Joseph Condurso III

One key reason why healthcare technologies like AI, telemedicine, and software haven't structurally lowered costs or broadened access for the entire system after decades of experimentation (excluding pure financial engineering of payer contracts) is the limited reimagining of care delivery itself, with asynchronous telemedicine as a notable exception. In the same way that digitizing physical paper failed to exploit the capabilities of a new computing medium for word processing, hosting physician-patient conversations over video does not transform the actual delivery of care. In telemedicine, many of the inputs (e.g., clinician time) and therefore cost structures of in-person care persist, which is why we often see fee-for-service telemedicine companies struggle to achieve economies of scale (i.e., growing revenues non-linearly while growing costs linearly). Until we deconstruct the components of a medical appointment – from intake and triage, to chart review, history gathering, physical examination, diagnosis, treatment, and follow-up – we will continue to be underwhelmed by the disconnect between the transformative potential of these technologies and real-world patient/system impact. I’m optimistic that the emergence of reliable and performant medical AI agents will urge us to perform this deconstruction and redesign the fundamental building blocks of a “medical appointment.”

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🌟 Generative AI and Healthcare Transformation: A New Era of Innovation 🌟 I am constantly asked about #AI applications for healthcare transformation. I continue to take people back to the pain points or problems being solved. The healthcare industry is undergoing a significant transformation, driven by the integration of generative AI. This revolutionary technology is currently reshaping the way we approach care management, early disease detection, and administrative tasks. Early Benefits of Generative AI: Enhanced Care Management: AI serves as a "co-pilot" for healthcare professionals, assisting in managing patient care more efficiently and accurately. This leads to improved patient outcomes and more personalized care plans. Early Disease Detection: AI's ability to analyze vast amounts of unstructured data enables early identification of diseases, potentially saving lives and reducing healthcare costs. It's a game-changer in preventive healthcare. Reducing Clinician Burnout: By automating repetitive administrative tasks, AI allows clinicians to focus more on patient care. This not only improves job satisfaction but also enhances the quality of care provided. Affordability and Efficiency: AI-driven processes streamline operations, making healthcare more affordable and accessible. From optimizing workflows to reducing operational costs, AI is paving the way for a more sustainable healthcare system. Challenges and Considerations: Ethical and Legal Frameworks: Ensuring AI is used responsibly requires robust ethical, legal, and policy frameworks. Trustworthy AI adoption is crucial for patient safety and health equity. Technology Infrastructure: Organizations need to update their technology infrastructure, including cloud capabilities, to fully support AI implementation. As we embrace these advancements, it's essential to stay informed and engaged in the conversation about how AI can continue to transform healthcare for the better. #HealthcareTransformation #GenerativeAI #HealthTech #Innovation #AIinHealthcare Thanks to sources McKinsey & Company (https://lnkd.in/g7HZHEST) and MedCity News (https://lnkd.in/gi95t4qJ)

