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As providers move beyond piloting artificial intelligence-powered clinical documentation tools to scaling deployments, they’re sharing best practices that can guide later adopters: using data to understand expected and unexpected outcomes, tailoring solutions for specific roles and specialties, and applying change management expertise to make new workflows sustainable.  Two heal...

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While healthcare providers have identified best practices for deploying ambient listening tools for clinicians, the industry has been slower to develop consensus around governance from a patient perspective. As a result, deployments are often inconsistent, and patients may have questions about privacy, security and data access. In March, a panel at the 2026 HIMSS Global Health C...

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When an artificial intelligence system makes a “bad decision,” most organizations can’t really explain why. They aren’t entirely sure which data trained it, where the error was, which version it was running or which third-party components were involved. This is an ethical and regulatory blind spot that creates risk for healthcare tech leaders in organizations of all sizes, and i...

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It’s not just you. A March 2026 poll found that nearly a third of adults have typed their symptoms into generative artificial intelligence platforms to inquire about their physical health. But this activity can be risky. Not only are people sharing personal information with what are technically public databases, but AI chatbots have been shown to produce inaccurate answers. Rese...

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Across industries, solutions powered by artificial intelligence continue to dominate organizational priorities. In healthcare especially, there’s a focus on supporting a strained workforce and doing more despite thin margins. It can be overwhelming to parse through all of the new capabilities, potential regulations and necessary integrations, especially when change can happen so...

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