2 min read
Published on 28 Jul 2025
In my recent guest article for Healthcare IT Today, I explore how combining smartphones with artificial intelligence can transform healthcare delivery at scale: Bringing continuous, predictive, and personalized care without the costs and operational bottlenecks of traditional remote patient monitoring (RPM).
Key takeaways:
Scale meets speed with smartphones. Everyday devices can collect continuous clinical and behavioral signals at population scale to provide insights traditionally tied to costly RPM hardware.
AI delivers smarter risk detection. Machine learning models can sift through millions of data points to detect early patterns, such as early diabetes, neurodegenerative markers, or social determinants of health, and alert care teams proactively.
Personalized clinical recommendations can be made at scale. AI can combine health data with evidence-based recommendations to help care teams make tailored, cost-effective decisions across large populations.
Access and equity get a boost. Mobile-first strategies lower barriers to care, extend reach into underserved communities, and enable real-time patient data to inform research and public health planning.
By harnessing capabilities already built into everyone’s phone—and pairing them with advanced AI—we can move from reactive care to proactive health management. It’s about delivering precision population health that is efficient, equitable, and effective.
Read the full article on Healthcare IT Today.
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