Laura Furmanski

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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My colleagues, James R. Bush, Adarsh Gosu and I were honored to lead an Executive Roundtable at the #BeckersAnnualMeeting last month. Leaders discussed the capabilities of Generative AI in health care, emphasizing the trust, governance, data modernization, and workforce training. Some highlights included: ☑ Establishing effective governance is crucial for successful AI implementation. ☑ The importance of change management can’t be overlooked. ☑ Building consumer trust and engagement is essential in AI adoption. ☑ Workforce upskilling is necessary for AI fluency and successful implementation. ☑ Designing AI solutions with scalability in mind is a must. A special thanks to Becker's Healthcare for the opportunity! Read a recap of our conversations on Beckers Hospital Review. https://lnkd.in/gEVWxwzq Want to learn more about Deloitte guidance for the potential of #AI in healthcare? We have a report with critical insights about implementation and governance. https://lnkd.in/gXE_HVG2 Bill Fera, Tina Wheeler, Adarsh Gosu, Dan Kinsella, Anne Phelps #AIinHealthCare #GenAI #FutureofHealth #Deloitte #hospitals #HealthIT *Information posted here is a personal opinion and is not a substitute for medical advice. Shared publications contain general information only and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services.

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Predictions for the Healthcare Analytics Space in 2025 Increased Integration Across Data Ecosystems As value-based care models continue to expand, seamless data integration across clinical, claims, and social determinants of health (SDOH) sources will become critical. Organizations will prioritize interoperability through networks like QHINs, Carequality, and CommonWell to create a unified patient view. Interoperability Will Become Non-Negotiable Regulatory and operational pressures will force healthcare organizations to embrace true interoperability, with frameworks like TEFCA, QHINs, and platforms like Carequality/CommonWell gaining momentum. Seamless data exchange will shift from a competitive edge to a baseline requirement. Shift from Retrospective to Predictive Analytics Organizations will move away from merely reporting past events and toward anticipating future risks, costs, and care needs. Predictive models will guide both operational efficiencies and patient care interventions. Demand for Transparent ROI Healthcare organizations will increasingly demand clear ROI from analytics investments, driven by financial pressures and accountability in value-based contracts. Solutions must demonstrate tangible outcomes like cost savings, care improvements, and enhanced risk stratification. Rise of Decentralized and Multi-Tenant Data Repositories As data ownership and governance become central, healthcare providers will adopt multi-tenant architectures to securely store and access aggregated data while maintaining control over proprietary information. AI and Machine Learning in Care Pathways(*) The use of AI to identify care gaps, optimize workflows, and automate routine tasks will grow exponentially. Providers will seek analytics solutions incorporating explainable AI to maintain trust and compliance. (*) Steep adoption curve Focus on SDOH for Equitable Healthcare Delivery Payers and providers will deepen their focus on SDOH to address health inequities. Analytics platforms will need to integrate SDOH data into actionable strategies for population health management. Emergence of Modular and Workflow-Specific Tools Comprehensive dashboards will give way to modular, workflow-specific tools that empower users to interact directly with data. These tools will emphasize usability and decision-making at the point of need. Partnerships Over Proprietary Solutions Collaboration between analytics providers and adjacent industries (e.g., tech, pharma, and public health) will drive innovation and adoption. Open ecosystems will gain traction over closed, proprietary platforms.

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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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Fabulous to be on the investor panel for Mintz’s Life Sciences Pitch Event today, on yet another glorious fall day in Boston. ☀️🍁 Key feedback shared by our panel: 🔹 Ensure your target market is clear - especially when the population for your relevant indication is highly heterogenous 🔹 Share your current assumptions about how your product may be used (e.g., chronically vs. episodically) and open questions 🔹 If you're exploring a range of commercial use cases, share how you anticipate prioritizing across them over time 🔹 If your GTM strategy requires you to displace heavily entrenched solutions and/or processes, share how you will enable these transitions 🔹 Note the specific set of milestones to be achieved with investment 🔹 Always include target timelines and potential paths to exit Thank you to the incredible lineup of entrepreneurs who pitched today, and please stay in touch! Thank you to Dean Farmer and Charlie C. for facilitating today's event. Thank you to panelists David Fogel, CPA, Ben Littauer (he/him), Molly Hoult, and Richard Wagner for your contributions. Great to meet you, and thank you for all of your help, Emily (Krasowski) Yanachkov and Diana Malkin. #lifesciences #pitchevent #investor #panel #boston

