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OpenEvidence just hit a $12 billion valuation — here's the full story of how it happened. Daniel Nadler sold his first company, Kensho, to S&P Global for $550 million. Then he turned his attention to one of the most broken systems in the world — medical information. Hosts Roupen Odabashian, MD and Osama Hyder break down the full story of OpenEvidence — the AI-powered clinical decision support platform now used by 40% of US physicians, handling 358,000 queries per day. We cover Daniel's origin story from Toronto to Harvard PhD, the Federal Reserve, and the founding of Kensho in 2013. We explore the $550M S&P acquisition, his parallel career as a published poet and MoMA PS1 board member, co-founder Zachary Ziegler's background, the Mayo Clinic partnership, domain-specific AI architecture, the USMLE 100% score debate, and the explosive growth that followed. The second half dives into the funding roadmap (Series A–D), product expansion into AI Scribe and DeepConsult, the direct-to-physician business model, monetization strategy, competitive analysis, network effects, and bear case risks. Whether you're a physician, a health tech founder, or an AI investor — this is the most in-depth breakdown of OpenEvidence you'll find anywhere. Subscribe for weekly deep dives: deltahealth.tech | Sponsored by PMWC 2026 — use code DELTAHEALTH at pmwcintl.com Timestamps: 00:00 - Hook: Who is Daniel Nadler & Why OpenEvidence Matters 01:46 - Welcome & Host Introductions 05:48 - Daniel Nadler's Origin Story 12:10 - Harvard PhD & The Federal Reserve 17:00 - Founding Kensho Technologies (2013) 22:00 - S&P Global Acquires Kensho for $550M 29:38 - Poetry & Art Career (MoMA PS1) 31:29 - The Information Crisis in Medicine 48:25 - The Founding of UpToDate 1:02:26 - ChatGPT Launches (November 2022) 1:15:00 - Zachary Ziegler's Background 1:21:00 - Self-Funding & Founding OpenEvidence 1:27:46 - The Mayo Clinic Partnership 1:34:46 - Technical Architecture: AI, RAG & Citations 1:46:00 - USMLE 100% Score & The Debate 1:53:30 - Growth: 358,000 Queries Per Day 2:08:00 - Funding Roadmap: Series A Through D 2:40:00 - Future of AI & The Physician Relationship 2:45:17 - Product Expansion: AI Scribe & DeepConsult 3:05:00 - Direct-to-Physician Approach 3:17:20 - Business Model & Monetization 3:32:15 - Competitive Analysis & Network Effects 3:47:00 - Bear Case & Risks Hosts: Roupen Odabashian: [email protected] | linkedin.com/in/roupen-odabashian-md-frcpc-fasco-183aaa142 Osama Hyder: [email protected] | linkedin.com/in/sam-hyder

In this episode, we dive deep into the incredible story of Doximity—the "LinkedIn for Doctors" that captured 80% of US physicians and became one of healthcare's most under-the-radar success stories. Thank you for the sponser of today’s episode 🎟️ PMWC Conference – Use code DELTAHEALTH at pmwcintl.com for a discount! 🔑 What You'll Learn: How founder Jeff Tangney went from Epocrates (the first medical app on iPhone, endorsed by Steve Jobs) to building DoximityWhy Doximity succeeded where competitors like Sermo and Osmosis failedThe brilliant business model that keeps physicians happy while generating billionsHow COVID-19 transformed Doximity's telehealth tools from 1M calls/month to 1M calls/dayStrategic acquisitions: Curative (staffing), Amion (scheduling), and Pathway (AI clinical decision support)The explosive launch of Doximity GPT and the AI scribe warsThe controversial Open Evidence lawsuit shaking up healthcare AI⚠️ Disclaimer: This is not financial advice. Do your own due diligence. Doximity Links 🌐 Website: doximity.com📈 Investor Relations: investors.doximity.com💼 Doximity LinkedIn: linkedin.com/company/doximity📱 Doximity App (iOS): apps.apple.com/us/app/doximity/id393714498🏥 Curative (Physician Staffing): curative.com🩺 Pathway Medical: pathway.mdHosts Roupen Odabashian LinkedIn: linkedin.com/in/roupen-odabashian-md-frcpc-fasco-183aaa142/Email: [email protected] Hyder LinkedIn: https://linkedin.com/in/sam-hyderEmail: [email protected]🎧 Subscribe for more deep dives into the playbooks of successful healthcare companies! #Doximity #HealthTech #DigitalHealth #Telemedicine #PhysicianNetwork #StartupStory #HealthcareAI #LinkedInForDoctors

