Arun Ranganathan

Crazy to think how fast interfaces will evolve: Screens → Voice → Brainwaves https://lnkd.in/gd_V9YqG

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“Over one million new articles are added to PubMed annually—about two per minute. No physician can keep up.” This highlights a challenge that PCPs face daily, managing countless chronic and acute conditions while adapting to ever-evolving clinical guidelines. We can’t expect our clinicians to act like machines. At RhythmX AI (https://rhythmx.ai), we address this by revolutionizing primary care with our generative AI-native precision care platform, developed collaboratively by our physicians, specialists, and AI teams. Our platform integrates advanced AI and longitudinal data to deliver patient-specific, evidence-based recommendations directly within clinical workflows. These hyper-personalized insights help physicians make informed decisions at the point of care, bridging the gap between research and practice. Trust is at our core. Our physicians rigorously validate every recommendation to ensure clinical-grade reliability, empowering clinicians to confidently rely on the insights we provide. #PioneerPrimaryCare #Hyper-PersonalizedCare #PCPBurnOut #HealthAI #ResponsibleAI

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What do you think about AI in senior care? Personally, I think we have to be careful with it. When AI presents itself as human, it can be confusing for seniors who may not have strong digital literacy skills. In fact, if they think they're talking to a person and not an AI chatbot, it can be dangerous if they're having a medical emergency or issue. However, there are some helpful use cases. I think Kristen Fischer's exploration of AI here is really interesting. "Artificial intelligence may be a useful communication tool to help older adults with cancer communicate with their doctors and have more of a say in their treatment," she says. AI can provide more context or explanation about certain treatment plans and translate the patient’s needs to clinicians in situations where the patient doesn't feel understood or heard. AI will never replace professionals, but it could help patients and clinicians better understand each other. Feel free to share your thoughts on this—I'd love to know if you think AI would be an effective tool for these situations. #AI #SeniorCare #FutureOfHealthcare

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Sobering commentary on the state of platform engineering. Key takeaways on where PE needs to go from here: * You can’t manage what you can’t measure * Platform as a Product Mindset shift needed * Platform Engineering is socio-technical - the blending of adoption and transformation with engineering.

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As the CEO of an AI-driven health-tech company, Labops, I’m constantly evaluating how technology can create the most impact. While Large Language Models (LLMs) are making headlines, I believe Small to Medium-sized Language Models (SMLs) deserve more attention—especially for businesses operating in niche domains like healthcare. Why do I say this? 1️⃣ Tailored Solutions: In healthcare, where precision and specificity are critical, SMLs (40–50B parameters) are more adaptable to domain-specific needs. 2️⃣ Cost-Effectiveness: For startups, running and fine-tuning a SML is more economical than relying on large, resource-intensive LLMs. 3️⃣ Ownership & Flexibility: Open-source SMLs allow businesses to build and deploy models on their terms, giving greater control over data and performance. At Labops, where we’re building solutions to transform diagnostic services, the ability to leverage AI that aligns with our unique requirements is crucial. SMLs strike the right balance between scalability and practicality, making them a natural fit for startups like ours. LLMs have their place, but they’re not always the answer for every use case—especially in sectors where focus and efficiency matter more than sheer size. If you’re in healthcare or another specialized industry, I encourage you to explore the potential of SMLs. They might just be the competitive edge you’re looking for. What’s your perspective on SML vs. LLM? Let’s discuss! 💬 #AI #HealthTech #LLM #SML #Startups #Innovation #Labops

