Mar 27, 2025 · 38m · no-priors
No Priors Ep. 108 | With Abridge Founder and CEO Shiv Rao, MD
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In this episode of No Priors, host Sarah Guo interviews Dr. Shiv Rao, practicing cardiologist and CEO of Abridge, to discuss how clinical generative AI is revolutionizing healthcare documentation. Dr. Rao details Abridge's technical architecture, enterprise go-to-market strategy, and mission to eliminate clinician burnout by transforming doctor-patient conversations into structured medical records.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. The hosts hold 7.6% of the talking time here. How this is scored →
The hosts as informed peer 4.3 Guest teaching 4.9 Guest disagreement 0.6 The hosts pushing back 0.7
speaking balance: gold is the hosts, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 15:07 Reframing voice recognition as an unsolved specialized problem
Shiv politely dismisses the assumption that generic speech APIs suffice for healthcare, emphasizing pronunciation variability in oncology medications and complex dialectal nuances.
Hardest push from the hosts ▶ 7:42 Challenging healthtech adoption speed assumptionsSarah presses on why health systems are adopting AI at historic speeds despite healthcare historically lagging a decade behind in software adoption.
Biggest teaching moment ▶ 3:03 The reality of clinical notes as billing artifactsShiv breaks down medical documentation economics, teaching that US doctors are reimbursed strictly for documented care rather than care delivery itself.
The host holds their own ▶ 25:26 Grounding adoption curves in healthtech historyThe hosts leverage personal venture and founding history to challenge tech optimism by contrasting benchmark success like Med-PaLM 2 with real-world enterprise adoption barriers.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The hosts as informed peer | Guest teaching | Guest disagreement | The hosts pushing back | Why |
|---|---|---|---|---|---|---|
| Abridge's Founding Thesis on Medical Conversations | 4 | 5 | 1 | 1 | Sarah sets the context and asks Shiv to explain the distinction between a clinical note and a billable note. Shiv educates listeners on how physician reimbursement functions around documentation rather than raw care. | |
| Targeting Enterprise Health Systems Over Mid-Market | 3 | 6 | 1 | 0 | Shiv details Abridge's counter-intuitive strategic decision to target large academic health systems rather than small practices due to higher barriers to entry and scientific defensibility. Sarah listens as Shiv explains the technical bar. | |
| Physician-Led Strategy and Rapid Enterprise Adoption | 4 | 4 | 0 | 0 | Sarah highlights Abridge's high-profile customer roster and asks how Shiv's background as an active cardiologist informs GTM and product development. Shiv shares his background balancing medicine and venture. | |
| The Alignment of Burnout and Generative AI | 5 | 4 | 1 | 2 | Sarah draws on her decade of venture experience observing slow adoption in healthtech to question why the market is suddenly moving fast. Shiv explains the confluence of post-pandemic burnout and the catalyst of generative AI. | |
| Ecosystem Trust, EHR Integrations, and Competitive Advantage | 4 | 5 | 1 | 1 | Sarah asks how Abridge overcomes incumbent enterprise inertia and navigates health ecosystem partnerships. Shiv details earning trust as core infrastructure and competing head-to-head with Microsoft. | |
| Technical Architecture: Multilingual ASR to Clinical Synthesis | 5 | 7 | 2 | 2 | Sarah probes whether off-the-shelf voice APIs make speech recognition a solved problem. Shiv pushes back with deep domain knowledge, detailing phonetic medical terminology, multilingual polyglot conversations, and agentic clinical synthesis. | |
| Expanding the Frontier: Orders, Trials, and Decision Support | 4 | 5 | 0 | 0 | Sarah asks about roadmap prioritization between specialized translation and broader clerical tasks. Shiv lays out how upstream medical conversations naturally feed into downstream orders, revenue cycle coding, and real-time clinical decision support. | |
| Scale, Contextual Reasoning, and Post-Training Feedback Loops | 5 | 5 | 0 | 0 | Sarah asks for the macro view on healthcare AI timeframes. Shiv explains how operating at scale provides millions of physician edits, fueling fine-tuning, preference optimization, and post-training reinforcement learning. | |
| Adoption Wedges and Collaborative AI in Clinical Practice | 6 | 4 | 1 | 1 | The co-host/speaker brings up prior digital health founding experience and notes how models like Med-PaLM 2 stalled in adoption. Shiv agrees and outlines his framework of lower-stakes, high-frequency wedges with collaborative human-in-the-loop AI. | |
| Balancing Enterprise Personas and Complex Clinical Workflows | 4 | 5 | 0 | 1 | Sarah inquires how Abridge defines minimum viable quality when balancing diverse stakeholder personas. Shiv walks through satisfying CMIO, CIO, and CFO requirements while handling discontinuous ER workflows. | |
| Patient Empowerment, Ending Pajama Time, and Love Stories | 3 | 4 | 0 | 0 | Shiv reflects on founding Abridge, recounting a poignant story about a cancer patient's husband taking notes and sharing feedback from their internal 'Love Stories' channel about eliminating clerical pajama time. |
Statements from this episode (17)
Rao: Doctors and Nurses Will Not Be Fully Automated in 10 Years
“And the thesis for us in healthcare delivery is that we don't think doctors or nurses are going to get fully automated over the next 10 years.”