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A whirlwind of activity last week at the America's Physician Groups conference. Lots of solid insights shared by health system leaders. Some notable thoughts: +++ Artificial intelligence is intelligent in different ways: By now, we all know ai has a diverse set of use cases, incorporated in different applications and tools. But there are fundamental differences in how the intelligence itself is brought to life. Examples include: - Predictive AI, used to forecast future outcomes by leveraging historical data. Shout out to UCLA’s CKD/ESRD early intervention protocol (Joycee Berin) and Diagnostic Robotics’ intelligence care post-dicharge journeys (Kira Radinsky) - Protocolized AI, used to automating a user’s administrative load by using a set of detailed, pre-defined rule sets. Thanks to ARC for sharing their experience using Elaborate 's automated outpatient lab summaries (Manish Naik) - Generative AI, used to create new content. Great overview of ambient documentation at MGB as well as Cedars’ Sinai talking through its medical ontology model powering acute triage (Caroline Goldzweig) Across system leaders and experts, there was clear agreement that the first step to implementing intelligence intelligently is defining the ‘jobs to be done’. That way, internal and external stakeholders are clear on what they're solving for when they architect the solution.  +++ Scaling AI takes time and rigorous observation: Market leaders describe a phased pilot approach that allows clinicians to build confidence and system leaders to measure ROI before deploying systemwide. Loved hearing Rebecca Mishuris outline MGB’s novel approach of piloting two solutions against one another, to pressure test implementation, workflow, and value creation. +++ Proving ROI continues to be challenging: Lots of vendors using lots of different metrics to prove value, but the majority of leaders agreed that estimating the ROI of these new tools today is part science, part art. Demonstrating the ROI of the “soft” metrics around provider burnout and retention seemed to be a big opportunity, especially for investment in more efficient primary care and PCP wellbeing. After all, PCPs drive referrals to specialty-level care (and higher reimbursements) for health systems. Appreciated Anurang Revri's overview of how working team setup can also impact ROI estimates. +++ Value-based care = tools + humanity: VBC will require not only implementing tools to support clinical documentation, risk capture, upcoding, etc, but also humanizing interactions to engage patients. Countless examples, but one that made me smile was a depression focused chat bot responding in the following interaction: - Context: post-discharge check in Bot: Hi Freida, how are you feeling today after your surgery?  Patient: I’m having a tough time, am in a lot of pain.  Bot: Well, it can’t be that bad, I’m sure it will get better with a positive mindset!    🤣 🤣 🤣 Can't wait for next go-around!

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Here’s your recap of last week’s health IT news 🗞️ 👇 🤖 AI Clinician Assistant • Avaamo launched an AI ambient scribe solution with support for over 50 specialties with pre-trained models. • Wound AI, an AI clinical decision support solution built by VANTIQ, Telemedicine Solutions, LLC, and NTT DATA, launched and is now available 📞 AI Contact Center • Premier Inc. awarded a group purchasing agreement to TeleVox Healthcare. 🏥 AI Facility Management • Medely has integrated with Oracle, allowing users to leverage Oracle’s Cloud HCM capabilities. 🌡️ AI Remote Patient Monitoring and Triage • The Alliance for Smart Healthcare Excellence—established by care.ai, now a part of Stryker, and developed with assistance from CHIME—was established to promote the Smart Hospital Maturity Model (SHMM). 📈 Data & Analytics • Epic expanded its set of APIs available to developers to support USCDI v3. • Health Catalyst will acquire Intraprise Health, a cybersecurity provider; it was also selected for analytics and interoperability by CyncHealth, Iowa’s health information exchange (HIE). • Health Commons Project acquired OneHealthPort • Socially Determined released a new application that helps organizations access data for minors. 🧾 Orders & Fulfillment • Surescripts is expanding its Medication History for Populations product to health plans, enabling care management teams to identify gaps in care and improve outcomes. 🧑‍💻 Virtual & At-Home Care • Mass General Brigham launched a partnership with the New England Center and Home for Veterans to provide hospital at home services for veterans experiencing homelessness. • MedStar Health expanded its partnership with DispatchHealth to support care transitions.    🍎 VBC • i2i Population Health is partnering with CureMD to surface actionable data to providers at the point of care. 🧠 Food For Thought • Brendan Keeler shared an interesting post differentiating AI solutions across augmentative vs. autonomous and then further breaking down each. One take we found interesting was, “Active interfaces are fun, but ultimately have some of the same problems as Siri - they require explicit engagement and cognitive overhead to use. This means their adoption and impact often fall short of expectations - users must actively remember to use them and overcome the friction of engagement.” https://lnkd.in/eR39qFpK --- Want the latest healthcare tech news delivered to your inbox each week? Sign up here 📬 👉 https://lnkd.in/e2UJ3ckP

