17 articles
A medical AI agent autonomously carries out a series of tasks — gathering information, drafting documents — in response to instructions. We explain how it differs from mere AI features, use cases in hospitals, and cautions.
"AI-equipped EHR" covers very different things: bolt-on AI versus AI-native design. We explain comparison criteria, the difference from AI-native, and how to choose wisely, for hospital decision-makers.
Using generative AI in hospitals requires managing risks such as data leakage and training use. We explain checkpoints for safe adoption and how to engage with internal rules and guidelines, for practitioners.
Generative AI can speed up drafting referral letters, medical information documents, and discharge summaries. We explain how to use chart-based document generation and the essential cautions — data leakage and review processes.
AI pre-consultation gathers symptoms from patients before or during the wait and hands the key points to physicians. We explain the mechanism, benefits, how to think about efficiency, and cautions for hospital practitioners.
Voice input and AI clerk features can ease the burden of documentation in the EHR. We explain what to check when selecting — medical-term accuracy, chart integration, generative-AI summarization — and how to think about the impact.
How acute-care physicians can streamline charting with voice input — the burden of keyboard entry, where voice fits, and combining it with generative AI to record without stopping care.
How generative AI can ease acute-care physicians' document workload — drafting referrals and discharge summaries, a review-first workflow, and points for safe use.
How to lighten the heavy paperwork of recovery rehab by delegating drafting and organizing to an AI agent — letting AI support plans, summaries, and reports while clinicians focus on review and judgment.
Published hospital cases and time-savings for auto-drafting discharge and nursing summaries with generative AI — how it works and what to watch for when adopting it in clinical settings.
How to standardize rehab plans that vary by author in form and granularity, using generative AI and form design — keeping quality consistent while streamlining, with review as the premise.
Why rehab progress reports and discharge summaries take time, and how generative-AI drafting eases the burden — auto-summarizing from accumulated assessments and course, with clinician review as the premise.
How to shorten therapists' record time by combining voice input with generative AI — capturing notes on the spot between sessions and letting AI summarize and format, while preserving accuracy.
Breaking down why rehab comprehensive plans take time, and how generative-AI drafting reduces the burden — auto-populating from assessment data while keeping clinician review as the safe premise.
Psychiatric nursing records take time due to free text. We explain drafting via voice and AI while a review step keeps quality, cutting record time without strain.
Automate CP-equivalent and polypharmacy checks in the EHR. We cover visualizing overdose risk, dose-reduction support, and cautions around psychotropic reimbursement reductions.
How does an AI-native EHR change psychiatric documentation? We cover where voice and generative AI help, governance for safe use, and how to make it stick.
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