Doctors Struggle to Use Wearable Data From 30% of US Adults as EHR Systems Lag
Updated
Updated · ZDNet · Jun 9
Doctors Struggle to Use Wearable Data From 30% of US Adults as EHR Systems Lag
3 articles · Updated · ZDNet · Jun 9
Summary
More than 30% of US adults now use fitness or wellness wearables, but many doctors say most of the resulting data still cannot be used reliably in patient care.
Episodic care systems and EHRs were not built for continuous streams of heart rate, sleep, blood pressure and other metrics, leaving clinicians to juggle separate platforms, formats and patient-matching problems.
Researchers and physicians also question the validity of proprietary scores such as recovery or strain, warning that ignoring patient-generated data can alienate patients while acting on weak data can cause harm.
Some clinical wearables already feed into records, and efforts including Samsung's 2025 Xealth deal, open-source JupyterHealth and AI summarization tools aim to filter the useful signals back into EHRs.
New guidance from the American Academy of Neurology and calls for stronger validation, transparency and public infrastructure show the field is shifting from gadget adoption toward clinical governance.
Can US hospitals afford data systems for continuous monitoring when payment models still reward episodic care?
With AI analyzing our health data, are privacy laws like HIPAA strong enough to protect us?
AI can now synthesize patient data, but who is legally liable when its medical insights are wrong?
The Future of Healthcare: AI, Interoperability, and the Clinical Value of Wearable Data at 25% U.S. Adoption
Overview
As of mid-2026, healthcare is rapidly changing due to the combination of artificial intelligence, better data sharing, and the widespread use of wearable technology. This shift is moving patient care from a reactive approach to a more proactive and personalized one. By using real-time processing of Patient-Generated Health Data from wearables, healthcare providers can gain actionable insights. Machine learning and AI analyze this data live, supporting clinical decisions and improving precision medicine. As a result, doctors can use up-to-date information from wearables to make better care decisions, leading to more effective and targeted treatments.