Join us for an insightful conversation with Dr. Rishi Khakhkhar, Chief Medical Officer at Counsel Health, as we explore how this AI-enabled virtual care company is transforming the way patients access healthcare through chat-based, physician-supervised medical AI. In this episode, we dive deep into: - How Counsel Health combines medical AI with real physicians for safe, supervised care - The patient journey: from AI-powered intake to physician consultation - Asynchronous vs. synchronous care and what it means for busy patients - Emergency escalation protocols and patient safety in AI-enabled care - The "clinician cockpit" - AI tools built for physicians by physicians - The future of longitudinal patient-physician relationships in virtual care - Counsel Health's $35M Series A led by Andreessen Horowitz and Google Ventures Dr. Khakhkhar shares his journey from ER physician at Mount Sinai during COVID-19 to helping build the next generation of telemedicine, and why he believes AI will help physicians focus on what matters most - the human moments of care. Timestamps 00:00 – Introduction 01:28 – Dr. Khakhkhar's Background & How He Joined Counsel Health 04:48 – The Patient Journey: From AI Chat to Physician 09:00 – Longitudinal Care & the Patient-Doctor Relationship 12:00 – Asynchronous vs. Near-Synchronous Care 15:00 – Emergency Escalation & Patient Safety Protocols 19:00 – AI as a Team Member, Not a Replacement 22:00 – Dr. Khakhkhar's Journey: COVID-19 & Virtual Care 24:22 – Funding: $35M Series A from a16z & Google Ventures 27:00 – The Clinician Cockpit: AI Tools for Physicians 31:00 – Isolating the Human Moment in Medicine LinkedIn: https://www.linkedin.com/in/rishi-khakhkhar About Counsel Health Founded by Dr. Muthu Alagappan (former CMO of Notable Health, Stanford MD), Counsel Health is an AI-enabled virtual care company on a mission to be the primary doctor for the next billion people on earth. Company Website: https://www.counselhealth.com Company LinkedIn: https://www.linkedin.com/company/counselhealth Founder LinkedIn (Dr. Muthu Alagappan): https://www.linkedin.com/in/muthualagappan Host: Dr. Roupen Odabashian, MD, FRCPC, FASCO Hematology-Oncology Physician | Healthcare Innovation Enthusiast Connect with Us: 🎙️ Podcast: Delta HealthTech Innovators 💼 Host LinkedIn: https://www.linkedin.com/in/roupen-odabashian-md-frcpc-fasco-183aaa142 📧 Email: [email protected] Listen on: 🍎 Apple Podcasts: https://podcasts.apple.com/us/podcast/delta-healthtech-innovators/id1703827145 ▶️ YouTube: https://www.youtube.com/@RoubenOdabashianMD 🎧 Spotify: https://open.spotify.com/show/2vYC26pNkZVIhsqloNcCm9

Preventing Dialysis Access Failure: How Auvi Labs is Building a Wearable Ultrasound Device | Rishab Veldur & Kevin Volkema In this episode, I sit down with Rishab Veldur (CEO) and Kevin Volkema (COO) from Auvi Labs to discuss how they're tackling a critical problem in dialysis care. 40% of dialysis patients experience fistula or graft failure within their first year—leading to endless hospitalizations and life-threatening situations. Auvi Labs is building "Beacon," a wearable ultrasound patch that patients can use for just 10 minutes a day to detect early signs of access failure. We dive deep into their journey from a university capstone project to launching clinical pilots, the challenges of building a healthcare startup, and their unique approach to networking and building clinical partnerships. Whether you're a healthcare founder, engineer, or just interested in medtech innovation, this episode is packed with actionable insights. Timestamps • 00:00 – Introduction • 01:00 – The Problem: Dialysis Access Failure • 03:15 – From Acoustic Device to Wearable Ultrasound • 10:06 – The 20-Patient Pilot Study • 11:52 – How to Find Clinical Pilots • 17:40 – Networking Playbook for Healthcare Founders • 21:01 – The Power of a Founder Newsletter • 