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The Hidden Roadblocks to Smarter Hospitals

Healthcare systems struggle to transform patient care when outdated infrastructure can't keep pace with modern clinical demands

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As hospitals look to improve outcomes with faster, more informed decisions, infrastructure limitations remain a major hurdle. This episode—part two of a five-part Health and Life Sciences at the Edge series exploring The Future of Patient Monitoring—dives into what's holding back smarter, more connected care. Intel's Andrew Lamkin, AI Solutions Architect, and Bikram Day, Director of Informatics at Medical Informatics Corp., join Michelle Dawn Mooney to unpack the technical and clinical roadblocks buried deep in hospital systems today.

According to Day, the problem starts at the edge: "Most devices in the environment are not even connected. You end up with all that data going down a black hole."

Most devices in the environment are not even connected. You end up with all that data going down a black hole.
— Bikram Day, Director of Informatics at Medical Informatics Corp.

Despite the availability of rich clinical data, fragmented device ecosystems and legacy workflows keep critical insights from reaching providers in time. Lamkin adds that while continuous monitoring has improved, infrastructure hasn't kept pace with what's possible: "Hospitals have networks and computing resources… we’re not talking about something that's too high throughput to even start the conversation."

The discussion emphasizes that many monitoring systems are still designed around outdated processes. "Almost all the infrastructure… has been there to replicate the manual charting," Day explains. This manual-first mindset leads to hidden work for clinicians—connecting cables, hunting down data, and relying on telemetry stations that don't scale. "We have way too many cables connecting things," he says, but progress is happening with newer wireless sensors and shared protocols for devices like infusion pumps.

What's needed to break through? Interoperability, automation, and rethinking the role of metadata. "Who, where, and when—all those factors are critical," Day stresses, especially when preparing data for AI.

Use the human bandwidth for what the human is really good at… let the machines do their thing, which is crunching a whole bunch of data.
— Bikram Day, Director of Informatics at Medical Informatics Corp.

Looking ahead, he calls for a mindset shift toward enabling machines to process data while clinicians focus on higher-value work.

Learn more about patient monitoring innovation by connecting with Andrew Lamkin and Bikram Day on LinkedIn, or by visiting Medical Informatics Corp. and Intel Health and Life Sciences.

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