Healthcare Innovation Models

We reviewed 800+ health startups in India this year. Met 200+ founders in person. These are entrepreneurs building across health tech, fitness, nutrition, software for doctors, diagnostics, healthy food, longevity, sports, elder care, women health, lifestyle management & more. This is a long post on everything we've seen and observed in 2024 at Rainmatter by Zerodha. If you're an entrepreneur, investor of health enthusiast, this is for you. 1) There is a telemedicine fatigue- The post-pandemic boom in telemedicine has plateaued. While accessibility improved, sustainable consumer engagement still remains a challenge due to weak doctor-patient relationship and lack of differentiation. Patients want emotional and personalised engagement. Most companies are overusing AI in the disguise of scale. Opportunity is to solve for depth (chronic disease management) rather than breadth (generic consultation marketplaces). 2) Overload of premium fitness and wellness Apps- Apps targeting high-income urban users are oversaturated. Most startups overestimate the willingness of users to pay for digital fitness content. Opportunity is to focus on communities, hybrid models (offline + online), or affordable mass-market solutions. India is still not ready for Peloton content. We breathe YouTube. 3) Selling SaaS tools to Doctors- Doctors in India are notoriously price-sensitive. Most SaaS products fail due to limited willingness to adopt technology and low ROI visibility. Maybe companies should emphasise on simplicity and immediate value delivery. Job of a Doctor is to deliver treatment to patients and not learn how to use software. Need to humanise software in primary and secondary health care 4) Longevity buzz- Longevity startups sound exciting but cater to a niche. Everyone loves the idea of a pill or device that adds 50 years to life. But longevity is 80% lifestyle and 20% intervention. Startups chasing the 20% often overpromise and underdeliver. Without a strong clinical base or mass appeal, they will remain limited to aspirational urban elites. Opportunity is in integrating into broader wellness solutions rather than standalone ventures 5) Healthy food & nutrition- Overcrowding of “healthy snacks” and “superfoods” where differentiation is low and margins are squeezed by Quick commerce and logistics. Maybe companies should move beyond buzzwords like “organic” or “keto” and solve for authentic, local, and culturally aligned nutrition. India is a country of a million palates 6) Chronic disease management- Diabetes, hypertension, Weight loss and mental health requires long-term engagement and behaviour modification. While the space is competitive, there is room for solutions that prioritise patient journeys and retention over time. Driving outcome has to be the focus. Everything else is a vanity feature that doesn’t earn trust. Paid marketing will get expensive customers who won’t stick around Sharing the remaining notes in the comments section. Read below

Turns out the best investment opportunities in healthcare are hiding in nausea, gallstones, and constipation. In recent conversations with several large healthcare private equity funds, the consensus is clear: GLP-1 drugs like Ozempic, Wegovy, and Mounjaro are not just transforming obesity care. They are quietly creating a secondary gold rush in treating the side effects of weight loss. And it is not small. More than 6 million Americans are already on GLP-1s. Global GLP-1 sales are expected to exceed 130 billion dollars annually by 2030. Up to 40 percent of patients experience significant gastrointestinal side effects. Around 5 to 7 percent end up with gallbladder complications. Sarcopenia is now a real concern. Mental health utilization among GLP-1 users is rising by nearly 20 percent. Fertility clinics are seeing double-digit growth from GLP-1-related cases. So while everyone is applauding the miracle of weight loss, the savviest investors are looking at the flip side. They are rolling up GI clinics, expanding ASC platforms with cholecystectomy capacity, funding digital fitness and nutrition programs to fight muscle loss, backing behavioral health services for body image and binge relapse, and building analytics tools to help payers track it all. It is not just a new drug. It is a new healthcare economy. I have unpacked this trend in detail in my latest white paper: a playbook for investing around the GLP-1 explosion by targeting the ripple effects no one is talking about. Because in healthcare, what goes down (appetite) must come up (utilization of something else). #PrivateEquity #Healthcare #GLP1 #OzempicEconomy #HealthTech #DigitalHealth #VentureCapital #ObesityCare #PEInvesting

