Wearables produce huge amounts of health data - and doctors are struggling to keep up

2026-06-09 · Source: News and Advice on the World's Latest Innovations | ZDNET · Field: Health & Wellbeing — Healthcare Systems & Policy, Medical Devices & Health Technology, Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

Over 30% of US adults own a fitness or wellness wearable, generating a "fire hose" of health data that doctors struggle to integrate into clinical practice. Cardiologist Dr. David Kao notes that approximately 70% of this data is clinically unusable due to proprietary formats and lack of validation, though some insights are invaluable. The current episodic care system is ill-equipped to handle continuous streaming data, facing challenges with electronic health record (EHR) integration, managing diverse proprietary platforms, and ensuring data validity. Researchers highlight a "professional dilemma" where dismissing data risks alienating patients, while acting on unvalidated readings risks harm. Despite these hurdles, some doctors, like Dr. Kenneth Civello, see potential, citing instances where wearables saved lives. Efforts are underway to address these issues, including Samsung's 2025 acquisition of Xealth for Epic EHR integration, the University of Colorado's work on intelligence support for EHRs, and the open-source JupyterHealth platform. The American Academy of Neurology also released guidance in March for neurologists on wearable use.

Key takeaway

For Healthcare IT Administrators and Clinicians evaluating wearable data integration, recognize that current episodic care systems and EHRs are not designed for the continuous "fire hose" of consumer health metrics. You should prioritize exploring AI-driven solutions for data synthesis and advocating for standardized data validation and open-source infrastructure like JupyterHealth. This approach will help you move beyond proprietary data silos and mitigate the risk of clinical harm from unvalidated readings, enabling more effective personalized care.

Key insights

Healthcare's episodic model struggles to integrate the continuous, often unvalidated, data stream from consumer wearables.

Principles

• Episodic care systems are not structured for streaming health data.
• Unvalidated wearable data creates a professional dilemma for clinicians.
• Health data infrastructure should be a public good, not solely commercial.

In practice

• AI tools can synthesize large volumes of health data for personalized care.
• Open-source platforms like JupyterHealth aim to solve data ingestion challenges.
• Regulatory bodies can provide guidance for clinicians on wearable device use.

Topics

• Wearable Health Data
• Electronic Health Records
• AI in Healthcare
• Data Integration
• Episodic Care
• Data Validation
• JupyterHealth

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Editorial summary, takeaway, and curation by AIssential. Original article published by News and Advice on the World's Latest Innovations | ZDNET.