23:45 – Business Model & Value-Based Care • 29:19 – Biggest Risks & Clinical Integration Challenges • 36:04 – Bottlenecks for Scaling Key Takeaways 1 Start with the problem, not the solution – They pivoted from an acoustic device to ultrasound after learning what patients and physicians actually needed 2 Healthcare is relationship-based – Cold outreach has low success; invest in building genuine connections over time 3 Skip the big conferences early on – Niche events and reaching out to researchers on Google Scholar yields better results 4 Use your student email – Everyone wants to help students 5 Send a newsletter – Share highs AND lows to bring people along on your journey 6 Value-based care is the path – Working with kidney contracting entities can bypass traditional CPT code reimbursement Guest Links • 🌐 Website: auvilabs.com • 💼 Rishab Veldur (CEO) LinkedIn: https://www.linkedin.com/in/rishab-veldur/ • 💼 Kevin Volkema (COO) LinkedIn: https://www.linkedin.com/in/kevinvolkema/ Host • 💼 Roupen Odabashian LinkedIn: https://www.linkedin.com/in/roupen-odabashian-md-frcpc-fasco-183aaa142/ • 📧 Email: [email protected] #healthcarestartup #medtech #dialysis #wearables #digitalhealth #medicaldevice #startup #healthcare #founders

Join us for an incredible conversation with Dr. Amit Phull, Chief Physician Experience Officer at Doximity, as we explore how the largest professional medical network in the United States is revolutionizing healthcare with AI-powered tools built by physicians, for physicians. In this episode, we dive deep into: - How Doximity grew to serve over 80% of U.S. physicians - The development of HIPAA-compliant AI tools including Doximity GPT - The importance of clinician input in healthcare technology - Real-world impact: How AI is saving physicians hours and improving patient care - The acquisition of Pathway (Montreal-based company) and integration of clinical decision support - Privacy-focused AI scribe technology generating millions of notes - Lessons learned from product failures and successes Dr. Phull shares his unique journey from computer engineering to emergency medicine, and how maintaining both clinical practice and tech expertise positions him to bridge the gap between technology and healthcare delivery. Timestamps [00:00:00] Introduction & Welcome [00:01:24] Dr. Phull's Journey: Computer Engineer to Emergency Physician [00:04:00] Role as Chief Physician Experience Officer [00:06:41] Why Maintaining Clinical Practice Matters [00:11:04] Introduction to Doximity Tools & Platform [00:14:52] The Secret Sauce: Clinician-Driven Development [00:18:44] Doximity GPT Evolution & HIPAA Compliance [00:22:21] Acquiring Pathway AI (Montreal) [00:28:41] AI Scribe: Privacy-First Documentation [00:30:52] Lessons from Product Failures [00:36:18] Success Story: 10% to 90% Prior Auth Approval Rate About Our Guest Dr. Amit Phull, MD Chief Physician Experience Officer, Doximity Board-Certified Emergency Medicine Physician Adjunct Lecturer, Northwestern University Feinberg School of Medicine Dr. Phull combines deep expertise in medicine, technology, and strategy. He completed his MD at University of Virginia (where he also earned a BS in Computer Science), finished emergency medicine residency at Northwestern, and has been with Doximity since 2014. He continues to practice emergency medicine while leading physician experience strategy for the nation's largest medical professional network. LinkedIn: https://www.linkedin.com/in/amit-phull-09931667/ Doximity Website: https://www.doximity.com Doximity LinkedIn: https://www.linkedin.com/company/doximity My email: [email protected] YouTube: https://youtu.be/ElB-a5Mubm4

