What the Future Looks Like if We Get It Right

 

As the Patient Monitoring series concludes, the conversation shifts from today’s challenges to tomorrow’s possibilities. This final episode of the five-part Health and Life Sciences at the Edge series looks ahead to what healthcare could become if patient monitoring gets it right. Intel’s Kaeli Tully is joined by Sudha Yellapantula, Senior Researcher at Medical Informatics Corp., with a special appearance from Bikram Day, Director of Informatics at Medical Informatics Corp., to explore bold predictions, personalized care, and the safeguards needed to responsibly build the future of healthcare.

Yellapantula grounds the conversation in real-world innovation, sharing projects that use physiological data to predict cardiac arrest, compare CPR techniques, and detect critical events through signal analysis alone. These experiences shape her vision for the future, where predictive analytics are deeply personalized. “All our predictive analytics should be personalized to us,” she explains. “Your history, your genetics, your past surgeries—really fine-tuning your model to you.”

Looking toward 2050, the episode imagines a healthcare system that is proactive rather than reactive. Yellapantula envisions universal monitoring on hospital entry, where wearables immediately screen for major events like strokes or heart attacks, and monitoring intensity adapts based on patient acuity. “You’re customizing your monitoring and producing the best prediction to be sent to the correct people,” she says, emphasizing the need to surface only the most relevant, actionable alerts without overwhelming clinicians.

The discussion also explores how clinician workflows could change. Instead of searching across fragmented systems, nurses and physicians would receive a comprehensive, centralized view of each patient’s physical, emotional, and psychological state. “Those logistical hassles should really be in the past,” Yellapantula notes. “We’ve gone to outer space. We can bring our healthcare system up to speed.”

Day expands the vision further, pointing to advances in wearable technology, biomarker detection, and multimodal AI. He predicts that future wearables will not only collect data but process it intelligently, flagging early warning signs and guiding patients toward timely intervention. “The cost to intervene is going to go down,” he says, making proactive care more accessible and equitable.

But with opportunity comes responsibility. One of the episode’s most critical lessons centers on data integrity. Yellapantula warns that poorly managed training data can undermine even the best AI models. “To build a good predictive model, you need good quality data and good quality labels,” she explains, urging the industry to address data contamination now before it becomes a limiting factor.

The episode closes with a clear takeaway: if patient monitoring succeeds, it enables earlier detection, smarter decisions, and more personalized care. “We’re able to have very actionable alerts where we really have the greatest impact on patient outcomes,” Yellapantula says. It’s a future built not just on better technology, but on better choices, collaboration, and trust.

Connect with the thought leaders driving this discussion:

Subscribe to this channel on Apple Podcasts and Spotify to hear more from the Intel Internet of Things Group.

Recent Episodes

The Rothman Index, developed by Dr. Michael Rothman and his brother Steven, is a pioneering patient acuity score designed to help clinicians recognize patient deterioration earlier and more clearly. Presented as an easily understood, color-coded graph that updates in real time, the Index displays upward and downward trends in patient condition at a glance—transforming…

Hospitals collect enormous amounts of clinical data, yet preventable patient decline remains a persistent challenge. Over the past two decades, hospitals have invested heavily in early warning scores and rapid response infrastructure, but translating data into timely, meaningful action has proven difficult. As clinicians contend with alert fatigue and increasing documentation burden, a more…

Healthcare generates enormous volumes of clinical data, yet making sense of that information in real time remains a challenge. Subtle changes in vitals, labs, and nursing assessments often precede serious events, but when that information is fragmented across the medical record, emerging risks can go unnoticed. The central challenge facing hospitals today is not…