Rao: Two in five doctors and 27% of nurses want to quit
“Two out of five doctors don't want to be doctors in the next two to three years and 27% of nurses per a JAMA article that was published last year don't want to be nurses in the next 12 months.”
Rao: US doctors are paid for documented care, making every note a bill
“In this country, we're not compensated as doctors for the care that we deliver. We're compensated for the care that we documented that we deliver. So every single one of these notes is actually a bill.”
Rao: Enterprise Focus Limited Abridge's Competition to One Rival
“Running into that end of the market allowed us to sort of compete with just Pretty much one other company, while a lot of the other startups were starting mid market or, you know, down market individual like primary care doctors with the hope probably over tim…”
Dr. Shiv Rao: Abridge is live in over 110 health systems
“We're live in over, I think it's like over a 110 health systems right now.”
Rao: Replacing a Clinician Costs Health Systems Close to $1 Million
“The cost is sort of like hire another clinician is like close to a million dollars and it takes a long time.”
Failed hospital AI deployments lock startups out via CIO WhatsApp groups
“All these CMIOs and CIOs are on WhatsApp groups every single day and talking to each other. And if you screw up with one of those health systems, maybe two of those health systems, you're kind of done for like a couple years, probably. You don't get another sh…”
Shiv Rao: Abridge has never lost a head-to-head evaluation against Microsoft
“Now, the, you know, who we're competing with is Microsoft. That's who we essentially almost, like always have to do a head-to-head against, and it's usually, like, three to four weeks. And then we sort of move on from there. And so far we've never lost a head …”
Shiv Rao: Abridge competitor's 2022 solution relied on manual scribes in Bangalore
“And at that point in time, like the large competitor, they had a solution in the space, but it was humans in the loop. So it was really like Indians in Bangalore who were listening to audio and writing the note and Wizard of Oz-ing it back into the medical rec…”
Rao: Abridge processes tens of thousands of non-English clinical conversations daily
“And so today in California, we'll probably do 50,000 conversations at least in Vietnamese and Haitian Creole. Today in Boston, we'll do thousands of conversations in Brazilian Portuguese and Spanish.”
Rao: Abridge extracts and places medical orders into patient records
“So we can distill, we can extract those orders. We can
Structure them, and we can place them in the medical record.”
Rao: Abridge processes millions of clinical conversations every few days
“Like we're live, we're doing millions of conversations like every couple days, like it, it's real scale.”
Rao: Stanford survey shows Abridge cuts clinician burnout by 50%
“We're seeing in the metrics that we use these validated instruments that we're reducing cognitive burden by, like, 60% within six weeks of a clinician using this, and clinician burnout per one survey that Stanford came up with, we reduced that by, like, 50% so…”
Rao: Healthcare AI adopts fastest in low-stakes, high-frequency workflows
“When you have high stakes and like high frequency workflows, like that's probably not gonna get absorbed into like the healthcare system proper. Very, very quickly. But when it's lower stakes, higher frequency, like our, you know, workflow because there is tha…”
Rao: Abridge has raised over $500 million
“We've raised over, like, five hundred million dollars now”