Why do 30% of patients take medications differently than what's in their medical records? Dr. Eve Cunningham, Chief Medical Officer at Cadence, reveals the shocking gaps in traditional healthcare—and how remote patient monitoring is revolutionizing chronic disease management for 70,000+ patients across 20 health systems. In this episode, we dive deep into: ✅ The hidden cost of episodic vs. continuous care ✅ How a practicing OB-GYN broke into healthtech leadership ✅ Why 20% of medication changes are actually DOWN-titrations ✅ The future of AI-powered clinical decision support ✅ Real outcomes: 18% fewer hospitalizations, $183/month savings per patient TimeStamps: Dr. Cunningham spent 20 years leading physician groups at Kaiser Permanente, CommonSpirit, and Providence before joining Cadence—a remote patient monitoring company backed by $141M from General Catalyst and Thrive Capital. She shares candid insights on physician leadership, technology transformation, and why clinicians MUST develop technical competency. 🎯 Perfect for healthcare entrepreneurs, medtech founders, physicians exploring innovation, and anyone building the future of digital health. KEY TOPICS COVERED: Remote patient monitoring at scale (70,000+ patients) Clinical AI and machine learning in chronic disease management Breaking into healthtech from clinical practice Value-based care and Medicare reimbursement (CPT codes 99453, 99454, 99457, 99458) Medication reconciliation and polypharmacy management Virtual care infrastructure: telehealth, virtual nursing, hospital-at-home Technology adoption in large health systems The emerging clinician-engineer hybrid role Deprescribing and down-titration opportunities Social determinants of health and caregiver engagement PUBLISHED OUTCOMES: 📊 New England Journal of Medicine: Catalyst validates Cadence's model: https://catalyst.nejm.org/doi/abs/10.1056/CAT.24.0521 CONNECT WITH DR. EVE CUNNINGHAM: LinkedIn: https://www.linkedin.com/in/evecunninghammd/ 🔗 CONNECT WITH CADENCE: Company LinkedIn: https://www.linkedin.com/company/cadencerpm Website: https://www.cadence.care/ Published Research: https://www.cadence.care/outcomes-report-2024

​MalkeAsaad, plastic surgery resident and founder of Rank RX, shares how he built an AI platform using large language models to revolutionize residency application screening. From med school in war-torn Aleppo to Mayo Clinic and MD Anderson, Malke discusses the unfair filtering system that inspired Rank RX—where Nobel Prize laureates get rejected for missing a cutoff by one point—and how AI can make hiring more objective and efficient. What you'll learn: - Why the current residency application system is broken (Nobel Prize winner rejected for 1-point score gap) - How Rank RX uses AI/LLMs to screen 1,000–2,000 applications (30–80 pages each) in minutes - Building a tech team as a physician entrepreneur without coding background - Customer acquisition strategies for healthcare startups (networking, ads, vendor screening) - Market validation: assessing if your solution solves a real problem people will pay for Timestamps - 0:00 – Unfair residency filtering: Nobel Prize winner rejected for 1-point gap - 1:14 – Malke Assad’s journey: From Aleppo to leading U.S. institutions - 3:45 – Rank RX: How AI/LLMs bring objectivity to application screening - 4:21 – How it works: Custom scoring and program-driven selection criteria - 8:36 – Real-world usage: Positive feedback and automated recommendation letter analysis - 10:32 – Building a tech team without a coding background - 17:35 – Key advice for physician entrepreneurs: Turning ideas into scalable companies - RankRX Website: https://www.rank-rx.com/ - Malke Assad LinkedIn: https://www.linkedin.com/in/malke-asaad-43b908177 - The Match Guy Website: https://thematchguy.thinkific.com

When Sahil and his brother started Otoset in their mid-20s, they had no idea their FDA-cleared ear cleaning device would generate over 1 billion social media views and force them to completely pivot their business model. In this episode, Sahil shares the unexpected journey from building a B2B medical device company to creating "the front door to ear care", a direct-to-consumer healthcare network serving 40 million Americans with chronic ear wax issues. 