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Oracle Health announced plans to launch a next-generation EHR platform in 2025, incorporating advanced cloud and AI capabilities. This new EHR will feature Oracle's clinical AI agent, voice-activated navigation, and Health Data Intelligence, which integrates patient data from over 300 sources to enhance clinical workflows and improve patient outcomes. The platform aims to replace traditional EHRs, which often dictate rigid workflows, with a more dynamic system that allows for personalized care plans. Oracle Health emphasizes that the new EHR is a complete reinvention rather than an upgrade of the previous Cerner system. Additionally, Oracle plans to become a Qualified Health Information Network to facilitate standardized data sharing across the healthcare ecosystem. Executives at Oracle also unveiled new cloud applications to improve patient management and streamline front-office operations, reinforcing the company's commitment to enhancing healthcare accessibility and data utility while addressing interoperability challenges in the industry.

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This 👂 podcast episode and insight’s from a16z Bio + Health's Julie Yoo spoke so clearly to the fundamental challenge facing both 🩺 clinicians and 🏥 healthcare systems.  There is a huge disconnect between supply, in the availability of clinicians, and demand, in the increasing volume and complexity of healthcare needs. -     36% of physicians plan to reduce their hours next year according to the AMA -     48% of physicians reported feeling burned out in a 2024 Medscape survey At the same time, the demographic baby boomer bubble and steady increase in the prevalence of major chronic disease, which consumes up to 90% of healthcare expenditures according to some estimates, is driving demand. With this context, Yoo points to a major opportunity for AI adoption in healthcare in 2025. Yeah, a VC hyping a wave of new AI companies that will replace the decades of training and experience of clinicians, the skeptic would say.  But Yoo is thoughtful in pointing to the role AI can play, and is already playing, through solutions such as ambient, autonomous scribe solutions (of which local star Abridge is leading the pack) in not replacing, but freeing up productivity for clinicians. There is so much unstructured context in both the complexity of disease and treatment options and the social/emotional considerations that we shouldn't be looking for AI to *replace* clinicians. But companies are getting better at finding the structured, repetitive and time-consuming places where AI tools can *help* clinicians. Nearly two-thirds of doctors cited bureaucratic tasks as the leading contributor to burnout. Rigorously trained-AI driven solutions can be a force multiplier for clinicians, and I’ve seen several interviews where nurses and doctors go as far as to say some of these solutions are ”restoring their joy in practicing medicine”. Our health is precious; and we rightly want any technology engaging with it to be developed thoughtfully and thoroughly tested. This requires top AI talent and diverse and realistic training data. Pittsburgh’s strengths in both areas is why we are an emerging hub for data-driven healthcare. #AIinhealthcare #clinicianburnout #healthinnovation #digitalhealth

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John Kell's recent article in Fortune, "The best investment opportunities in AI for health care right now," provides incredible insights about the challenges of healthcare data and how it impacts the advancement of #ai. Three out of every four leading health care companies are experimenting with generative AI or attempting to scale it across their business. What are they creating and why? Venture capitalist Deena Shakir asks founders if they "are aiming to solve a technology problem or a clinical adoption problem". Solving existing problems will speed decision making and improve data quality. The Deloitte report:  “Navigating the Emergence of Generative AI in Health Care” shares some of the data challenge in health care. While boasting the largest source of raw data, 80% of the data are unstructured.  Simon Gisby, managing director and the global leader of life sciences and health care at Deloitte further expounds "But as an industry, we’re not surprisingly that good at analyzing and drawing correlations out of that" https://lnkd.in/gXE_HVG2 Read thus great article for use cases and examples from fertility and maternal health care to predicting adverse outcomes to drug development and immunotherapies. The future of health and #ai is the hope that we can provide value in health care data equal to the volume we produce Read the article here: https://lnkd.in/gTx6ic_b

