Eric Hsiao

🧠 Everyone wants to build HealthTech products that scale. But scaling in healthcare isn’t just about velocity - it’s about rigor. You’re not just shipping features. You’re earning trust across users, buyers, regulators, and clinicians. That means: Product ≠ MVP. Product = workflow, risk profile, data flow, and compliance posture. Product-market fit isn’t enough. You need product-market-trust. GTM without alignment? That’s a misfire waiting to happen. Would love your thoughts or war stories. What have you seen break first?

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Several people know about this problem but nobody talks about how to solve it. I was asked one time to help fix this issue at a company. The fix lies in breaking the work down to a few critical steps. First, never just hand off work in its entirety and expect you'll get anything you can use. Regardless of how good or bad the team is, always ask, always, the offshore team to pseudo code their approach. They should explain which files they'll touch, which systems they'll touch, integrations, which areas or layers of the application, etc. I call this the first pass. Why is this important? This tells me they're thinking about the problem right and if there are any gaps in their understanding, or any pieces they're missing. After that, they'll do a second pass. That is stubbing out which functions or code will need to be added or modified, maybe even making the functions and service calls work but with mock data. This is the "prove it to me" moment. This second pass also helps me as a dev manager gauge how fast or slow the offshore team is working, giving me indications too if they're stuck somewhere. Only after this second pass, do I actually turn them loose to go execute and "deliver" the solution. Only now, because I did some diligence on my managerial end, I've got greater confidence that what I'll get will be something on par with what I'm expecting and can use. This partnership and collaborative arrangement also fosters trust and over time the offshore team will learn how your organization operates, critical thinking, and that nothing should ever be done in a vacuum or cowboy way. For more helpful tips like this, follow me. I'm paying it forward in 2026 and will be sharing gems most people aren't talk about with a focus on the solutions, not just problems.

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New post about product-led-growth in healthcare - Why OpenEvidence's approach is interesting - Heuristics for how to think of other opportunities in direct-to-employee tools - A look at other roles and tools they might need (CRCs, home aides, med lab techs, pharmacy) - Some of the open questions that will dictate this space going forward full post in the comments

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Healthcare SaaS That Reduces Burnout — An Engineering Perspective We talk a lot about physician burnout. Long hours. Administrative overload. Endless documentation. But here’s something we don’t talk about enough: Software design plays a direct role in burnout. As engineers, we don’t see the exam room. We see workflows, schemas, APIs, dashboards. But every extra click… Every slow screen… Every poorly designed form… Eventually lands on a clinician already under pressure. Healthcare SaaS that reduces burnout doesn’t start with features. It starts with empathy. From an engineering perspective, that means: • Designing around real clinical workflows — not admin convenience • Reducing cognitive load (less clutter, smarter defaults) • Minimizing context switching between systems • Making performance a priority, not an afterthought • Automating documentation where it truly helps Speed matters. Clarity matters. Timing of information matters. If your system forces a physician to fight the interface, you’ve already failed — no matter how compliant or feature-rich it is. Good healthcare software should feel invisible. It should support decisions, not interrupt them. Technology can either amplify stress… or quietly reduce it. That choice happens at the architecture and product design level. If you're building healthcare SaaS and want to align engineering decisions with real-world clinical impact, I help teams design systems that balance usability, compliance, and scale. Because in healthcare, good architecture isn’t just technical — it’s human. #HealthcareIT #HealthTech #DigitalHealth #SaaS #UXDesign #SoftwareArchitecture

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The App Store has about 50,000 health apps. And… maybe 100 of them are actually worth downloading. The rest are digital snake oil dressed up in a clean UI design. But something just shifted that might actually change what's possible. Apple quietly updated its Health app to support FHIR R4. That's the same data standard major EHRs use, which means Health app data can now flow directly into clinical systems. This simple tech update changes what remote monitoring and patient engagement can actually do. Remote monitoring becomes easier to deploy. Patient portals can access continuous data instead of episodic uploads. The boundary between consumer health data and clinical records is disappearing. The problem is, clinicians don't want to see ALL the data. After hundreds of hours of product research with clinicians, trust me when I say: Physicians want signals, not noise. Your Apple Watch tracking your heart rate 24/7 is only useful if someone filters that data down to what actually matters clinically. Otherwise, it's just overwhelming providers who are already drowning in information. The tech companies that succeed here will be the ones who design clinical experiences that filter, prioritize, and surface what matters in practice. There are dozens of effective patterns for these clinical workflow experiences that can be optimized with research and validation. Don't start from scratch. So yes, most health apps are still garbage. Meditation apps promising to cure anxiety. Fitness trackers claiming to diagnose conditions. Symptom checkers telling you everything is either nothing or cancer. But integration standards like FHIR R4 mean the useful apps can finally connect to actual healthcare systems instead of collecting data that goes nowhere. How do you tell the difference between health tech that works and garbage wrapped in a shiny interface? - Look for clinical validation. Did the app get tested in actual studies with real patients? - Check if it's FDA-cleared or approved for medical use. If an app claims to diagnose or treat conditions without it, that's a red flag. - See who built it. Was it developed by healthcare professionals or just software engineers who think they understand medicine? - Ask whether the app integrates with your actual healthcare. Can your doctor see the data? - Be skeptical of apps requiring expensive subscriptions for basic features. Apple's FHIR R4 support is a step toward health apps that actually integrate with clinical care instead of existing in isolation. But the apps still need to be built right, clinically validated, and designed for actual workflow. Your health deserves better than digital snake oil, even if it syncs with your EHR.