🔑 KEY TAKEAWAYS: → How they became some of the youngest founders to get FDA 510(k) clearance → The unexpected social media virality that changed everything → Why they pivoted from partner clinics to owning their own locations → Marketing strategies: organic content, influencers, and patient education → The critical role of FDA clearance as a competitive differentiator → Building credibility before scaling consumer marketing → Finding the right mentors in healthcare entrepreneurship 💡 WHO THIS IS FOR: ✓ HealthTech & MedTech founders navigating FDA pathways ✓ Startups exploring direct-to-consumer healthcare models ✓ Entrepreneurs learning to leverage social media for medical products ✓ Anyone interested in the consumerization of healthcare 📊 BY THE NUMBERS: - 40 million Americans affected by ear wax buildup - 1 billion+ views across social media - $99 cash-pay model (first treatment) - 20-30 patients/day in company-owned clinics - Expanding to 50+ major metros Timestamps: 00:00 - Introduction: The Brother's Ear Wax Problem 01:21 - What is Otoset? The First FDA-Cleared Ear Cleaning Device 03:22 - Why FDA Clearance Matters & How They Got It 06:56 - The Unexpected Social Media Explosion 08:55 - The Strategic Pivot: B2B Device to D2C Healthcare Network 11:36 - Business Model: $99 Cash-Pay & Building Owned Clinics 15:18 - Beyond Ear Care: Hearing Health & Expansion Plans 17:15 - Marketing Strategy: Organic, Influencers & Patient Education 20:33 - Building Credibility Before Scaling Consumer Marketing 22:35 - Biggest Lesson: Find Healthcare Entrepreneur Mentors Early 24:33 - Final Thoughts & Key Takeaways 📌 Key Resources & Links 🔗 Otoset Website: https://otoset.com/ 🔗 Otoset Linkedin: https://www.linkedin.com/company/visitallears/ 🏥 Find a Certified Clinic: https://otoset.com/pages/find-clinic 💼 Connect with Sahil: https://www.linkedin.com/in/sahildiwan/

Is AI really ready to replace doctors? Stanford PhD researcher Suana reveals shocking truths about medical AI that Big Tech doesn't want you to know. When she tested leading AI models like GPT-4, Claude, and DeepSeek on modified medical questions, their accuracy plummeted by up to 40%!In this eye-opening conversation, we dive deep into: ❌ Why 95%+ accuracy on medical exams means nothing in real clinical practice ❌ How AI models fail when there's "no right answer" (which happens constantly in medicine) ❌ The dangerous gap between flashy headlines and clinical reality ✅ How doctors can safely use AI as a co-pilot (not replacement) ✅ The future of medical AI evaluation and what needs to changeSuana is a 3rd-year PhD student at Stanford in Biomedical Data Science, pioneering real-world evaluation methods for medical AI. Her research on MedELM and benchmarking is reshaping how we think about AI deployment in healthcare.🔬 Key Research Discussed: JAMA Open publication on AI robustness in medical diagnosis MedELM: 35-dataset benchmark suite for real clinical tasks Why MedQA and USMLE-style tests don't reflect actual patient care ⚠️ CRITICAL TAKEAWAY: AI models are trained to always give an answer, even when "none of the above" is correct—a potentially dangerous flaw in medical decision-making.📚 Resources Mentioned: MedELM Leaderboard (public repository available) Research on medical AI evaluation standards Real-world hospital deployment considerations Timestamps: 0:00 - Introduction: Why Medical AI Evaluation is Broken 1:04 - Suana's Journey: From Computer Science to Healthcare AI 2:32 - The 3 Critical Problems with Current AI Benchmarks 8:28 - The Research: Testing AI with "None of the Above" 17:24 - Shocking Results: AI Accuracy Drops 8-40% 19:02 - Why AI Can't Say "I Don't Know" 23:10 - Take-Home Message: Use AI as Co-Pilot, Not Replacement 24:58 - Real Clinical Examples: When AI Actually Helps 28:12 - MedELM: The Future of Medical AI Evaluation 34:35 - Final Advice for Doctors, Patients & Developers Whether you're a physician, healthcare worker, AI developer, or patient curious about medical AI, this conversation will change how you think about artificial intelligence in healthcare. Paper link: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2837372

