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𝗔𝗜 𝗶𝘀 𝗿𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲, 𝗯𝘂𝘁 𝗽𝗿𝗼𝗴𝗿𝗲𝘀𝘀 𝗶𝘀𝗻’𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗮𝘀 𝗶𝗺𝗽𝗮𝗰𝘁. This 𝘍𝘦𝘥𝘦𝘳𝘢𝘭 𝘕𝘦𝘸𝘴𝘸𝘪𝘳𝘦 article raises a key point: if AI doesn't ease the work of care or improve the patient experience, it's not the right tool. At Hutchins Data Strategy Consultants, we call this 𝗛𝘂𝗺𝗮𝗻𝗶𝘇𝗶𝗻𝗴 𝗔𝗜 𝗳𝗼𝗿 𝗖𝗮𝗿𝗲. For health system leaders, that means aligning use cases to mission, not trend cycles. For rural providers, it means using data to extend reach without adding burden. For data leaders, it’s about trust and transparency. For policymakers, it's making sure innovation doesn’t leave people behind. The best AI supports people, not replaces them. It should reduce administrative load, improve access, and give clinicians time back. None of this works without clear guardrails and strong governance from the start. The goal isn’t faster. It’s better. 𝗪𝗵𝗲𝗿𝗲 𝗮𝗿𝗲 𝘆𝗼𝘂 𝘀𝗲𝗲𝗶𝗻𝗴 𝗔𝗜 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝗰𝗮𝗿𝗲 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗹𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗵𝘂𝗺𝗮𝗻 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝗼𝗻? #HumanizingAI #AIForCare #HealthSystemStrategy #RuralHealth #DataLeadership #HealthcareInnovation #ResponsibleAI Excited to collaborate with DataSpot Consulting Group Ingenious Dataworks (IGD) Reliath AI Susie Branagan BSN RN and Richard A D Jones on building responsible, high-impact analytics strategies that scale. https://lnkd.in/eFxAAbiT https://lnkd.in/eZjAxpc8

🚀 Exciting news from #SCDM2025! Saama Introduces Modular and Adaptive AI Agents For Clinical Innovation At Society for Clinical Data Management (SCDM), Saama is introducing industry-first Clinical AI Agents to help sponsors streamline trials from protocol to submission. Built on our next-generation Agentic AI Framework, these agents are: ✅ Purpose-built for clinical development ✅ Modular and customizable for sponsor needs ✅ Capable of reasoning, planning, and acting autonomously ✅ Always keeping human expertise at the center At SCDM? Visit Booth 407 to see how we are ushering in a new era of AI-driven clinical development. 📖 Read the full announcement: https://lnkd.in/emY9-n3W 🎓 Join our upcoming webinar on October 30 to learn more about Agentic AI: https://lnkd.in/egwyYRBZ #AIinClinicalTrials #AgenticAI #Saama Bhaskar Sambasivan, Ari Srinivasan, Malaikannan Sankarasubbu, Seshan Ramachandran, Angshuman Deb

The promise of AI in healthcare depends on one thing: the quality of the data behind it. In this recent MedCity News feature, Charlie Harp, CEO of Clinical Architecture, spoke about why data assessment and trust are foundational to the responsible adoption of AI. He discussed how the PIQI Framework helps organizations objectively evaluate clinical data, identify inconsistencies, improve accuracy, and create a shared understanding of what “good data” looks like. Without that clarity, AI tools risk making decisions based on incomplete or unreliable information. With it, the industry can move toward safer, more equitable, and more effective care. Read the full article in MedCity News: https://hubs.ly/Q03MB1qC0 #DataQuality #AI #HealthcareInnovation #Interoperability #PIQI #HealthData

