a network of surgical robots. Engineers from Medtronic and GE walked away from Silicon Valley salaries to build this. They're not chasing profit margins. They're chasing one vision: "Every hospital should have one." The egg demonstration proves what matters: Precision doesn't require premium pricing. The robot's multi-backbone continuum mechanisms deliver the same submillimeter accuracy whether peeling eggs or operating on hearts. What This Enables: ↳ Thoracic surgery in rural hospitals ↳ Urological procedures locally ↳ Reduced surgical trauma everywhere ↳ Surgeon shortage solutions The Multiplication Effect: 1 affordable robot = 10 hospitals equipped 100 deployed = provincial healthcare transformed 1,000 units = surgical access democratized At scale = geography stops determining survival Traditional robotics kept precision exclusive. Surgerii makes it accessible. We're not watching price competition. We're watching healthcare democratisation. Because that farmer needing heart surgery shouldn't die waiting for a $2 million robot his hospital will never afford. Follow me, Dr. Martha Boeckenfeld for innovations that put patients before profit margins. ♻️ Share if surgical precision should be accessible, not exclusive. #healthcare #innovation #precisionmedicine

When you’ve been a patient inside the healthcare system you work in, you start noticing the little things: the silence after a monitor alarm, the hallway conversation you’re not sure was meant for you, the well-meaning “we’ll know more soon." The list goes on. I’ve experienced world-class medicine across the country all thanks to my heart transplant. But the system isn’t only a collection of procedures. It’s also a network of people and pauses. One missed follow-up call or one delay that no one explains? These become mountains when you’re the one in the bed. Yes, design is about technology and efficient throughput, but it's also about how a system feels when you’re scared. When I returned to medicine as a physician, those 'patient experience' memories followed me into every patient encounter. They changed how I communicate, lead, & potentially help design future systems. Good healthcare solves problems. But in my opinion, great healthcare prevents people from feeling like one. If we design for that moment between uncertainty and trust, we design for the kind of system we all want to work in. #womeninmedicine #patientdoctor #doctor

The Centers for Medicare & Medicaid Services has proposed that Medicare Advantage plan revenues will remain flat going into 2027 at a moment when underlying medical costs, labor expenses, and pharmaceuticals continue to rise materially. What does this mean in practice? For beneficiaries: Over time, beneficiaries should expect less generous benefits, tighter utilization management, and narrower provider networks. Access may become more constrained—not necessarily through explicit benefit cuts, but through fewer participating provider groups and more selective contracting. The tradeoff between affordability and choice will become more acute. For brokers and distribution partners: Distribution costs in Medicare Advantage are largely fixed, particularly commissions and marketing infrastructure. As margins compress, plans will continue to reassess how (and how much) they pay for growth. This may include lower upfront commissions, greater reliance on retention-based compensation, or shifts toward more direct-to-consumer enrollment strategies. For provider groups: Provider organizations seeking rate increases will face a much tougher negotiating environment. With plan revenues constrained, upward pressure on provider rates becomes difficult to absorb. As a result, some provider groups may choose to exit Medicare Advantage entirely, while others will narrow participation to fewer plans. The result may be increased network fragmentation and heightened tension between plans and providers over risk, quality expectations, and total cost of care. For managed care company employees: Cost discipline will extend inward. Plans will be slower to hire, more selective about new investments, and may pursue workforce reductions. Expectations will shift toward higher productivity, flatter organizational structures, and doing more with fewer resources. For Investor-backed Medicare Advantage plans: The economics of growth will change. Longer payback periods, lower internal rates of return, and greater regulatory uncertainty will make Medicare Advantage investments less immediately attractive. Capital will still flow to the sector, but it will be more discriminating, favoring scale, operational excellence, and differentiated capabilities rather than growth at any cost. For small and regional health plans: Scale matters more than ever. Smaller plans will struggle to compete. Many may exit the market or seek partnerships, mergers, or acquisitions. Consolidation pressures are likely to intensify as fixed administrative and compliance costs consume a greater share of revenue. Time will tell whether the rate decisions outlined in the Advance Notice hold through the Final Rule. Regardless of the ultimate number, one thing is clear: Medicare Advantage is entering a period of transition. The era of easy growth is ending, and the next phase will be defined by tradeoffs—between generosity and sustainability, growth and discipline, innovation and affordability.