Healthcare revenue integrity is broken, and Charlene, CEO of Ember, is fixing it with AI. In this episode, she reveals how hospitals lose millions due to inefficient billing processes and how her platform helps recover 51% of initially denied claims. From her background at Google Health to building a YC-backed startup that's generating over $60,000 per month in additional revenue for clients, Charlene shares the secrets behind focusing on one specific problem and executing flawlessly. Key topics covered: Healthcare revenue cycle management, AI in medical billing, startup focus strategies, building in regulated industries, and the future of healthcare fraud detection. Perfect for healthcare executives, CFOs, startup founders, and anyone interested in healthtech innovation. Timestamps 0:00 Introduction & Ember Overview 1:05 What is Revenue Integrity in Healthcare? 2:31 Ambient Listening & Clinical Documentation 4:10 Product Implementation & Integration Process 6:02 Real Results: $60K+ Monthly Revenue Recovery 8:33 Technical Deep Dive: How Ember Works 10:28 Charlene's Background & Healthcare Industry Insights 12:53 The $10B Healthcare Fraud Problem 16:17 Y Combinator Experience & Startup Focus 18:22 Building the Right Team (3-Year Journey) 21:44 Future Vision for Ember 22:41 Advice for Healthcare Entrepreneurs

Can AI forecast ICU risk from the first 36 hours of EHR data? University of Washington researcher Sihan explains TrajSurv, a survival-prediction model that converts noisy, irregular ICU time series into interpretable latent trajectories using Neural Controlled Differential Equations (NCDEs) and time-aware contrastive learning aligned to SOFA. We cover how trajectories outperform snapshots, handle missingness without heavy imputation, and remain clinically legible via vector-field feature importance and trajectory clustering. Validated on MIMIC-III and eICU with reported C-index ≈0.80 and cross-cohort ≈0.76, TrajSurv points to safer escalation, de-escalation, and bed allocation in the ICU. In this episode: survival prediction basics; limits of Cox/RSF vs deep time-series models; NCDE explained in plain language; first-36h feature set (53 labs/vitals/demographics); metrics (C-index, Brier, dynamic AUC); interpretable clustering linked to outcomes; and what’s next—adding interventions for counterfactual simulation and extending to oncology. Link to the paper: https://arxiv.org/abs/2508.00657 Timestamps 00:00 Why trajectories beat snapshots in EHR 01:00 Guest intro: Sihan, UW Biomedical Informatics 01:40 Survival prediction 101 and clinical use 03:40 From Cox/RSF to deep learning on time-varying data 05:03 What is TrajSurv (pronounced “traj-surf”)? 06:16 NCDE explained with the “ship + weather” analogy 08:14 Handling irregular sampling and missing data 09:14 Time-aware contrastive learning aligned to SOFA 10:47 Datasets: MIMIC-III and eICU; first 36h features (labs, vitals, demo) 12:40 Results: C-index ≈0.80; cross-cohort ≈0.76; interpretability 14:30 Workflow: CDS, monitoring, escalation, de-escalation 16:15 Why humans miss multi-variable long-horizon trends 18:21 Latent trajectory clustering and survival differences 23:18 Next: interventions, counterfactuals, oncology applications 25:40 Closing Roupen Odabashian LinkedIn: https://www.linkedin.com/in/roupen-odabashian-md-frcpc-abim-183aaa142/ Sihang Zeng: https://www.linkedin.com/in/zengsh/ #HealthcareAI #ClinicalDecisionSupport #EHR #ICU #SurvivalAnalysis #DeepLearning #NCDE #MIMICIII #eICU #SOFA

Medical documentation errors cost U.S. hospitals over $70 billion in denied claims and $55 billion in lawsuits every year. In this episode, we sit down with Dimitri, Founder & CEO of WorkDone Health, a Y Combinator-backed startup that’s building the "Grammarly for medical records." WorkDone Health automates chart review, compliance checks, and billing validation in real-time, preventing errors before they cost hospitals money—or compromise patient safety. We explore: Why CFOs are the first to feel the pain of documentation errors How AI-powered compliance and quality checks reduce denials Lessons from Y Combinator and scaling a healthcare