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Reimagining Healthcare Workforce Platfforms: Turning Capital Into Labor The future isn’t just about filling shifts. It’s about scaling labor intelligently, driving better outcomes for systems, staff, and patients alike. Andreessen Horowitz and Alastair (Alex) Rampell reinforced this Vision in a recent post and it applies to the next phase of healthcare workforce evolution. Healthcare workforce marketplaces plus AI are at the tipping point of transformation, evolving into systems of record that don’t just manage labor—they optimize it. Much like EHRs centralized patient care data, these marketplaces can centralize workforce operations, aligning talent supply with clinical demand. But there’s a bigger opportunity here: turning capital into labor. Here’s what I mean. Historically, industries (including healthcare) have focused on enterprise computing tasks—streamlining data entry, compliance, and back-office functions. While valuable, this approach often stops short of transforming the real-world, repetitive processes that make up the bulk of work in healthcare. Think beyond enterprise software. The next frontier lies in leveraging embodied AI and workforce marketplaces to automate and enhance labor-driven processes, transforming capital investments into productive labor outputs. For healthcare, this means turning staffing costs into scalable, dynamic systems that deliver value far beyond filling shifts: 1. Dynamic Labor Matching: Capital invested in marketplace platforms enables real-time matching of labor supply with patient demand, replacing outdated scheduling models with predictive, automated systems. 2. Workflow Automation: From credentialing to compliance and shift bidding, embodied AI can streamline traditionally manual tasks, freeing human resources for higher-value work. 3. Labor as a Strategic Asset: Workforce marketplaces shift the focus from static staffing budgets to proactive labor deployment, ensuring that every dollar invested in labor drives outcomes and efficiency. It is about the billions of repetitive, planned tasks that AI can improve. In healthcare, that means automating everything from staffing logistics to clinical task assignments, creating a horizontal system of engagement for labor (think Zendesk) that integrates seamlessly with vertical, workflow-specific platforms (think Toast for staffing operations). The result? Hundreds of billions in untapped market potential—and a healthcare workforce model that transforms how care is delivered. By turning capital into labor through smarter marketplaces and automation, we don’t just solve staffing challenges; we redefine what’s possible in healthcare operations and ShiftMed is leading the way with health systems moving beyond tired models. #capitalintolabor #systemsofrecord #healthworkforce #aiworkforce #healthsystems #hospitals #cno #hospitalceo #healthcareinnovation

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New study suggests that gpt-o1 achieves "superhuman performance" on clinical benchmarks that include differential diagnosis, diagnostic reasoning, and crafting care management plans: * On Management Decisions, o1 outperformed both GPT-4 and clinicians by ~40% in generating accurate and actionable management plans. * On differential diagnosis, o1 included the correct diagnosis in 78.3% of cases, and its first suggestion was correct in 52% of cases. * On 70 diagnostic cases, o1 produced a response with an exact or very close correct response in 88.6% of cases. This was done with relatively simple zero-shot prompts. During the early 20th century, x-ray machines gradually went from "technical novelty" to "it's unethical to diagnose without them" for a range of medical conditions. It would be no surprise if the industry went through a similar transition to require use of medical generative AI over the next 2-3 decades. https://lnkd.in/gd3RhFbr #ai #generativeai #healthcare #healthcareai #healthai #datascience

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I am torn by this as well. When I see a new platform shift, I see the opportunity for a shift that benefits the end user. The ultimate end user in healthcare is the patient. In the current model, the structure is to chase revenue by driving it up or maximizing profit. The AI platform shift, targeting low-hanging fruit like administrative efficiencies, follows this path. It's reminiscent of the famous quote: "We wanted flying cars, but we got 140 characters." The same thing is happening all over again, without truly challenging the status quo. Maybe AI can help people get less sick, prevent disease, and navigate spending less money in the first place. But in the current model, it's difficult to get penetration. Ultimately, everyone needs short-term metrics and traction to raise another round of funds. I am not criticizing those who play this game. I respect them for playing it well. However, they shouldn't position themselves as lowering costs for patients by decreasing administrative costs. The trickle-down effect simply doesn’t work.