Dr. S M Ziaur Rahman, a medical professional, has made a commendable transition from a high-paying position in Delhi to establish a vital healthcare center in rural Bihar. His initiative directly addresses a critical gap in rural medical infrastructure, exemplified by his nominal charge of just ₹250 per patient visit. This significantly contrasts with typical urban healthcare costs, ensuring that financial barriers do not prevent individuals from receiving necessary medical attention. Dr. Rahman’s decision was deeply influenced by a poignant experience: witnessing the plight of a patient from Bihar who had to travel to Delhi for treatment due to the severe lack of adequate facilities in their native region. This encounter underscored the urgent need for local, high-quality medical services. By establishing this center, Dr. Rahman is not only providing essential care but also significantly contributing to the improvement of public health outcomes and fostering hope among countless underprivileged individuals in rural Bihar. His exemplary action highlights the transformative potential of dedicated medical professionals addressing critical healthcare disparities in underserved regions. LinkedIn LinkedIn News LinkedIn for Learning

A Dutch nursing home has found a simple, powerful way to help dementia patients feel at home: it places life-size stickers of their former front doors on their current room doors. The village, called Hogeweyk in the town of Weesp, is designed to look and feel like a normal Dutch neighborhood. It features familiar storefronts, a town square, and even a theater. Inside, the door stickers act as visual anchors, helping residents find their way and reducing the confusion that often comes with a new living environment. The approach is part of a broader philosophy that prioritizes quality of life, autonomy, and familiarity over a traditional clinical setting. It's a small detail with a massive impact. 🚪💛

This cartoon made me laugh… and then stop cold. Too often, patients give up on care not because they don’t want it, but because the system puts up too many barriers. Download this. Log into that. Navigate a portal. By the time they get through the maze, the moment has passed. As a physician, I’ve seen the human toll of delayed care. As a digital health executive, I’ve seen the organizational toll: rising costs, unused technology, and clinicians burning out under systems they don’t trust. The irony? We keep investing in tools meant to simplify, but without engaging clinicians, embedding trust, and keeping the patient’s experience front and center, we end up with technology people work around, not with. Whether it’s agentic AI in clinical workflows, payment integrity systems to reduce waste, or new tech rollouts in health systems, the lesson is the same: efficiency alone isn’t enough. Trust, safety, and usability are what turn innovation into outcomes. So here’s my question for you: 👉 How do we design healthcare technology that clinicians trust and patients can actually use in the moments that matter most? Because care delayed by complexity is too often care denied. #digitalhealth #healthtech #clinicianengagement #patientexperience #healthcareinnovation

Your board wants 20% growth next year. Your team hears that number and their souls leave their bodies. 20%??? After they just killed themselves to hit this year's number? Todd Caponi , during this past week's Revenue Manager Lab at Sales Assembly, broke down a formula that should hopefully result in folks who are faced with goals like this exhaling a huge sigh of relief. The Results Formula: Revenue = (Qualified Opportunities × Deal Size × Win Rate) ÷ Cycle Length. Now here's where it gets interesting. Improve each metric by just 5%: - 5% more qualified opportunities (literally one more per rep). - 5% higher deal sizes ($2K on a $40K deal). - 5% better win rate (win one more deal you'd normally lose). - 5% faster cycle time (close 3 days faster). Result: 22% revenue growth. Don't believe Todd? Run it through whatever spreadsheet you want. Change the variables. Use different baseline numbers. ALWAYS comes out to 22%. Try 10% improvements across all four? You get 46% growth. But here's a mistake many leaders make: They pick one metric and try to double it. "We need MORE PIPELINE!" So they hire more SDRs, blast more emails, book more meetings. Pipeline goes up 50%. Revenue goes up 8%. Why? Because they flooded the zone with bullshit opportunities that destroyed their win rate and extended their cycle time. The magic is in the compound effect of tiny optimizations. A 5% improvement is nothing: - One better discovery call per month. - One less discount given. - One deal closed three days faster. - One bigger upsell identified. Stack those improvements. Compound them. Watch what happens. Your team doesn't need to raise their hand another foot higher. They need to raise it one inch higher in four places. Stop asking for heroics. Start asking for tweaks. The math is undefeated.

