The power of computing is getting roughly twice as fast and half the price every two years. And that’s why a pocket computer and even our iphones now have more power than a Cray supercomputer did by far 20 or 30 years ago. In Fact our smart phones are now FDA approved devices. And we have many examples of exponentials. The convergence of fast moving technologies—from Moore’s Law to A.I. to nanotech to Low-Cost Genomics to Big Data—is giving us an opportunity to reimagine health care around the planet. And hopefully to bring care anytime, anywhere at much lower costs and have a big impact, including on health equity, on clinical trials and moving us from what we’ve done, traditionally—sick care—which is episodic and reactive to a sort of an era of continuous, proactive health care.
When it comes to remote patient monitoring , I think one of the things that’s really accelerated the idea of remote care, virtual care, the idea of hospital to home is the idea that in the old form of thinking care happens in the four walls of the hospital or the E.R., or the intensive care unit. And a lot of what we keep people inside of the hospital for, or will delay sending them home, is to collect some data. It might be to measure their temperature or their vital signs. And now we’re at the sort of convergence point where a lot of that technology has been, in this exponential realm, digitized, democratized, demonitized, the fact that you can wear a little patch that can stream an intensive care unit level of data through your smartphone anywhere in the world. Or from your simple wearables you can track your sleep and how you’re doing after you’ve been sent home from a COVID infection or maybe after a total hip replacement. Are you walking more, walking less?. So all these new forms are starting to align. And so that really has accelerated the ability to do virtual care. A lot of care still does need the hands on, the face to face, the interaction. But it can be blended more with virtual care, on everything from mental health to diagnostics to complex chronic disease management. For example @ Lumeris we are leveraging AI, ML and genomics to predict outcomes and converting data into actionable insights to ultimately keep patients away from the hospital
Traditional healthcare providers, innovators, and even biopharma researchers are using machine learning and analytics from the Internet of Things (IoT), where devices monitoring patients in their daily lives will be used as a standard approach to deliver cost savings, improve patient visibility outside of the physician’s office, and to create new insights for patient care. Yet as new IoT apps and solutions are developed, two consistent barriers are preventing broad scalability of these solutions: interoperability of IoT device data with the rest of the healthcare data, such as clinical or pharmaceutical records, and the secure and private exchange of protected health information (PHI) from these devices in the cloud.
At Lumeris we are using Real-time patient data to transform the relationship between clinician and patient, shifting from traditional reactive, symptom-based care toward proactive, personalized care. Whether in the hospital or in the home, continuous patient monitoring is critical for enabling timely medical interventions, reducing readmission rates, and improving health outcomes.
