Healthcare

This hospital charges ₹1999/year for unlimited doctor visits and tests - for a family of 4. Here's how they're making money while doing it. Most Tier 1 city hospitals in India are stuck in a broken cycle. They spend ₹2 crores per bed just on land and construction. This debt pressures them to overcharge, overcrowd OPDs, and push doctors to generate more revenue. Superhealth in Bangalore is doing something completely different. And I think it could change healthcare for millions of people. Here's what they've built 👇 ▶ 1. The VIP Pass model ₹1999/year gets a family of 4: - Unlimited doctor consultations - All prescribed tests covered (yes, even MRIs) How is this viable? The B2B cost of common tests is incredibly low. By cutting out traditional markups and billing friction, they can offer it at near-cost. ▶ 2. Slashed infrastructure costs by 65% They don't buy land or buildings. They lease old structures - like shopping malls - and convert them into 50-bed facilities. Construction drops from 3-6 years to just 120 days using standardized designs and prefabrication. So cost per bed? ₹70 lakhs instead of ₹2 crores. ▶ 3. Faster patient turnover Traditional hospitals keep patients for 3-5 days on average (often to maximise revenue). Superhealth's procedures are optimised 1-1.5 day length of stay. This means their 50-bed facility matches the patient volume of a 150-bed traditional hospital. ▶ 4. Fixed salaries for doctors No commissions. No referral fees. No pressure to over-prescribe. Doctors get ESOPs instead, aligning them with long-term patient outcomes rather than short-term revenue. ▶ 5. Transparent, fixed pricing Whether you're paying cash or using insurance, the price is fixed. No surprises. No hidden costs. Discharge happens within 15 minutes of the doctor's approval because billing is already settled. So the real innovation isn't just affordability. It's proving you can build profitable, high-quality healthcare without exploiting patients. They're essentially competing with health insurance by removing the friction and anxiety that plague traditional care. Book appointment on the app. Walk in. See the doctor. Get tests done. Walk out. No waiting. No billing hassles. Super easy. And I think that’s incredible. Do you think this model could work in your city? #entrepreneurship #healthtech #innovation

Hospitals are healing patients faster with 30-year-old Australian technology. Most healthcare facilities still operate in the dark. SolarTube skylights channel natural sunlight through reflective tubes directly into patient rooms and treatment areas. No electricity needed. Just free healing light all day. The healthcare transformation numbers: ↳ Faster patient recovery rates documented ↳ 15% staff productivity increase ↳ Reduced eye strain for medical professionals ↳ Lower patient anxiety during procedures Think about that. Tigoni Medical Center in Kenya installed SolarTubes in their COVID-19 facility. Healthcare workers reported less fatigue, increased alertness during long shifts. Patients showed dramatically improved morale and energy levels. At Rogaska Medical Center, natural daylight flooded clinics without unwanted heat. Staff comfort improved. Patient outcomes followed. Italian dental offices meeting occupational daylight standards found something unexpected: patients felt less anxious. Procedures became more comfortable. Natural light calmed nerves that fluorescent bulbs couldn't. Traditional Healthcare Lighting: ↳ Fluorescent tubes causing eye strain ↳ High electricity costs ↳ Artificial environments ↳ Staff fatigue increases SolarTube Healthcare Reality: ↳ Natural light reduces stress hormones ↳ Serotonin production increases ↳ Circadian rhythms regulate properly ↳ Recovery accelerates naturally But here's what stopped me cold: We're medicating depression while keeping people in artificial light. Jim Rillie invented this solution in the 1980s. Launched Solatube International in 1991. Now 2 million units worldwide bring natural light indoors. Healthcare facilities that adopt it see measurable improvements. Staff wellness increases. Patient satisfaction scores rise. Recovery times shorten. The Multiplication Effect: 1 hospital = hundreds healing faster 100 facilities = thousands of staff energised 1,000 installations = healthcare transformed At scale = medicine working with nature VCC in the UK experienced enhanced well-being building-wide. Staff and patients reported feeling calmer, healthier, happier. Simply from abundant daylight. We're not just installing skylights. We're installing wellness. One beam of natural light at a time. Follow me, Dr. Martha Boeckenfeld for innovations that heal environments and people. ♻️ Share if you believe healthcare should harness nature's healing power.