I've watched 3 "revolutionary" healthcare technologies fail spectacularly. Each time, the technology was perfect. The implementation was disastrous. Google Health (shut down twice). Microsoft HealthVault (lasted 12 years, then folded). IBM Watson for Oncology (massively overpromised). Billions invested. Solid technology. Total failure. Not because the vision was wrong, but because healthcare adoption follows different rules than consumer tech. Here's what I learned building healthcare tech for 15 years: 1/ Healthcare moves at the speed of trust, not innovation ↳ Lives are at stake, so skepticism is protective ↳ Regulatory approval takes years usually for good reason ↳ Doctors need extensive validation before adoption ↳ Patients want proven solutions, not beta testing 2/ Integration trumps innovation every time ↳ The best tool that no one uses is worthless ↳ Workflow integration matters more than features ↳ EMR compatibility determines adoption rates ↳ Training time is always underestimated 3/ The "cool factor" doesn't predict success ↳ Flashy demos rarely translate to daily use ↳ Simple solutions often outperform complex ones ↳ User interface design beats artificial intelligence ↳ Reliability matters more than cutting-edge features 4/ Reimbursement determines everything ↳ No CPT code = no sustainable business model ↳ Insurance coverage drives provider adoption ↳ Value-based care is changing this slowly ↳ Free trials don't create lasting change 5/ Clinical champions make or break technology ↳ One enthusiastic doctor can drive adoption ↳ Early adopters must see immediate benefits ↳ Word-of-mouth beats marketing every time ↳ Resistance from key stakeholders kills innovations The pattern I've seen: companies build technology for the healthcare system they wish existed, not the one that actually exists. They optimize for TechCrunch headlines instead of clinic workflows. They design for Silicon Valley investors instead of 65-year-old physicians. A successful healthcare technology I've implemented? A simple visit summarization app that saved me time and let me focus on the patient. No fancy interface, very lightweight, integrated into my clinical workflow, effortless to use. Just solved an problem that users had. Healthcare doesn't need more revolutionary technology. It needs evolutionary technology that works within existing systems. ⁉️ What's the simplest technology that's made the biggest difference in your healthcare experience? Sometimes basic beats brilliant. ♻️ Repost if you believe implementation beats innovation in healthcare 👉 Follow me (Reza Hosseini Ghomi, MD, MSE) for realistic perspectives on healthcare technology

How can we make genomic foundation models actually useful to biology?! Teach them to REASON!! 🧬 Excited to share BioReason - the first model to successfully integrate DNA foundation models (eg, Evo 2) with LLMs (eg, Qwen3) for biological reasoning! 🔬 What we built: • Novel multimodal architecture that lets LLMs directly process genomic sequences as input • Trained with supervised fine-tuning + GRPO reinforcement learning for sophisticated multi-step reasoning • Generates interpretable step-by-step biological reasoning traces from genomic data 📊 Benchmarks & Performance: • KEGG pathway reasoning: 97% accuracy on mechanistic variant-to-disease prediction • Variant effect prediction: 80-88% accuracy on pathogenic/benign classification • Evaluated on 1,449 KEGG entries + 86K+ ClinVar variants across coding/non-coding regions • Consistent 15%+ performance gains over DNA-only or LLM-only baselines 🎯 What this truly means: This enables AI systems to provide mechanistic biological insights comparable to domain experts - bridging the gap between "black box" DNA foundation models and interpretable scientific reasoning. Could fundamentally accelerate hypothesis generation and biological discovery by making genomic AI transparent and actionable. 🙏 Thanks to our amazing team: Adib Fallahpour , Andrew Magnuson, Purav Gupta, Rex Ma, Jack Naimer, Arnav Shah, Haonan Duan, Omar Ibrahim, Hani Goodarzi , Chris Maddison Across institutions: University of Toronto Vector Institute University Health Network Arc Institute Cohere Google DeepMind 🗒️ Paper: https://lnkd.in/gCdWT5mb 🌐 Website: https://lnkd.in/gzh4cFYV 💻 Code: https://lnkd.in/gfQfNytK 🤗 Datasets: https://lnkd.in/gCnbvHM2 #AI #MachineLearning #Genomics #Biology #Research #BioAI