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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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Super excited for this launch ✨ There's been some wonderful growth over the last few years in the remote care and virtual health spaces, but the increase in disparate solutions has also created a ton of fragmented workflows for clinicians, forcing them to switch between various point solutions to service a patient. We've seen it even with our own web app and provider-facing tools — clinicians are often spending more time trying just to find the right data on a patient than actually analyzing it and taking action. We're launching Connect to embed our insights on medication adherence directly into other web and care platforms to reduce the administrative time spent jumping between solutions to find different data points and increase the time clinicians are spending taking action and addressing patient needs. If you're a care platform of any sort and/or looking to provide your patients with a medication adherence support tool, we'd love to assist :) #virtualcare #medicationadherence #rtm

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Taking a brief intermission from our innovation series, I wanted to share about the newest episode of the Best Ideas Win Podcast. As healthcare leaders, we can't "stick our heads in the sand" when it comes to AI, and this conversation with Dennis was especially helpful in outlining important steps to take to be proactive in your AI strategy. #LeadWithImagination #BestIdeasWin #HealthcareAI #ArtificialIntelligence

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Navigating Real-World Evidence for Health Technology Assessment: Key Insights from Industry Experts 📊🔍 *The recent webinar featuring insights from April Betts (UCB), Stephen J. Duffield (NICE), and Rachel Cummings (Decisive Consulting) provided an in-depth look into the evolving role of real-world evidence (RWE) in health technology assessments (HTAs). Here are the key takeaways: ✔ Evolution and Importance of RWE: RWE is becoming a staple in healthcare, impacting regulatory decisions and market access. It addresses gaps inherent in randomized controlled trials (RCTs) by providing data on larger populations and real-world practices. 🌐🧬 ✔ Challenges and Opportunities: The integration of RWE faces challenges such as data quality, relevance, and regulatory acceptance. However, it presents opportunities to enhance evidence for HTAs, especially in demonstrating long-term effectiveness and safety. 🚧📈 ✔ Strategic Applications: RWE is critical in areas like cost-effectiveness analyses and can influence the decision-making processes of bodies like NICE. Effective RWE strategies involve early planning and continuous adaptation to evolving healthcare landscapes. 📝💡 ✔ Collaborative Efforts: Successful RWE utilization requires collaboration across various stakeholders, including academia, industry, and regulatory bodies. This collaboration helps ensure that RWE meets diverse regulatory requirements and adds value to HTA submissions. 🤝🌍 ✔ Future Directions: The use of RWE is expected to grow, with increasing sophistication in data analytics and broader regulatory acceptance. Stakeholders must remain agile and proactive in leveraging RWE to inform healthcare decisions and policies. 🔮📊 *These discussions highlight the critical role of RWE in shaping the future of healthcare decision-making, underscoring the need for strategic alignment and robust methodologies in its application. #HealthcareInnovation #RealWorldEvidence #HTA #Pharmaceuticals #HealthTech

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Reflecting on a thought-provoking panel discussion alongside Meghan Sarli, Christine Franklin, and Matthew Walsh. I’m inspired by the depth and breadth of insights shared on patient centricity, patient experience, and the transformative role of technology—particularly AI—in reshaping patient engagement. One of the most compelling takeaways from our conversation is that patients today are no longer passive recipients of care; they are active, empowered partners in their health journey. This paradigm shift underscores the need for advanced, omnichannel solutions that not only support but also elevate the individualized patient experience. Grateful to Digital Health Coalition and GSK for hosting this dynamic exchange of ideas—it was truly energizing to be part of such an impactful conversation. Below are a few key takeaways from the panel that I hope resonate with others as much as they did with me: 𝗣𝗵𝗮𝗿𝗺𝗮𝗰𝗶𝗲𝘀 𝗮𝘀 𝗖𝗮𝗿𝗲 𝗖𝗼𝗿𝗻𝗲𝗿𝘀𝘁𝗼𝗻𝗲𝘀: Pharmacies are transforming into pivotal hubs of patient-centric care. With patients visiting their pharmacists 12 times more frequently than their primary care providers, pharmacies are uniquely positioned to educate, build trust, and deliver personalized support. Today’s patients demand health information that is both trustworthy and seamlessly accessible, tailored to their busy lives. 𝗔𝗜 𝗮𝘀 𝗮 𝗖𝗮𝘁𝗮𝗹𝘆𝘀𝘁 𝗳𝗼𝗿 𝗖𝗵𝗮𝗻𝗴𝗲: Artificial intelligence is revolutionizing patient engagement by delivering expert-approved, personalized health content directly to patients. These tools not only enhance health literacy and adherence but also foster patient loyalty by providing convenient, on-demand support. In this context, “direct-to-patient” (DTP) isn’t just a concept—it’s a holistic approach, empowering patients to manage their health proactively, often from the comfort of their homes. 𝗧𝗵𝗲 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗣𝗮𝘁𝗶𝗲𝗻𝘁 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁: The pharma industry is shifting its focus from purely clinical efficacy to prioritizing patient satisfaction and engagement. Technology-driven solutions—like AI-powered reminders, telehealth services, and real-time pharmacist consultations—integrate care into daily routines, creating better patient outcomes. As we navigate this digital evolution, it’s crucial to keep data security, patient empowerment, and health equity at the forefront to ensure an inclusive, tech-enabled future for healthcare. Conversations like these remind us of the incredible strides being made in patient engagement and how much potential still lies ahead. The path forward is clear: innovation, collaboration, and a relentless focus on the patient. How are you seeing technology and patient-centric strategies unfold in your area of healthcare? Let’s keep the conversation going. Watch the full discussion here: https://okt.to/SLQbVq #AIDrivenHealthcare #PatientCentricity #DigitalHealthCoalition #PharmacyOfTheFuture #PatientEngagement