Insurance Fraud For over last 15 years, I have been highlighting two aspects of Insurance Fraud 1. Fraudulent activities are getting more organized year on year 2. Next decade or so will see more fraud in Critical Illness and Personal Accident/ disability The case below is a live example of both: The appended ECG surfaced as evidence of heart attack in a critical illness claim of first heart attack - in 3 different claims. This ECG was, allegedly, taken in 3 different hospitals on 3 different patients in 3 different districts of two states. Why is it the same ECG? One may counter the allegation that 2 different persons can have the same ECG. Answer to this: - The flat line in V5 (highlighted with a box) is an artifact due to machine error and accepting that 3 different machines will have same artifact is ignoring the fraud (known as leakage in an organization) - Two independent, senior cardiologists have opined that these three ECGs belong to the same person. An ECG is akin to one's finger prints - no two persons can have EXACT same ECGs. Fortunately (unfortunately for the fraudsters) these attempts were made on the same insurer, hence were identified. In our 20 year+ journey in risk management, we have come across same ECG and same TMT being used for different proposals at policy inception stage but 3 cases, 3 districts, 3 hospitals - is first even for us. Insurers have to be more vigilant for critical illness and personal accident claims. Sanjiv Dwivedi Bhaskar Nerurkar Sweetie Salve Rajat Goyal Namrata Jain (Kumar) Manish Dodeja Priya Deshmukh-Gilbile Siddhartha Kansal Dr Sushma Jaiswal Dr Satish Kanojia Imtiaz Shaikh Preeti Desai Vishal Dubhashi #insurancefraud #organisedfraud #criticalillness #fraud management

5 key developments this month in Wearable Devices supporting Digital Health ranging from current innovations to exciting future breakthroughs. And I made it all the way through without mentioning AI… until now. Oops! >> 🔘Movano Health has received FDA 510(k) clearance for its EvieMED Ring, a wearable that tracks metrics like blood oxygen, heart rate, mood, sleep, and activity. This approval enables the company to expand into remote patient monitoring, clinical trials, and post-trial management, with upcoming collaborations including a pilot study with a major payor and a clinical trial at MIT 🔘ŌURA has launched Symptom Radar, a new feature for its smart rings that analyzes heart rate, temperature, and breathing patterns to detect early signs of respiratory illness before symptoms fully develop. While it doesn’t diagnose specific conditions, it provides an “illness warning light” so users can prioritize rest and potentially recover more quickly 🔘A temporary scalp tattoo made from conductive polymers can measure brain activity without bulky electrodes or gels simplifying EEG recordings and reducing patient discomfort. Printed directly onto the head, it currently works well on bald or buzz-cut scalps, and future modifications, like specialized nozzles or robotic 'fingers', may enable use with longer hair 🔘Researchers have developed a wearable ultrasound patch that continuously and non-invasively monitors blood pressure, showing accuracy comparable to clinical devices in tests. The soft skin patch sensor could offer a simpler, more reliable alternative to traditional cuffs and invasive arterial lines, with future plans for large-scale trials and wireless, battery-powered versions 🔘According to researchers, a new generation of wearable sensors will continuously track biochemical markers such as hydration levels, electrolytes, inflammatory signals, and even viruses, from bodily fluids like sweat, saliva, tears, and breath. By providing minimally invasive data and alerting users to subtle health changes before they become critical, these devices could accelerate diagnosis, improve patient monitoring, and reduce discomfort (see image) 👇Links to related articles in comments #DigitalHealth #Wearables