HealthTech AI is no longer exciting. It’s expensive. And the market has re-priced itself for performance. The first half of 2025 solidified a new reality in digital health. US-based digital health startups secured $6.4 billion across 245 deals (Rock Health). While total funding is up from H1 2024, the trend of fewer, larger checks persists. Rock Health pegs the average deal size at a robust $26.1 million, a significant increase from $20.4 million in 2024, signaling a concentrated investment in more mature, impactful companies. Investors are no longer buying potential. They're buying precision and demonstrable value. They care if your AI: Saves hours, not just clicks: The focus is on quantifiable time savings for clinicians and administrative staff, directly addressing burnout and efficiency gaps. Cuts costs, not just code: Real-world cost reduction is paramount, whether through optimized operations, reduced errors, or improved resource allocation. Embeds in real workflows, not pitch decks: Solutions need to be seamlessly integrated into existing healthcare systems, proving their utility in daily practice. McKinsey calls this the "productivity premium," and it has become the new funding filter. A significant portion of VC dollars continues to flow into AI-enabled startups, not because they're novel, but because they perform and deliver tangible returns. Abridge: This AI note-taking startup for doctors raised a staggering $316 million in June 2025 (Series E), bringing its total funding to over $770 million. Its value proposition is clear: giving clinicians hours back by automating documentation. Innovaccer: Secured $275 million in Series F funding in January 2025 to expand its AI and cloud capabilities, aiming to be a "one-stop shop" for healthcare AI solutions. They focus on data aggregation and intelligence to optimize value-based care programs and reduce administrative burden. Truveta: Raised $320 million in Series C funding in January 2025, solidifying its position in health data and analytics. Their mission revolves around leveraging data to drive insights and improve care. Hippocratic AI: Completed a $141 million Series B financing round in February 2025, valuing the company at $1.64 billion. Their focus is on developing safe, patient-facing AI for non-diagnostic tasks, addressing healthcare staffing shortages. These companies optimize operations, not optics. The delta? Execution. This is not a hype cycle. It’s a competency correction. The end of vision-only founders. The rise of operator-founders who understand: Unit economics: The true cost and value generated by each patient interaction or service delivered. Integration latency: The speed and ease with which new technologies can be embedded into complex, often legacy, healthcare IT infrastructure. Reimbursement drag: Navigating the intricate and often slow process of getting innovative solutions covered by payers. What part of this feels uncomfortably true?

I’m just old enough to have practiced medicine in an analog world, where pen and paper naturally constrained information. There was only so much we could write. I remember how my hand would ache after writing an H&P and admission orders (especially if including an insulin sliding scale or heparin drip). Note bloat wasn’t an option. Information didn’t flow freely either. Learning what had happened elsewhere meant trekking to the medical records department or waiting by a fax machine. Often, it was easier to triangulate and infer the history. We know what happened next. EHRs have brought enormous benefits, but also information overload. The average medical record is now half the length of Hamlet. Our inboxes overflow with innumerable patient messages, results, and notifications. We need help. Fortunately, LLMs are very good at summarizing and transforming information. Tech analyst Scott Belsky forecasts an impending “Era of Summarized Living,” where nearly every interaction is condensed for later recall. We're already seeing this to an extent. After Zoom calls end, we now receive automated summaries with clear action items. Healthcare is heading the same way. AI scribes already summarize conversations into notes. We will soon prepare for visits by reading CliffsNotes-style digests rather than raw records. EHRs will provide contextual summaries alongside results and patient messages. This will help. And it will also change us. We’ll be one degree removed from the source information (which we would often not have reviewed anyway). We will write different kinds of notes (and may eventually stop writing them at all). We may even start speaking differently to optimize what the summaries capture (“you’re making an important point the summary should include”) . Ultimately, we may develop a kind of shared institutional memory that anyone can access. But there will be harder questions. Like what gets captured? What information gets lost? And how much of our thinking and reasoning is tied to today’s manual processes? This shift is a necessary response to the overload digitization created. I'm mostly excited about it. But I also wonder what happens when the summary becomes the reality, and whether we will maintain the discipline to return to the source when it matters.