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I’ve spoken to 50+ CMIOs/CIOs over the past year. Here are 5 thoughts about AI Scribes I'm hearing that many people are NOT talking about👇 1️⃣ Distribution matters more than Product. Most are just buying Nuance because it’s easier to buy. It’s a known entity. It’s an add-on to the Microsoft contract which means less internal hoops. Key question for who wins long-term: will the startups get distribution faster than the incumbent gets innovation? Will the EHRs eventually just release their own native AI scribes? (my belief is yes… which Oracle/Cerner has already done). 2️⃣ There is a clear “phenotype” for the clinicians who actually use AI Scribes: it’s clinicians who don’t care to have control over how their notes look and sound. But for those who really care about controlling the output? Those folks will keep writing their own notes. 3️⃣ The impact of AI scribes on medical education and trainees is very unclear. Some believe trainees should get exposure to AI scribes early on. Others worry that trainees who don’t learn to write notes are going to miss a critical skill that helps clinicians think. And what happens if there’s a cybersecurity incident and the EHR goes down? Will future clinicians not know how to document manually? 4️⃣ ROI is still hard to truly measure. Few see any improvement in “productivity” (i.e. more patients seen). The real value is in improving clinician well-being. However it’s hard to prove AI scribes are lowering staff churn since that is a lagging indicator many steps away and affected by many other factors. 5️⃣ The per clinician pricing model used by most vendors breaks down at scale. If I have clinicians who would only use the AI scribe for 30% of their patient encounters, am I going to buy a license for them? Probably not. What other less talked about learnings or insights are you hearing behind the scenes?

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🤯 Imagination in Action gets beyond the AI hype . Own your own digital persona and decide how your data is used. We’re looking at new business models here and new design paradigms. Awesome demo Anna Kazlauskas ! ProductRX.org Healthero.io #GenAI #ImaginationInAction #MITFORGE2024

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Created an AI assistant app to connect patients and doctors using Vercel AI SDK, Assistant-UI.com components, function calling, thread suggestions, check it out (Guillermo Rauch, Simon Farshid, Kajari Ghosh)

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We're trying a new thing: Company spotlights to help people better understand what various health IT vendors actually do 🔦 We’ll be cutting through the marketing speak to give short, to-the-point descriptions of a company’s product and/or service + some context on how they see their differentiators. Tag any companies in the comments you'd like to see us cover (and follow Elion if you want to stay in the loop!)

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The most common argument I hear regarding doctors building their own AI agents and software applications is that they won’t be able to maintain nor scale them. My counter question is if they purchase traditional SaaS applications instead of building in-house with AI, what exactly do they think is being maintained and scaled? Is it? - DevOps - Cloud Services - API connections - updating libraries - Bugs - security Why would a doctor in independent practice need to scale their application if they’re offering their services to a few hundred (maybe few thousand) patients? And if they did, why can’t AI not automate this for them? I mean, isn’t that what we’re already witnessing with AI consoles and AI coding environments? #HealthcareOnLinkedin #PrivatePractice #AIAgentsForDoctors

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When it comes to design debt in HealthTech, it's tempting to push it aside. You’ve already got complexity, compliance and deadlines to contend with. But you’ve probably seen these symptoms: • Inconsistent UI elements and design. • Confusing, poorly structured navigation. • Cluttered, overcrowded interfaces. • Redundant features causing confusion. • Vague, unhelpful error messages. • Inconsistent user flows and experiences. • Outdated visuals misaligned with branding. • Hidden, hard-to-find features. • Inconsistent accessibility and mobile support. • Unclear AI explanations causing mistrust. Ignoring design debt isn't just risky, it's a ticking time bomb. Like a small leak in your roof—it’ll only get worse (and more expensive to fix). The best way to manage it? Treat every decision as if a life depends on it—because sometimes with medical software and healthcare apps, it does. #DesignDebt #HealthTech #UXDesign #UserExperience #DesignChallenges #HealthcareDesign #UIUX #DesignThinking #DesignStrategy

