artificial intelligence

Defending Against AI-Powered Healthcare Fraud

By Zac Amos – Artificial intelligence powers healthcare operations, clinical decision support and administrative efficiency, but cybercriminals use the same tools to carry out more convincing, scalable and adaptive fraud. AI-enabled schemes exploit complex systems, data and human trust, making strong governance, technical controls and organizational awareness essential.

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HHS Wants Your Ideas to Accelerate AI in Clinical Care

By Steven Posnack – In collaboration with the U.S. Department of Health and Human Services Deputy Secretary’s office, the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology has released a request for information focused on one big question:


6 Considerations to Evaluate AI in Clinical Decision Support

By Gavin McNatt PharmD – According to 2024 data from the American Medical Association, more physicians are using AI and recognize its benefits for documentation support and visit summaries, among other tasks. The research found nearly 66% of physicians surveyed now use AI, up from 38% in the 2023 report.


There Seems to be No Limits on AI in Clinical Settings for 2026 – Part 1

Our annual predictions for 2026 continue with AI in Clinical Settings, look for Part 2, tomorrow. Throughout the next few weeks we will be asking the industry experts what they think we will see in 2026. Check back as we cover AI in healthcare, healthcare business, interoperability, Life Sciences, patient experience, and Value-Based Care.


Detecting Model Drift in Healthcare AI

By Zac Amos – As healthcare providers increasingly rely on artificial intelligence and machine learning to support clinical decisions, operational workflows and population‑health management, maintaining the reliability and safety of such AI systems becomes critical.



Decoding Patient Needs With AI Call Analytics

By April Miller – Healthcare providers hear patients on the phone every day, but much of the insights from these conversations disappear when the call ends. It is challenging to capture every sentiment when relying solely on notes from front desk staff, while clinicians see only a fraction of what patients share when they are anxious or confused.