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Healthcare AI has a trust problem. Not a technology problem. Not a regulation problem. A trust problem. And it's self-inflicted. Years of overpromised products. Tools that required clinicians to change their workflow instead of improving it. Platforms that generated alerts nobody acted on. AI that made confident recommendations clinicians couldn't verify or explain to patients. The result: a clinical environment that is deeply, reasonably skeptical of anything that calls itself AI. You don't fix that with better marketing. You fix it by building something so focused, so reliable, and so clearly scoped that the risk of trusting it feels smaller than the cost of ignoring it. That's what we set out to do with Nexustria, Inc. One problem. One environment. One output clinicians can actually use. Not because the vision is small, but because trust is earned in narrow lanes before it's extended to wide ones. That's the only way back in. #HealthcareAI #ClinicalAI #HealthTech #DigitalHealth #Nexustria

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Most health systems are still trying to drive care gap closure the same way they have for years: by hiring more people to manually read charts. That approach doesn’t scale. Using the Notable Platform, Montefiore Health System took a very different path: programmatically reviewing charts across both structured and unstructured data to surface evidence for payer-submitted gaps. No custom templates. No rigid rules engines. Just AI that reads the chart the way a clinician does - across every location, every format. What this unlocked: - 50K+ charts reviewed - 4K incremental gap closures - Gap closure rates increased from ~3–4% to 7% - 95%+ accuracy - 4,000 hours of staff time saved - 6× ROI in early production This is the shift happening in Quality. And it isn't a pilot. It's real and repeatable. Huge credit to Desiree P., Cathleen Santiago, Nicole Halverstadt, MBA, the Montefiore team. Proud to partner on powering impact like this. https://lnkd.in/gqjbGuYb

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Everyone in healthtech says they’re building disruption. But if it doesn’t show up in patient care, team workflows, or clinical trust, it’s just noise, isn't it? Here’s what I’m watching closely right now: 1️⃣ Medicare telehealth is hanging by a thread The COVID-era waivers have been extended through September 2025. That’s 67 million seniors still connected to virtual care. But the industry is on edge. And, if Congress doesn’t act again, entire care models could be left scrambling. 2️⃣ AI is commanding healthtech investment, but with scrutiny VCs are still writing checks, but they’re asking for two things before they commit: 👉🏻Real clinical integration 👉🏻Clear, measurable ROI The days of demo-driven rounds are over. Teams like Omada Health and Abridge are setting a different bar, deep clinical alignment, and daily use. As someone building at the intersection of healthcare and tech, here’s where I land: ➡ Policy is not a headline, it’s a foundation. If reimbursements shift again, telehealth doesn’t bend, it breaks. ➡ AI is only useful if it reduces work. Nobody has time to ‘figure it out later.’ Adoption happens when tools show up seamlessly where people already work. And disruption? It’s not what you launch. It’s what survives. The teams I trust most aren’t optimizing for attention. They’re building systems that deliver, silently, when nobody’s watching. What’s one trend in healthtech that looks overhyped to you? Curious to hear others building in this space. Share your thoughts. 👇🏻 #PabloDiaz #Blossend #OpenMyDoctor #HealthTech #AIHealthcare #telehealth #Founder #HealthCareInfrastructure

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Real thing that happened on an EMR demo today: AI created a script that was read by AI to demo the ambient listening AI tool I don't know whether to be pumped, terrified, or run away to the mountains Probably should ask AI...

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Here’s your recap of last week’s health IT partnership and product release news. 🗞️ 👇 (Part 1 of 2 - this was a busy week for health IT announcements!) 🤝 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗻𝗲𝘄𝘀: • UMass Memorial Health is expanding Mednition KATE AI system-wide. • Stanford Health Care is using Atropos Health to surface personalized evidence at the point of care.    • MetroHealth System selected Pieces for inpatient and outpatient settings.    • TriHealth selected Reveal-Dx and announced a clinical study to evaluate real-world impact.    • Cleveland Clinic announced it would be using AKASA's coding AI assistant and CDI tool.    • Allegheny Health announced its first "touchless" prior auth with Humata Health.    • Sentara Health is expanding its use of Andor Health.    • Albany Med selected Honest Health as its ACO enabler. 🚀 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗡𝗲𝘄𝘀: • Videra Health launched AI-powered Group Notes • Cedar released an agentic AI solution to handle patient billing calls. • Relatient launched a conversational AI feature for automating patient scheduling calls. • Zocdoc released Zo, a voice AI agent that handles  inbound scheduling calls. • CliniComp integrated enterprise-wide PACS with its Intrinsic AI solution suite. • Viz.ai announced Viz 3D CTA, which converts computed tomography angiography scans into AI-enhanced 3D images for neurovascular visualization.    • Limbic launched Limbic Intake Agent, a voice AI agent that handles patient intake. • CoreCare launched Pre-Admit to help SNFs assess referrals. • NeuroFlow published new research showing the efficacy of its solution in recognizing suicidal ideation. • Get Well announced an AI patient assistant to support inpatient care navigation and discharge.    • Digital Medicine Society (DiMe), Duke University, University of North Carolina at Chapel Hill, Fitbit (now part of Google), + ŌURA announced a collaborative aimed at helping prevent relapse and reduce deaths from opioid use disorder using wearable technology. 𝗥𝗲𝗺𝗶𝗻𝗱𝗲𝗿: you can always catch the full details of each of these announcements in our weekly Elion Briefing (sign up at Elion [dot] health [slash] newsletter).

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