Delta: HealthTech Innovators

Roupen Odabashian

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Welcome to 'Delta', a podcast where we delve deep into the world of healthcare transformation. Join us as we speak with Health Tech innovators, leading researchers, forward-thinking engineers, and passionate individuals dedicated to reshaping the healthcare landscape. If you're curious about the future of healthcare and those spearheading positive change, 'Delta' is your essential listen.

10月6日

AI in Medicine is BROKEN: Stanford PhD Exposes the 95% Accuracy Lie | LLMs in Healthcare

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

36 分鐘
9月22日

From $60K/Month Revenue Recovery to YC Success: How Ember is Fixing Healthcare's $10B Fraud Problem

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

24 分鐘
9月8日

How AI Turns Messy EHR Into Clear Survival Predictions

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

26 分鐘
8月25日

How AI Fixes Medical Record Errors | $125B Healthcare Problem Solved

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/

39 分鐘
7月27日

Fixing the $1 Trillion Healthcare Bottleneck with AI

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: roupen@deltahealth.tech 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

22 分鐘
7月2日

Revolutionizing MedTech: How SimAI Is Changing Medical Education Forever

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: roupen@deltahealth.tech 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

26 分鐘
6月16日

HealthTech Fundraising Secrets: AI-Driven Pitch + Investor Outreach 🇺🇸

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: roupen@deltahealth.tech 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

39 分鐘
6月1日

Healthcare Documentation with Commure | Dr. Mitchell & Ian Shakil | Health Tech Podcast

In this special episode of the Health Tech Podcast, we dive into the future of clinical documentation with Ian Shakil, founder of Augmedix, and Dr. Bill Mitchell, a practicing oncologist and real-world user of Augmedix’s ambient AI scribe. Discover how ambient AI is transforming the way physicians interact with electronic health records, saving hours per day, reducing burnout, and enhancing patient care. Learn about the journey of building Augmedix, the power of human-in-the-loop AI, and what differentiates this platform in a crowded health tech landscape. 🔔 Don’t forget to like, subscribe, and hit the bell icon to stay updated on the future of healthcare innovation! 🚀 What You’ll Learn: What is Ambient AI in healthcare? How AI scribes work in real clinical settings Time savings and impact on burnout Building a startup in a tough health tech market How Augmedix integrates with EHRs Key strategies for entrepreneurs in health tech Roupen Odabashian: LinkedIn: https://www.linkedin.com/in/roupen-odabashian-183aaa142/ X: https://twitter.com/RoupenMD Email: roupen@deltahealth.tech 🎙 Featured Guests: Dr. Bill Mitchell – Medical Oncologist, Private Practice, Charlotte, NC Ian Shakil – Founder of Augmedix LinkedIn: https://www.linkedin.com/in/ishakil/ ⏱️ Timestamps: 00:00 – Intro: What is Augmedix? 00:52 – The founder’s advice: “The obstacle is the way” 01:21 – Meet Dr. Bill Mitchell, oncologist & AI scribe user 02:14 – What is ambient documentation? 03:24 – How the AI captures notes in real time 04:20 – From Dragon to AI: The clinical experience 05:41 – The impact on patient interaction and documentation quality 06:49 – Cutting 40% of clinic time with AI 08:11 – Becoming a beta user through Cardinal/Vista 09:08 – Legal protection and accuracy through real-time capture 10:50 – How Augmedix improves workflow for support staff 12:00 – From point solution to AI platform: Augmedix’s evolution 14:04 – Differentiation from competitors 16:06 – Integration with life sciences and value-based care 17:57 – Why most ambient scribe startups will fail 19:57 – Ambient’s effect on patient perception 21:47 – Peer-to-peer learning through enhanced notes 22:59 – Why Ian Shakil founded Augmedix 26:43 – Behind-the-scenes: Ambient AI’s real value 28:44 – Advice for future health tech founders 30:09 – Co-creating with clinician champions 31:10 – Closing remarks Augmedix: https://www.augmedix.com/ Commure: https://www.commure.com/ Watch Our Podcast at YouTube: https://youtu.be/UvRvLbGMkG0 #HealthTech #AmbientAI #Augmedix #DigitalHealth #AIscribe #EHR #HealthcareInnovation #MedTech #PhysicianBurnout #OncologyCare #StartupStory #MedicalAI #HealthIT #ClinicalDocumentation

31 分鐘

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Welcome to 'Delta', a podcast where we delve deep into the world of healthcare transformation. Join us as we speak with Health Tech innovators, leading researchers, forward-thinking engineers, and passionate individuals dedicated to reshaping the healthcare landscape. If you're curious about the future of healthcare and those spearheading positive change, 'Delta' is your essential listen.

創作者

Roupen Odabashian
活躍年代

2023年 - 2025年
集數

50
年齡分級

兒少適宜
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© Delta: HealthTech Innovators
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Delta: HealthTech Innovators