startup Why WorkDone could be the antidote to insurance AI denials If you’re a healthcare leader, investor, or builder in healthtech, this episode shows the future of clinical documentation. Timestamps: 0:00 – Intro: The cost of documentation errors ($70B in denials, $55B lawsuits) 1:00 – Dimitri’s journey: From physics to healthcare AI 3:00 – The problem: Reactive vs. proactive documentation review 5:15 – Real-world example: Left vs. right shoulder conflict 7:00 – Sepsis bundle case study 9:00 – How WorkDone Health prevents denials in real time 12:00 – Impact on CFO metrics: denials, lawsuits, billing cycle 14:30 – The “antidote” to insurance AI claim denials 18:00 – How the tool works: real-time vs. batch checks 22:00 – Prioritization of alerts: reducing physician burden 27:00 – Vision: “Grammarly for medical documentation” 29:00 – Lessons from Y Combinator for healthtech startups 32:00 – HIPAA compliance and why it matters from Day 1 37:00 – Future of WorkDone: API integrations with EMRs Dimtry Karpov: https://www.linkedin.com/in/dmitrykarpov/ WorkDone: https://www.linkedin.com/company/workdonehealth/ WorkDone: https://www.wrkdn.com/ Roupen Odabashian: https://www.linkedin.com/in/roupen-odabashian-md-frcpc-abim-183aaa142/

In this episode, we sit down with Chuck Feerick, founder and CEO of Latitude Health, a MedTech startup tackling one of the most overlooked — yet critically expensive — problems in healthcare: prior authorization and utilization management. Chuck shares how a personal experience in his early 20s inspired him to transform the way health plans make care decisions, using AI to reduce administrative burdens and accelerate patient access to treatment. With a background spanning health plan operations, venture capital, and startups, Chuck brings a 360° perspective on what it really takes to build a successful health tech company. We dive into: The $1 trillion administrative crisis in U.S. healthcareWhy prior authorization delays hurt patients and providersHow Latitude Health uses AI to empower—not replace—cliniciansThe real challenges of selling to health plansWhat every health tech founder must understand about procurement, ROI, and building painkiller productsThe future of AI in care decision-makingWhether you're a health tech entrepreneur, investor, or healthcare executive, this conversation is full of practical insights on solving big, unsexy problems with massive impact. 00:00 – Intro: Can AI Fix Healthcare? 01:03 – Meet Chuck Feerick, Founder of Latitude Health 02:15 – A Personal Story That Sparked a HealthTech Mission 04:10 – The Broken Prior Authorization Process Explained 06:32 – Automating Utilization Management with AI 08:44 – What Latitude Health Actually Does 10:05 – How Patients, Providers & Payers Benefit 12:20 – Chuck’s Journey: Operator, Investor, Founder 14:15 – Lessons from VC for Startup Fundraising in MedTech 16:01 – How to Sell to Payers: Complex Sales in Healthcare 18:30 – The Role of AI vs. Human in Clinical Decision Making 21:04 – How Latitude Uses LLMs to Structure Medical Data 23:19 – Training AI with Clinicians: Nurses, Doctors, CMO Input 25:12 – Building a HealthTech Startup the Right Way 27:00 – Tackling Long Sales Cycles in Healthcare 28:42 – AI is Moving Fast — Building for Flexibility 30:18 – The Unsexy Problem That Needed Solving 33:07 – Why Utilization Management Is the Key to Controlling Costs 35:45 – Administrative Waste: The $1 Trillion Opportunity 37:02 – Why Latitude Focuses on High-Impact Painkiller Tools 38:49 – Consumers, Behavior, and the ROI of Innovation 41:00 – Closing Thoughts: What Founders Must Understand About Healthcare Roupen Odabashian: LinkedIn: https://www.linkedin.com/in/roupen-odabashian-183aaa142/ X: https://twitter.com/RoupenMD Email: [email protected] Tigran (Tiko) Bdoyan: LinkedIn: https://www.linkedin.com/in/chuckfeerick Watch Our Podcast at: https://youtu.be/Xj89GFyPpxw #MedicalStartup #Telehealth #SimulatedPatients #Fundraising #MedicalSchoolTools #CME #AIinMedicalEducation #CasperExam