Are your clinical R&D risk models still relying on static data? That single-point-in-time assessment is a critical blind spot. The strategic shift is toward dynamic, longitudinal models that are updated daily, capturing the progression of illness or response—not just the baseline. 1: Implement Explainable AI (XAI) to interpret dynamic patient status changes and overcome "black box" analytics. 2: Shift from static baseline scores to dynamic, longitudinal models for continuous, time-sensitive risk assessment. 3: Engineer "difference features" that quantify day-over-day changes to detect subtle patient deterioration or recovery patterns. 4: Mandate rigorous external validation on diverse datasets to ensure model generalizability and reliability before deployment. How are you moving beyond static baseline data to capture longitudinal trends in your clinical development programs? You can also listen on YouTube: https://lnkd.in/de_Ffhha Source: https://lnkd.in/d2DKVR6p Subscribe to my newsletter to get such insights: https://lnkd.in/dMR24Fss

At Axtria, we're not just talking about how Generative AI can transform the complex clinical trial processes, we're making it happen! Introducing our latest GenAI-powered Clinical Solutions capability: Axtria LUCCID or LLM-based Unstructured Clinical Concept Identification. With initial results showing over 90% accuracy in the automated abstraction of relevant concepts and a significant reduction in data extraction time, Axtria LUCCID is paving the way for smarter, more efficient management of unstructured clinical data. Join the next big leap in clinical innovation: https://hubs.la/Q03kcJzZ0 #GenerativeAI #ClinicalInnovation #ClinicalTrials #DataScience

The future of AI in healthcare hinges on the quality of your data. A new framework called PIQI is emerging to address the critical problem of varied and unreliable clinical data, providing an objective, standardized way to assess data integrity, helping organizations ensure their AI tools are built on a trusted foundation. Read more about why data quality is the key to widespread AI adoption: https://lnkd.in/gYnCQyvQ

The future of AI in healthcare hinges on the quality of your data. A new framework called PIQI is emerging to address the critical problem of varied and unreliable clinical data, providing an objective, standardized way to assess data integrity, helping organizations ensure their AI tools are built on a trusted foundation. Read more about why data quality is the key to widespread AI adoption: https://lnkd.in/g3t83-xC

Seven years of healthcare-specific data. That's what separates our AI agents from every generic tool on the market. PharmaTech News just published a deep dive into why specialization beats general-purpose AI every single time. While other industries debate theoretical potential, we've been deploying voice agents across 1,500 healthcare facilities. The difference is nuanced understanding. Our agents know why ICU experience differs from med-surg background, recognize OR credential requirements, and navigate regulatory compliance. Generic language models struggle with these healthcare-specific distinctions. Processing interactions from over one million healthcare professionals creates a network effect that individual competitors simply cannot match. Domain expertise wins. Always. Link in comments

💡 Modeling Monday | From Univariate to Multivariate Modeling in Hospital Operations 🎯 How LLMs & GenAI Are Reshaping Hospital Forecasting — My Take Over the years, I’ve analyzed hospital operations — from 🏥 ED wait times and 🛏️ length of stay to 🔪 surgery volumes and 📈 readmissions. Like many data leaders, I started with SAS / R-based univariate and multivariate models to forecast volume trends and resource needs. They worked well — until hospital complexity outgrew them. Recently, I’ve been experimenting with LLMs and Generative AI, including Meta’s Llama 3 and Mistral, fine-tuned on clinical + operational text. The early results have been exciting — uncovering context-aware insights from discharge notes, improving triage and throughput forecasting, and surfacing patterns that once took weeks to identify. As healthcare shifts from classical statistics → intelligent automation, the real differentiator will be teams that blend domain knowledge, AI literacy, and governance discipline to turn data into intelligent action. 🤝 Always happy to connect with professionals and organizations exploring AI-driven transformation in healthcare analytics and operations. #ModelingMonday #AIinHealthcare #GenAI #DataStrategy #Leadership #HealthcareAnalytics

The future of AI in healthcare hinges on the quality of your data. A new framework called PIQI is emerging to address the critical problem of varied and unreliable clinical data, providing an objective, standardized way to assess data integrity, helping organizations ensure their AI tools are built on a trusted foundation. Read more about why data quality is the key to widespread AI adoption: https://lnkd.in/ewCW5BtC