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Healthcare is at a turning point, and the stakes couldn’t be higher. The demand to deliver better care at lower costs is relentless, and the leaders who can unlock the transformative power of AI and data will shape the future of our industry. The question isn’t if data can drive change but who will lead that change. At Aetion, we help healthcare leaders rise to the challenge. Our AI/ML suite is designed to turn complexity into clarity, enabling bold decisions that improve outcomes, allocate resources smarter, and spark innovation. - Smart Risk Profiling: Pinpoint the drivers of cost and resource utilization to focus interventions where they matter most. - Measures Assistant: Simplify the creation of complex analytics, empowering teams to spend more time driving impactful insights. - Aetion Generate: Enable secure, privacy-compliant collaboration, opening new pathways for research and innovation.This is analytics with purpose—designed to tackle healthcare’s most pressing challenges and deliver meaningful, measurable results. The opportunity to transform healthcare with AI is here. At Aetion, we equip leaders to harness the power of their data with confidence, clarity, and impact—charting a future where every decision is informed by evidence. Please read the blog to learn how we empower leaders to shape healthcare’s future. Contact us to explore how Aetion can help you turn healthcare’s potential into measurable progress. https://lnkd.in/dpt3J4du

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There is a misconception emerging that AI agents will lead to immediate reductions in healthcare labor costs. While AI agents can automate end-to-end workflows such as booking appointments, answering basic patient questions, and performing form completion for prior authorizations, automating a single task is not equivalent to automating an entire job. Nurses are a prime example. Certain nursing tasks, such as care coordination and patient documentation, are highly automatable by AI agents; however, there is a tremendous amount of work nurses perform on the ground that cannot be fully automated with current technologies such as direct patient care, physical examinations, medication administration, wound care, patient support, and clinical assessments. These nuances make full role elimination less likely with current technologies. When articulating the ROI of an AI agent, we need to be both precise and accurate. Automating a task is more often not automating an entire profession. For roles that encompass many functions, such as nursing, AI agents can be invaluable tools for unburdening staff, increasing efficiency, and boosting throughput—benefits that are particularly valuable given current healthcare staffing and resource shortages. The most promising job candidates for full role elimination through AI remain positions with monolithic task structures, of which there are relatively few in healthcare today—scribes, medical coders, and data entry specialists for example. It is therefore unsurprising then that the most progress has been made in these categories.

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Health tech companies reported strong Q3 2024 earnings, driven by expanded offerings, rapid adoption of AI tools, and increased client demand. Here’s a recap of key updates: - Hims & Hers: A telehealth platform offering personalized treatments across mental health, sexual health, dermatology, primary care, and weight management. Q3 revenue jumped 77% to $401.6M, net income was $75.6M, and subscribers grew 44% to 2M. The company plans to launch a generic liraglutide in 2025 and raised its 2024 revenue forecast to $1.46B-$1.465B. - Doximity: A networking and workflow platform for medical professionals providing tools like telehealth, scheduling, and AI assistants. Revenue increased 20% to $136.8M, with AI tools leading growth and 1M prompts used in Q2. The company raised its 2024 guidance to $535M-$540M in revenue. - Waystar: A healthcare payment and revenue cycle management company serving 30,000+ clients across care settings. Revenue grew 22% to $240M, driven by rapid client adoption after a competitor’s cyberattack. The company raised 2024 revenue guidance to $926M-$934M and expects 2025 revenue near $1B.

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Recently, I had the opportunity to listen to a podcast featuring the CEO's of Prime Therapeutics and Cap Rx. Investing time to learn what I can has always been crucial to my growth, and this podcast hit the mark for me. I was able to uncover some nuggets of wisdom that I can use to educate myself further. It's always exciting to learn from industry leaders and gain insights that can help me excel in my field. https://lnkd.in/eZTMUmiu

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As AI becomes more embedded in healthcare decisions, ensuring traceability from algorithmic decisions back to clear guidelines and submitted clinical evidence is critical. Recent findings on companies like EviCore reveal a disturbing gap where AI and algorithms drive treatment denials, often with little transparency. When decisions about patient care are delegated to AI, every outcome should be fully accountable—linking directly back to both the clinical guidelines and the evidence provided by the physician. For AI-driven decisions, transparency is not a nice-to-have; it’s essential. This traceability not only fosters trust among healthcare providers and patients but also ensures that cost savings don’t come at the expense of patient care or quality. As we advance AI in healthcare, let’s prioritize clear, traceable pathways that support both efficiency and patient-centered care. https://lnkd.in/gV-AP8j9 #HealthcareInnovation #AIEthics #PatientAdvocacy #HealthcareTransparency #PenguinAi #Healthcare #PriorAuth #Denials ProPublica Missy Krasner Peter Longo Kishore Ayyadevara

