How data analytics improves patient outcomes and care

How can faster diagnostic results reshape healthcare's proactive potential? Imagine a world where interventions happen sooner, and outbreaks are contained swiftly. CRISPR technology is streamlining diagnostics, delivering results in under an hour—a stark contrast to the days-long wait of traditional methods. This speed is critical for rapid decision-making and managing emergencies, offering clarity with 'negative means negative, positive means action.' The reliable and quick identification of asymptomatic carriers also builds essential trust in test results. What impact could such speed and accuracy have on public health strategies and individual patient care? Curious to hear your insights on the future of diagnostics. #Diagnostics #CRISPR #HealthcareInnovation #PublicHealth #MedicalTechnology #Innovation

Comet is a new form of healthcare intelligence designed to help clinicians, health systems, and patients make more informed decisions. By predicting what is likely to happen next in a patient’s journey, Comet estimates risk of disease, length of stay, treatment outcomes, and more. Comet has learned from more than 100 billion patient medical events to calculate likely futures. The story: https://lnkd.in/gf9YZcUS The paper: https://lnkd.in/e8kXKpSG

This is a significant leap forward in clinical decision-making. For too long, our healthcare system has been reactive, but technologies like Comet are fundamentally shifting the paradigm to proactive and predictive care. Being able to accurately forecast a patient's journey doesn't just optimize resources for health systems; it directly leads to better patient outcomes. Giving clinicians the power to see what's likely to happen next is the difference between prevention and intervention. Excited to watch how predictive intelligence becomes the new standard of care.

Fantastic work from Epic with the creation of Comet, new form of healthcare intelligence conceived to help clinicians, patients and health systems to predict the patient outcomes and risk and then make informed decisions. I have a few questions: - If its potential is confirmed in US health systems where it was designed using its data for training , is it valid for other countries and other ethnicities? - How accurate are these predictions? - Can this approach create unnecessary fears and anxiety among healthcare professionals and patients? - Who/What will be accountable when a medical error was made due to this system?

Epic’s new CoMET (Cosmos Medical Event Transformer) models mark an important step for generative AI in healthcare. Trained on 115B medical events from 118M patients across 310 health systems, these Transformers demonstrate predictable scaling laws and deliver strong results across 78 diverse clinical tasks — without fine-tuning. Key takeaway: generative event models can simulate realistic patient trajectories and outperform specialized models (e.g. 30-day readmission prediction, AUC 0.77 vs. 0.72). Still, translation into practice will depend on prospective validation, subgroup analysis, and handling data quality variation. The potential is clear — so are the challenges.

What if we could see the next step in a patient’s journey before it happened? As we prepare for our Epic transition, I have been reflecting on how we use data. Tools like Comet show what is possible when information becomes insight and foresight. It is exciting to imagine how far healthcare intelligence can take us in improving care and outcomes. #Epic #HealthcareInnovation #QualityImprovement #InfectionPrevention #EMRIntegration #PatientSafety

Epic’s new CoMET models are an exciting step forward for generative AI in healthcare. Training on 115B+ medical events across 118M patients and outperforming specialized models in 30-day readmission prediction (AUC 0.77 vs. 0.72) highlights the potential of large-scale event transformers. I’m especially interested in how these models balance scalability with interpretability and how prospective validation and subgroup analysis will shape their clinical impact. #DataScience #OrlandoHeath #HealthcareAI #PredictiveAnalytics #Readmissions #GenerativeAI

Comet built within Epic Cosmos takes full advantage of blending real-time and historical data to guide patient care.

How is CRISPR changing the landscape of disease detection, and what does this mean for the future of healthcare accessibility? CRISPR diagnostics offer a revolutionary approach, characterized by speed, precision, and accessibility. This technology promises to bring powerful testing capabilities to various settings, from clinical environments to even personal use at home. It marks a pivotal advancement toward earlier detection and improved health outcomes for everyone. This era of medicine highlights how innovation can reshape healthcare delivery and patient empowerment. What other advancements do you foresee impacting diagnostics and healthcare in the coming years? Would love to hear your thoughts! #CRISPR #Diagnostics #Healthcare #MedicalTechnology #Innovation #PublicHealth

Healthcare has blind spots, and patients face the cost. Clinical trials often miss the daily realities of living with disease: pain, fatigue, financial stress, or transportation barriers. Real-world data and social determinants of health fill in those gaps, revealing the full patient journey and helping pharma design treatments that work in the real world (not just in the trial). 🔗Read more in MedCity News https://lnkd.in/d6uteVhX