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Exciting to see deep analytic brains tap into human empathy, to best apply #AI. In this case, it's healthcare charting solutions with THE PATIENT in mind, not "talking to the computer" or ecosystem first. I applaud Joshua Tamayo-Sarver, MD, PhD, FACEP, FAMIA for not only designing AI solutions as a product innovator, but as an ER doc, using them for why healthcare exists in the first place -- to provide the best patient care possible. His leadership example here is also making time -- despite a packed schedule -- to translate findings into accessible insights, shared in such a personable way. As we build and deliver AI solutions, let's remember the ultimate goal is to make life better for as many humans as possible. Focus on that, and the user growth, revenue streams etc. will follow under good leadership. #HealthcareInnovation #AIinMedicine #PatientCare #MedTech #DigitalHealth #DoctorsOfLinkedIn #InflectHealth #Sayvant #Vituity #Ambient

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🎬 Matt Damon and 🏈 Colin Kaepernick have invested in it, and so has 💰Andreessen Horowitz... Function Health's executive team has "engineered a first-of-its-kind approach that focuses on prevention and empowerment"—very much in line with what we aimed to achieve with Carebook when we started it over six years ago. Could they be the ones to fulfill their lead investors' prophecy (link at the bottom) and Dr. Eric Topol, MD's premonitions in his books "The Patient Will See You Now" and "Deep Medicine"? They have just secured a $50 million grant. Let's hope this is not another Theranos and that we are truly witnessing the rise of the next generation of direct-to-consumer health companies. These companies will be key players in the "transition from reactive to proactive" health care that the system—and we—desperately need. What do you think? Links: 📝 Investment round press release: https://lnkd.in/eUG87qkf 🔗 Andreessen Horowitz's prophecy: https://lnkd.in/eZATCf4f

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Daniel never fails to inspire both emerging and seasoned industry professionals. In this alphalist episode, IMG.LY's MD & CPTO shares invaluable insights on building a stable, cross-platform SDK—focusing on developer marketing, optimizing performance, and creating seamless API designs. Key takeaways include: 👨‍💻 What makes an SDK truly developer-friendly 📜 The role of documentation for effective inbound marketing 🔌 Designing intuitive, purpose-driven APIs 🧩 Navigating cross-platform support (React, Flutter, etc.) ⚙️ Prioritizing Algorithm Optimization > Compute Optimization Listen below!

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🚀 Why fit in when you can stand out? Our newly launched release is pretty special. Now Physical Therapists can experience the power of ezPT AI in THREE different modes: ⏱️ Save time with 100% hands-free documentation: Seek consent and convert your patient conversations into charts with our ambient Scribe. ⚡ Improve efficiency and never lose any detail: Do a quick brain dump with our Dictation mode in between patient sessions. ✍️ Always be in the driver’s seat: Prefer typing? Jot down your shorthand notes and let our Ghostwriter draft a comprehensive SOAP note for you. Choose any mode. You'll always get a contextual, compliant, and comprehensive note in your writing style. Our name is our game! 💪 What else can we do to make your lives easy, PTs? Get immediate access at https://lnkd.in/gBUbGt6Z and share your experience in the comments. No sign-ups or credit cards needed. #ezPT #GameChanger #physicaltherapylife #physicaltherapists #doctorofphysicaltherapy #physiotherapist #EfficiencySolutions #BurnoutPrevention #DigitalHealth #WorkSmarterNotHarder #ProductivityTools #patientnotes

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Did you know that the ACA covers 21M Americans? This makes the individual insurance market an incredibly large and stable risk pool. Oscar Health unveiled its 3 year strategy a few weeks ago and shared how we plan to build on our strong position in the ACA market. We believe ICHRAs (Individual Coverage Health Reimbursement Arrangements) can transform the health insurance landscape – we will bring our Oscar Magic to small and medium-sized businesses. By moving these employees to the individual market, we create a win-win: employees get more choice and differentiated plans, while employers have more control over their benefits expense (often a business’s second largest after salaries!). And we all win when we drive down rising health care costs. I’m so excited to see what we can do by bringing our Oscar Magic to more of the health care ecosystem!! See some highlights from Investor Day here:

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