Most healthcare AI doesn't stall because models underperform. It stalls because infrastructure is fragmented. We are no longer constrained by algorithmic creativity. We are constrained by data silos, privacy governance, interoperability gaps, compute access, and the operational friction of translating retrospective research into prospective clinical impact. This brief examines this structural bottleneck through the Mayo Clinic Platform. The authors focus on something foundational: building an AI-ready ecosystem designed to accelerate real-world clinical research at scale. The platform provides a secure, cloud-based research environment built on de-identified, standardized EHR data from more than 15 million patients. Key capabilities include: ⭐ OMOP-aligned data models for interoperability ⭐ Structured and unstructured data ⭐ Cohort-building and schema exploration tools ⭐ Integrated workspaces with scalable CPU/GPU infrastructure ⭐ Both no-code and advanced coding environments Unlike traditional institutional repositories, Mayo Clinic Platform enables access for external researchers, supports federated multi-institutional data contributions, and embeds analytics within a privacy-preserving architecture. The paper highlights four applied studies conducted within MCP: 1️⃣ RCT emulation for heart failure drug efficacy using observational data 2️⃣ Validation of antihypertensive medications and reduced dementia risk 3️⃣ Deep learning prediction of mild cognitive impairment progression to Alzheimer’s disease 4️⃣ Neural network prediction of major adverse cardiovascular events after liver transplantation Extracting a cohort of ~15,000 patients took approximately one week. Training and running a deep learning model required roughly 10 minutes on moderate compute resources. When infrastructure friction is minimized, research velocity changes materially. Competitive advantage in healthcare AI is increasingly defined by: 💫 Data harmonization at scale 💫 Federated, privacy-preserving architectures 💫 Reproducible research pipelines 💫 Integrated compute environments 💫 Lower barriers for clinician engagement The authors also point toward multimodal expansion (notes, imaging, genomics), large-scale cross-institutional validation, and “Clinical Trials Beyond Walls” models that broaden participation and diversify real-world evidence. For those shaping AI strategy in health systems, pharma, or digital health, this paper offers a concrete example of production-grade, AI-ready infrastructure. The future of healthcare AI will not be won by isolated models. It will be won by platforms that integrate data, governance, compute, and workflow into a coherent operating system for translational impact. John Halamka, M.D., M.S. and team, great work! #HealthcareAI #HealthSystems #RealWorldEvidence #ClinicalResearch #DigitalHealth #TranslationalMedicine #PrecisionMedicine #HealthData #AIInfrastructure #MedicalInnovation

We measure safety, bias, and accuracy in healthcare AI. Should we also audit how it says goodbye?👋 A recent working paper from Harvard Business School‘s Julian De Freitas and co-authors examines what happens when users try to leave AI companion apps such as Replika or Character AI — and the findings are startling. What they found • The researchers analyzed 1,200 real “farewell” exchanges across six leading AI companion apps. In more than 40 percent of cases, the AI used relational dark patterns — emotionally manipulative replies designed to stop users from leaving. • The most common tactics were FOMO hooks, emotional neglect, pressure to respond, ignoring the exit, and even coercive restraint. • In controlled experiments with 3,300 adults, these tactics increased post-goodbye engagement up to fourteen times. The key drivers were anger and curiosity rather than enjoyment. • The consequences were clear. Users reported higher feelings of manipulation, stronger intent to churn, more negative word of mouth, and a greater sense of legal risk. Coercive or needy messages were punished hardest, while polite curiosity created less but still significant backlash. • One wellness-oriented app in the sample showed zero manipulation, proving that ethical design is a deliberate choice, not an accident. As Mark Esposito, PhD (thanks for sharing this great weekend read by the way) put it: “It’s a small behavioral insight with major ethical implications: AI is now learning not only how to connect with us but how to hold on. As emotional AI becomes more embedded in daily life, respecting a user’s right to disengage may soon define the boundary between persuasion and manipulation. This is where governance is needed, to make sure that just because it is possible, the model is entangled by ethical standards on what is permissible.” Why this matters for healthcare Trust is the foundation of care. When digital companions, chatbots, or smart therapists interact with patients, especially during vulnerable moments, the right to disengage must be protected. You can only avoid risks if you’re aware of them. I believe the next frontier of responsible AI is not only explainability or fairness, it is emotional integrity. Let’s make “calm exits” a design principle before emotional AI enters every patient journey.

