Joe Dustin

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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Has the increased use of digital patient-facing technologies led to "digital toxicity" for patients navigating their care? The authors of a recent article in Journal of Clinical Oncology Clinical Cancer Informatics suggest it might. They highlight the risks associated with digital toxicity when patients utilize electronic patient-reported outcomes (ePRO) assessment and monitoring tools. This underscores the importance of prioritizing the patient experience to ensure that technology enhances care coordination without adding to the patient's burden. What are your thoughts on this perspective? Read more: https://lnkd.in/gYAgFr28

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HTA evaluates the value of medical technologies, but too often, patient perspectives are left out of the process. Including patient input ensures decisions reflect their needs, leading to better outcomes and greater health equity. Explore how Patient-Centered HTA is shaping a more inclusive healthcare system in this blog by Xanthia Lam, MPH candidate at Columbia University and Center Patient Engagement Intern: https://ow.ly/oTZe50UBybT #HealthEquity #PatientEngagement #HTA #HealthcareInnovation

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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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🌟 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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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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My colleague Rafa Arranz ❄️ shows how to talk to your clinical data safely, securely, and without hallucinations using Snowflake Cortex Analyst. I'll always have a spot in my heart for data visualizations, but directly asking for insights from vast data is where the world is today thanks to ChatGPT. #Snowflake #AIDataCloud #snowflakeCortex #healthcare #healthdata #healthtech

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An interesting article that highlights the importance of aligning strategies with value-based care #VBC goals to enhance patient outcomes and operational efficiency. One critical aspect is #datadrivencare management. Utilizing analytics platforms to aggregate and analyze data from sources like electronic health records #EHRs allows for population health analysis, risk stratification, and tracking quality metrics, all of which contribute to improving care quality. Additionally, placing proactive #preventivecare at the center of your strategy is essential. Implementing wellness visits, chronic disease management, and timely immunizations can boost overall health while reducing long-term costs. Another vital factor is enhancing #carecoordination. Developing care transition protocols, streamlining provider communication, and creating multidisciplinary care teams help ensure a seamless patient journey and better outcomes. Furthermore, increasing #patientengagement and education plays a crucial role. Addressing #socialdeterminants of health is also key. Screening for social challenges, building a community resource database, and ensuring proper referrals and follow-ups are necessary steps to support overall patient well-being. Finally, building #partnerships and aligning incentives with payers, community organizations, and technology vendors is essential. Collaborative efforts to align goals, share data, and explore innovative solutions lead to better patient care and organizational performance. By integrating these strategies into your healthcare business approach, you can effectively align with VBC goals and enhance #patientcare. #healthcarestrategy #resourceoptimization #performanceincentives #stafftraining #healthcareinnovation #hbr #leadership #strategy #lifelonglearner #digitaltransformation #innovations

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Interesting piece by #JAMA on the FDA's perspective on #AI in healthcare and biomedicine. It highlights how AI presents challenges but also great opportunities to impact health outcomes. The opportunities are immense as it relates to improving clinical research, drug discovery, drug development, clinical trial support, post-marketing surveillance, etc. What is essential however is the need to have optimized tools, regulation and established frameworks to ensure that AI models are safe and effective across diverse settings. This is an exciting time for ongoing AI innovation!

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In the competitive world of #digitalhealth, having innovative tech isn’t enough. To truly stand out, ventures must show #proven clinical evidence—and the key to achieving that? Strategic #partnerships. In our latest blog, we reveal: - How #clinicaltrials, #regulatory approvals, and peer-reviewed #studies can fast-track your #solution to market #success - Why #partnering with #biopharma is crucial for credibility and growth - How #ventures with validated #clinicalstrength are securing more #funding and accelerating #marketaccess Ready to see how evidence-based #innovation is shaping the future of digital health? 🚀 Read the full blog now and subscribe for exclusive access to our upcoming #report! Stay informed. Stay ahead. Together, let's shape the future of healthcare. 🌟 https://lnkd.in/dFMXGTjK

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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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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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Very interesting, insightful study. Flare Capital Partners AI in healthcare is hype. Most AI stories for healthcare are tech advancements. Not real clinical advancements or fitting into their workflows, bearing few. MedTech Innovators face these paradox. 1.Adoption requires Evidence. But evidence comes only from adoption. Clinical data can not be synthetic data for good AI. 2.Regulatory, validation requires money. But investors require regulatory, validation. 3.MedTech need faster adoption, but healthcare is slower among every profession, a cut-throat industry. They won't use it, if it is more than 2-3 mouse clicks. https://lnkd.in/gUh8sDHe

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Many innovative ideas can become obscured when communicated, which was a significant challenge for Patient Blood Management #PBM as it was introduced to benefit those suffering from #anemia, in hopes of enabling surgery without the use of donated blood upon leaving the ER (Emergency Room). The PBM educational approach supports bloodless surgical procedures. To reduce this obscurity, we are simplifying the message and increasing awareness, benefiting #researchers, manufacturers, and healthcare practitioners. Most importantly, we are enhancing the patient experience and raising public awareness. We are confident that many global organizations, healthcare providers, and blood management surgical equipment manufacturers will support our efforts as we continue to be pioneers in building a bridge of engagement for public access, which will benefit this field of medicine. Remember our medical icons, just in case one day you need direction to the OR. #Bloodlines #BBTS #Blood #SABM

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In this upcoming webinar, join Force Therapeutics to discover: - Real-world CMS compliance data to benchmark your own organization's performance - Best practices derived from hospital workflows exceeding collection rates - The impact of specialized vendors on compliance and performance REGISTER: https://lnkd.in/ejwRc8GG

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Are you experiencing challenges with coordinating external data sources in clinical data management? In this article, Debra Anderson, our SVP of Strategic Partnerships, explores the complexities of coordinating external data sources and shares some practical strategies for navigating these challenges. Contact Veramed today to learn how we can provide you with tailored data management solutions to your study needs. Read now: https://lnkd.in/ekmWJsXm Going to SCDM Live next week? Deb will be there, along with other members of the Veramed team - stop by Booth 305 to find out more about how we can help your clinical study!

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Learn about ethical and practical integration of AI, focusing on creating systems that improve patient care without compromising physician autonomy or patient privacy from speaker Jesse Ehrenfeld MD MPH at AIMed24. He advocates for responsible AI use that supports clinical decision-making, enhances patient safety, and alleviates administrative burdens on healthcare providers. #AIMed24

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Microsoft has introduced advanced AI capabilities for healthcare organizations through Microsoft Cloud for Healthcare. This includes AI models in Azure AI Studio, which facilitate the integration and analysis of diverse medical data types such as imaging, genomics, and clinical records. Additionally, Microsoft Fabric enhances healthcare data solutions, allowing organizations to harmonize various datasets and perform care management analytics. The healthcare agent service in Copilot Studio automates tasks like appointment scheduling, while an AI-driven nursing workflow solution streamlines documentation, ultimately improving patient care and operational efficiency.

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