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The team at Define Ventures has published a paper on AI and how C-suite leaders at Payers and Providers are thinking about these exciting new technologies. Get the full report here:  https://lnkd.in/eVnp9N-k

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In healthcare, data alone doesn’t mean much. The real magic happens when we turn that raw data into "actionable insights"—and that’s where the real impact on patient care begins. At NirogGyan | Smart Health Reports & AI, I’ve personally seen how converting complex lab data into simple, meaningful insights can completely change how patients and doctors interact. It’s not just about presenting results—it’s about giving people the power to understand their health and take action. Whether it’s catching early warning signs or fine-tuning treatment, those insights are what drive proactive healthcare. Data is just the start. What we do with it is what truly makes a difference. #HealthData #PatientCare #ActionableInsights #NirogGyan #HealthTech

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The most gripping stories unfold over time and synthesize strong narratives and even stronger characters. The story of Alaffia Health's recent successful $10MM Series A raise is no different. Founders TJ Ademiluyi & Adun Akanni, MPH, PMP are driven by a clear vision to solve seemingly intractable problems. Aperture® Venture Capital General Partners Garnet S. Heraman & William Crowder are the same. Aperture® Venture Capital is committed to unlocking value in AI and has invested its resources and collective acumen in this goal. Read more here —> https://lnkd.in/d26iErDR

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How do we minimize the number of protocol amendments and increase the operational feasibility of our clinical trials? This article below points out the benefits of using data, conversations and real world data to enhance the feasibility of the protocol design and inclusion/exclusion criteria: 1) Are we being too strict on our criteria in order to "control" for data variability? 2) Do are criteria allow for the intended patient population in the real world (if not, they need to) 3) How realistic is your design in how the study sites actually work? How they see and treat patients? How is your company ensuring the design meets these requirements? https://lnkd.in/gzJzFd-3

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👏 Great article by Brian Spisak, PhD and Todd Norwood! They address the need to improve data quality to find value from AI in healthcare and lay out ✨ 10 KPIs ✨ that healthcare organizations can pursue to take advantage of the AI Revolution. Great work here!

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I agree every single word. Yes, technology might not be the most important part, but how to streamline use cases and payment system is so crucial

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🌐 Deep Dive from ISPOR: The Role of AI in Healthcare Decision-Making 🌐   At our ISPOR roundtable this week, we explored the growing importance of AI in market access and HEOR. AIs, especially large language models (LLMs), are exceptional at making predictions based on vast datasets. They simulate understanding by predicting the next word in a sequence, next sentence in a paragraph, but they don't make judgments.   This distinction between AI's prediction capabilities and human judgment is crucial. While AIs process and predict data at an unprecedented scale, the human mind performs analysis, prediction and judgment nearly simultaneously, bringing ethical and practical consequences into play. This fundamental difference underpins why human oversight remains indispensable as we harness the strengths of AI predictions.   In our session, we discussed the necessity of keeping a 'human-in-the-loop' to leverage AI's predictive power responsibly. We emphasized that while AIs can process information and suggest outcomes based on patterns, humans must remain accountable for interpreting and acting on these outcomes, considering broader implications and ethical dimensions.   Our conversation highlighted the rigorous training required for these models to perform effectively in specialized fields like cancer genomics. Just like training a new graduate, developing an AI model involves intensive guidance, examples, and feedback—often through methods like adversarial and reinforcement learning, where models learn from their mistakes in a controlled environment.   As we continue to integrate AI into healthcare, it's critical to maintain this balance—utilizing AI’s robust data processing and predictive capabilities while ensuring that final judgments are informed by human insight and accountability. This approach will maximize AI’s potential in improving patient outcomes and operational efficiencies in healthcare settings. #AIinHealthcare #ISPOR2024 #HumanInTheLoop #EthicalAI #HealthTech #cancergenomics

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