Healthcare leaders, we’ve been here before! When we implemented EHRs, many of us thought it would be way to make our lives a little easier. Well, in many ways! It wasn’t. It was a transformation of workflows, culture, and incentive. As we now move into the era of AI, the lessons from EHR implementation are more relevant than ever. And there are importantly lessons learned that we need to keep in mind as we seek AI implementation - which our recent survey showed is gaining interest by physicians. 1. Technology alone doesn’t create value — workflow does. With EHRs, simply digitizing paper didn’t improve care. Value came when workflows were redesigned around the system. Same for AI. We need to start with the problem - and then work with tech to help solve it. Too often we start with tech and then try to find a problem to solve. That just causes frustration. 2. Clinician buy-in is everything. Resistance to EHRs wasn’t about technology — it was about loss of autonomy, increased documentation burden, and lack of consensus as to what the true goal was. If AI feels like documentation or coding requirement or added work, adoption will stall. If it reduces cognitive load and admin burden, it will thrive. 3.Usability matters more than capability. Many EHR platforms are incredibly powerful — but power didn’t always translate to usability. AI tools that are 95% accurate but seamlessly fit into clincal workflow will lose to simpler tools that fit naturally into daily practice. 4. Data quality determines outcomes. Garbage in, garbage out was a daily reality in early EHR years. How many of know records they have perpetuated inaccurate info about patients especially as it relates to medications and disease conditions? AI is even more sensitive to data integrity, bias, and standardization. 5. Governance can’t be an afterthought. Security, compliance, and ethical concerns followed EHRs for years. With AI, governance must be proactive — not reactive. And physicians needs to be involved from the very beginning 6. Change management is the REAL implementation strategy. Training, communication, feedback loops, and leadership alignment mattered more than the go-live date. It’s not the launch but rather the continuous education around these tools The biggest lesson? For AI to truly be successful, we need to focus on safely integrating it into clinical care that promotes physician and patient trust. #ehr #changemanagememt #aihealth #hit #healthit

How many adverse drug reactions could be prevented if prescribers used pharmacogenetic testing before prescribing? --- A study from last month looked into the adverse drug reaction (ADR) reports for the United Kingdom (in the comments). Of the over 1 million ADRs in the system, 9% were associated with drugs whose side effects could be prevented using genetic testing (AKA #pharmacogenetics / #pharmacogenomics (PGx)) to guide prescribing. From #pharmacy school, you learn that most drugs are metabolized by a limited number of enzymes. These enzymes can vary with patient genetics. 75% of the 9% of ADRs came from just 3 enzyme gene variations (CYP2C19, CYP2D6, SLCO1B1) that have a PGx panel test available. --- In the attached image from the study, you can see that a major opportunity for PGx testing is psychiatry drugs. 47% of the ADRs could be mitigated by PGx testing for these drugs. This would be a major improvement in #MentalHealth treatment instead of relying on trial and error, which requires 4-6 weeks for each drug the patient has to try. --- There's still huge potential for PGx to be better implemented as part of the US healthcare system. Very few providers utilize PGx routinely in practice. This is a major step in #PrecisionMedicine. The next step to make this a part of practice is checking the financial reality--how much do these tests cost and how much value do they provide in reduced adverse reactions, untreated patients, prevented hospitalizations, etc. Even with the psychiatry drugs being cheap generics, the ROI may be worth making these tests a routine part of prescribing.