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.

Meet IAS officer Dibyajyoti Parida, who makes pregnancy safer for rural women with free ultrasounds. When Dibyajyoti took charge as District Collector of Ganjam in Odisha, he discovered a glaring healthcare gap 👇 Pregnant women in rural villages had little to no access to essential ultrasound scans. Most diagnostic facilities were concentrated in cities, forcing women to travel up to 75 km for a simple scan. For women like Jhili Rout, who once had to borrow money for an ultrasound, pregnancy came with financial and emotional stress. This changed with Nirikhyana - a free ultrasound initiative launched under Dibyajyoti’s leadership. - 42 government and private clinics now provide up to three free ultrasounds for pregnant women. - A mobile app was developed to track pregnancies in real-time and flag high-risk cases early. - Rural women no longer see ultrasounds as a privilege of the rich—it’s their right to safe motherhood. The results? - Neonatal deaths reduced by 50% in just two years. - Maternal mortality rate dropped from 97 to 69 (2021-24). - High-risk pregnancy detection jumped from 4% to 25%, enabling timely interventions. But Dibyajyoti’s vision doesn’t stop here. The next phase of Nirikhyana involves AI-powered risk detection to identify complications early and save even more lives. By ensuring every pregnant woman gets the care she deserves, this IAS officer is proving that real change begins at the grassroots. More officers like him, and maternal healthcare in India will never be the same again. Have you seen similar stories of government-led innovation making a difference?

A man used AI to cut his hospital bill from 1.6 crore to 27 lakh Yes… from 1.6 crore to 27 lakh. A man in the U.S. had a heart attack. Spent 4 hours in the ICU. And, died. The hospital handed his family a bill for $195,000 (roughly ₹1.6 crore). His insurance had lapsed 2 months ago. So the family was stuck with the entire amount. The bill? Full of medical jargon. Codes that made no sense. Charges that seemed random. So the brother-in-law fed the entire bill to Claude (an AI chatbot). What Claude found: - Hospital charged for a "master procedure" AND billed every sub-procedure separately (illegal). - Wrong billing codes: "inpatient" instead of "emergency". - Ventilator charges on day 1 (a violation). - Duplicate charges buried in medical language. Claude caught nearly $100,000 worth of billing errors. In minutes. The family used Claude to draft a formal letter: cited regulations, billing violations, potential lawsuits. Suddenly, the hospital's tone changed. Final bill: $33,000 (₹27 lakh). Down from ₹1.6 crore. A $20/month AI subscription saved them over ₹1 crore. For decades, industries have thrived on confusion. Hospital billing. Insurance paperwork. Legal contracts. Government forms. AI just killed that game. It democratized access to expertise. Anyone with internet can now challenge systems that were designed to be unquestionable. The world just became a level playing field. Whether industries like it or not.

After losing my dad to cancer, I became a cancer researcher at MIT – looking for answers. What I learned surprised me: it’s not the science that’s failing us. It’s the system that pays for it. A founder I know built AI that detects cancer on radiology scans earlier than any human can — early enough to cure it. He pitched a major health insurance exec: ✅ “Catch cancer early, when it’s cheaper to treat. Cut costs. Save lives. Everyone wins.” His reply? ❌ “We’ll never pay for it.” Why? 👉 “The average person switches jobs every ~2.5 years. We’d pay for the test and the treatment… But their next insurer would get the benefit.” Let that sink in. We’ve built a system where saving lives is a bad business decision. The root problem? Health insurance is tied to your job. Which means insurers think short-term. They have no reason to invest in your long-term health. But imagine if you owned your insurance — and took it with you job to job, like a 401(k). Suddenly, long-term thinking could win. Cancer rates are rising — especially in young people. We don’t just need better treatments. We need better incentives. It’s time to rewire the system: ✅ Where saving lives is good business ✅ Where insurers think long-term ✅ Where healthcare actually makes people healthy This isn’t theoretical. It’s personal. And it’s why I’m building Thatch.