In this episode, we dive deep into the future of MedTech and HealthTech innovation with Tikran Bdoyan, co-founder of SimAI, an AI-driven platform transforming medical education through realistic virtual patients. Learn how SimAI is: Reducing training bottlenecks in healthcareAccelerating student evaluation and feedbackSupporting medical schools, residency programs, and CME globallyHelping international students and telehealth teams scale their trainingWe also explore: SimAI’s journey through Y CombinatorFundraising in hard-to-crack spaces like healthcare and edtechThe growing role of AI in clinical education and patient simulationTimestamps: 00:00 – Intro: Why MedTech Needs Disruption 01:07 – Meet Tikran Bdoyan, Co-Founder of SimAI 02:22 – The Problem in Medical Education Today 04:11 – What is SimAI? AI Patients Explained 06:03 – From Reddit Post to Startup Breakthrough 07:36 – The Global Demand for AI in Clinical Training 09:15 – Why Medical Exams Are Outdated 11:27 – Real-Life Benefits of SimAI for Students & Professionals 13:35 – Getting into Y Combinator: SimAI’s Journey 15:40 – The Power of Focus and Realistic Expectations 18:01 – Why Healthcare Sales Cycles Are So Slow 19:38 – Customizing AI Patients for Schools 21:25 – Instructor Tools & Performance Insights 23:16 – Use Cases: Residency, CME & Telehealth 25:12 – Fundraising in MedTech & EdTech: The Challenges 27:06 – Finding Product-Market Fit in Counseling 28:55 – SimAI’s Global TAM: US, India, Canada, IMGs 31:00 – New Trends: AI-Augmented Practitioners 32:54 – The Future of AI in Medical Education (10-Year Outlook) 34:51 – Standardizing Bedside Manner Evaluation 36:27 – Cost & Limitations of Simulated Patients 38:19 – What Tikran Wishes He Knew Before Starting 40:00 – Final Advice: Do More, Compete Less Roupen Odabashian: LinkedIn: https://www.linkedin.com/in/roupen-odabashian-183aaa142/ X: https://twitter.com/RoupenMD Email: [email protected] Tigran (Tiko) Bdoyan: LinkedIn: https://www.linkedin.com/in/tigran-bdoyan/ Watch Our Podcast at https://youtu.be/7rmuSgTqkYw #MedicalStartup #Telehealth #SimulatedPatients #Fundraising #MedicalSchoolTools #CME #AIinMedicalEducation #CasperExam

Unlock proven strategies for HealthTech & MedTech startups to raise capital efficiently—from designing a lean deck and model to implementing AI powered outreach. In this episode, Jeff Fidelman, Harvard trained banker turned venture advisor, reveals why "Fundraising as a Service" is the next game changer in investor relations. Dive into: • Common funding mistakes founders make (like skipping the ask 😳) • Structuring your pitch (deck + model + valuation = 🟢) • Navigating SAFE vs. convertible notes • How AI reduces your MVP time & fundraising cost 👉 Ideal for startup founders, HealthTech entrepreneurs, and media tech innovators ready to scale with smart capital strategies. Timestamps: 00:00 Why fundraising execution matters 01:06 Meet Jeff Fidelman – HealthTech fundraising guru 02:03 Jeff’s path: from Morgan Stanley to venture banking 05:03 Why founders fail at decks & modeling 07:00 What "Fundraising as a Service" really means 10:42 Don’t forget to ASK for money 13:00 How investors evaluate your ROI 14:28 Customer vs. investor psychology 19:06 Equity dilution: how much you should give 22:18 SAFE vs. Convertible Notes—founder friendly? 23:50 The 3 critical slides: Problem, Market, Solution 27:43 Use anecdotes to sell your story 30:42 Funding sources in 2025: VC, angels, family offices 35:27 How AI is accelerating MVPs & fundraising process Roupen Odabashian: LinkedIn: https://www.linkedin.com/in/roupen-odabashian-183aaa142/ X: https://twitter.com/RoupenMD Email: [email protected] Jeffrey Fidelman: LinkedIn: https://www.linkedin.com/in/jeffreyfidelman/ Watch Our Podcast at YouTube #HealthTech, #MedTech, #StartupFundraising, #VentureCapital, #PitchDeck, #StartupTips, #Founders, #SAFEvsConvertible, #StartupEquity, #StartupDilution, #RaisingCapital, #HealthcareStartups, #FundraisingStrategy, #InvestorRelations, #StartupMVP, #AIForStartups, #SeedFunding, #SeriesA, #StartupMistakes, #JeffFidelman