Rewriting Healthcare’s Future: AI-Powered EHRs at the Core As hospitals worldwide explore AI to improve daily operations, one of the most promising breakthroughs lies in documentation and EHR management. Epic’s new generative AI tools, like MyChart’s augmented response technology, showcase how automated charting can free up clinicians to spend more quality time with patients. From reducing burnout to streamlining coding and billing, these innovations aren’t just about efficiency—they’re about empowering physicians to deliver empathetic, evidence-based care. Here are a few practical ways doctors can harness AI in the exam room today: • Voice Capture & Dictation: Use AI-powered dictation apps to convert speech into structured notes, reducing screen time and allowing more patient interaction. • Clinical Decision Support: Integrate AI modules that offer real-time suggestions for diagnoses or treatment plans based on data from similar patient cases. • Smart Summaries & Alerts: Adopt tools that automatically summarize key points from patient history and surface critical alerts (e.g., potential drug interactions) at the point of care. • Automated Order Entry: Rely on AI-driven systems that queue up suggested orders or follow-up actions, helping ensure no detail slips through the cracks. • Patient Engagement: Leverage AI chatbots or messaging drafts (like Epic’s ART) to quickly address patient questions, giving you more bandwidth for complex cases. It’s exciting to see Epic leverage vast data sets for research, real-time insights, and point-of-care support. While cost and ROI remain top of mind, the healthcare community is watching closely as AI transforms how we document, diagnose, and decide care pathways. The future of patient-centered care—supported by AI—is already here. #AIinHealthcare #DigitalHealth #ClinicianBurnout #EHRInnovation #PatientExperience #FutureOfHealthcare #HealthTech #Epic #MedicalResearch #HealthcareTransformation https://lnkd.in/eZSxZpp2

🚀 Medtech VC Investment: A Mixed Bag or a Sign of Growth? In Q3 2024, global medtech VC investment dipped to $3.2 billion, down from $3.6 billion in Q2. 📉 But before we sound the alarms, here’s why it’s not as concerning as it seems: 👉 VC deal activity was up 9.4% YoY, showing resilience despite typical Q3 seasonality. 👉 2024 deal flow is 17% ahead of 2023, reinforcing the view that last year marked the low point in the funding cycle. Yes, quarter-to-quarter fluctuations are expected, but the broader picture remains one of recovery and growth for the medtech sector. #medtech #vc #exits #medicalinnovation 💼 Exit Outcomes Shine Bright in Q3 While funding showed some choppiness, exit activity stole the spotlight: High-profile acquisitions of Endotronix, Paragonix, Innovalve, Endomag, and EndoGastric Solutions – all valued at over $100M. 💰 ⚙️ M&A: The Exit Strategy of Choice With IPO markets still challenging, M&A continues to dominate as the preferred exit route. But there’s optimism on the horizon – 2025 could see an IPO revival, as the backlog of startups nearing public readiness builds. 💡 Key Takeaway Medtech is holding steady in a volatile environment, and while quarter-to-quarter shifts in funding are inevitable, the upward trajectory remains clear. 🚀 The sector’s adaptability, bolstered by strong exits, is paving the way for a promising 2025.

Nearly 70% of healthtech innovations never reach the market. Launching a product in healthcare is 10x more complicated than regular tech products, so most first-time founders get lost along the way. After building and scaling over 100 healthtech products in the last 2 decades, here's the blueprint I use: ⏵ 1. Start with user needs Don't just survey doctors - observe them in action. Real insights come from watching how they interact with existing solutions. ⏵ 2. Prioritize regulatory compliance Begin documentation on day 1. The FDA looks at your entire development process, not just the final product. ⏵ 3. Clinical validation Get a medical advisory board early. Their expertise will shape your product and lend credibility with stakeholders. ⏵ 4. Establish data security One breach can kill your startup. Have redundant security measures, not just the minimum requirements. ⏵ 5. Design for scalability Your MVP should handle 100x your initial user base. Healthcare products can't afford downtime to rebuild. ⏵ 6. Focus on integration If you can't plug into existing hospital systems in under a week, most clients won't consider you. Period. ⏵ 7. Protect intellectual property File provisional patents before your first pitch. Healthcare giants have armies of lawyers watching startups. ⏵ 8. Plan for funding Budget 3x more time and money than you expect. The average healthtech product takes 18-24 months just to launch. Every step counts, and each decision plays a role in your success. Which step do you find most challenging? #healthtech #startups #innovation