Post by ARISE

What if the most powerful healthcare tool of the next decade isn't a scan or a lab, but a living computational copy of your patient? That's the promise of the medical digital twin, so why aren't we there yet? The authors of this insightful article, Neera Ahuja, Jason Hom, Jonathan H. Chen, and Olivier Gevaert, define a digital twin as a continuously updated, patient-specific computational model that integrates EHR data to simulate disease trajectories and test interventions for a single individual.  So, what are a few of the barriers they name to achieving this today? Data quality: A model is only as good as its data. Missing or inaccurate EHR data could make predictions inaccurate and potentially unsafe. Generative AI paradox: Ambient AI scribes may improve documentation efficiency, but the authors flag a real risk which is that LLM-generated notes could worsen chart bloat, entrench billing-driven documentation, and embed confabulations. Digital twins trained on such data could amplify errors rather than reduce them. Challenges of continuous data integration: Wearables could supply the constant data stream digital twins need, but this raises unresolved medical-legal questions about provider responsibility for monitoring 24/7 streams. Regulation and ethics: Digital twins could enable 'n-of-1' simulations and in-silico research to test therapies virtually which would be a faster, lower-risk complement to trials. But today's approval systems are built for population trials, not individual virtual ones and so new frameworks are needed. Equity ("techquity"): Socioeconomic disparities in EHR access could exclude already-underserved populations and widen existing gaps, so equitable access must be deliberately designed in. The authors also paint a picture of the payoff. If these issues are addressed, they expect pharmacogenetic-based prescribing to become standard of care, in-silico research to accelerate drug development, and earlier prediction and intervention to reduce disease burden: cost, polypharmacy, emotional toll, and mortality, at a population level. Read the article below to learn more. https://lnkd.in/gRg7FqSA #DigitalHealth #HealthcareAI #ClinicalAI #DigitalTwin #HealthTech