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ZignaAI has been my favorite partner to work with since the founding of Helix Advisory! Their work has already paid significant dividends for payors leveraging their technology, but we couldn't be more excited to combine our #RCM expertise with their technological innovation to bring those outcomes to providers! #healthcareAI #CDI

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Imagine swallowing the competition whole. That's what many players in tech do via roll-up strategies, gobbling up smaller firms to deliver richer solutions and amass greater market share. Where else are roll-up strategies common? // HEALTHCARE Picture being a patient at a medical practice that’s been part of a roll-up in Healthcare Services. It's an industry ripe for roll-ups due to its fragmented nature and potential for greater efficiency. // CONSUMER SERVICES Or let's say you needed your HVAC serviced, and notice your local repairman is now part of a bigger Consumer Services entity? Centralized management and scale economy turn these localized businesses into roll-up targets. // FINANCIAL SERVICES Think about your insurance agent or wealth management advisor. They're working in complex, highly regulated environments. In the Financial Services sector, roll-ups offer an effective way to consolidate expertise, streamline operations, and enhance customer offerings. // MANUFACTURING Now, imagine driving past factories under a new name — the result of Manufacturing and Industrial Services roll-ups. Bulk purchasing reduces costs, enhances production capabilities, and expands geographical footprints. // REAL ESTATE Lastly, envision your real estate brokerage firm. The industry sees roll-ups as a strategic move to increase market penetration, enhance service offerings, and hike up portfolio value. Roll-ups play a huge role in most industries, rather like a snowball rolling downhill, gaining momentum, and size. Are you seeing roll-ups in your sector or considering M&A?

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Should you sell your practice to a VC-Backed MSO Startup? tldr: - new VC-backed startups are forming MSOs to roll up independent practices - The pitch is physicians receive early liquidity from the roll up and are granted ESOP shares that can be used for retirement - Problem is the use of ESOPs with independent practices is not a new concept and has been used with large group practices since the 70's - ESOPs do not grant full ownership and in order for the shares to be valuable for retirement, the practice needs to run the same if not better post roll up - With VC-backed startups being primarily operated by non-physicians with zero clinical or medical practice experience, the likelihood of this happening is extremely low making the entire concept high risk However, there is a viable path for continued ownership + liquidity for independent practices. Check out the article to learn more. ⤵ https://lnkd.in/gmGvTYwP

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With $8.2B invested into digital health so far, 2024 is shaping up to be a $10-12B annualized investment year. This would make funding comparable to 2023. I suspect with continued venture investment, boards will require exits. One thing I’m particularly interested in is terms of recent acquisitions and growth equity rounds. What type of downside protection (e.g., structure) is not disclosed to media that protects the investor? Will funds who have specifically raised capital to buy stakes in VC-backed companies at significant discounts? And what revenue/EBITDA multiples are looking like for M&A in 2024/2025? Every founder has to spin their story in a positive light when speaking to media. I know this because PR agencies reach out to me about their clients (p.s. I don’t consider myself a member of the media). The private health tech market feels like it could significantly rip or drop in the next 12-24 months. Therefore, my general advice to early-stage founders is to assume you will not raise capital beyond your seed round. If the investor market heats up in 2025, you will have the option to raise a series A at that time if you’ve built a strong business. If you’ve already raised series c or beyond, then one of your goals will be to time the exit (M&A or IPO) appropriately so that you garner an attractive multiple. There are few private health tech startups that have founder board control, can reinvest positive cash flows, and stay private forever. So by necessity of the structure, exits are desired. - - - - Image Credit: Rock Health

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