As the market for AI medical scribes matures, a clear divide has emerged between specialty-agnostic tools and specialty-first assistants. See why Allied Health is choosing IntuScribe.

Background: Mental health providers (MHPs) face a significant administrative burden from documentation, which can contribute to burnout and reduce time available for direct patient care. Although artificial intelligence (#AI) (AI)–powered scribes have shown promise in general medical settings, their utility has not been well explored in the specific context of mental health care. This study describes the development and preliminary observational evaluation of Smart Notes, a generative AI tool designed to assist MHPs with documentation on a commercial virtual mental health platform. Objective: This study aimed to examine MHPs’ use and uptake of a generative AI documentation tool, including use patterns, perceptions of note quality, feedback and satisfaction, and changes in productivity. Methods: Smart Notes was developed using a HIPAA (Health Insurance Portability and Accountability Act)-compliant Azure OpenAI infrastructure to securely generate session summaries from individual therapy sessions. The tool was rolled out to MHPs in a phased approach, and its use required MHP and client consent as well as a mandatory review and edit by the MHP. We conducted a 1-year retrospective observational evaluation of the feature, examining MHP use, MHP-rated note quality, MHP feedback and satisfaction, and MHP productivity (weekly working hours, session completion rate, and client caseload). Results: Over 1 year, 162 full-time and 1366 contractual MHPs used Smart Notes to generate over 286,000 clinical notes. Use of the feature was high and stable, with nearly all (averaging 94% each week, SD 1%) full-time MHPs and most (averaging 72% each week, SD 6%) contractual MHPs using it weekly for eligible individual therapy sessions after the full launch. MHP-rated note quality was overwhelmingly positive, with 97.7% (9980/10,219) of feedback ratings among full-time MHPs and 98.4% (19,977/20,300) of feedback ratings among contractual MHPs being a “thumbs-up.” Qualitative feedback from MHPs was also largely positive, praising the tool for saving time and easing administrative burden. Finally, both full-time and contractual MHPs demonstrated changes in productivity. Conclusions: Our findings suggest that AI-powered documentation tools, such as Smart Notes, are a feasible and acceptable approach to supporting MHPs. The high adoption rate and favorable MHP feedback indicate the potential utility of these tools without compromising note quality. This study provides preliminary data regarding the application of AI documentation in the mental health care context, highlighting a promising path for future research and development in digital mental health.

AI를 단순 자동화가 아닌 협업 도구로 활용한 문서화 실험. 코드 기반 API 문서 작성의 새로운 길을 제시한다.

In this episode, host John Maeda welcomes Megha Anand, a content developer on the Microsoft Learn documentation team, to explore how AI is being integrated into developer documentation. From code migration to game development, Megha shares how Copilot Highlights are making technical docs more practical, actionable, and AI-powered. Learn how AI is being embedded directly into Microsoft Learn docs to help developers solve real-world coding challenges faster and smarter. Chapters: 00:01 - Why Developer Docs Matter 00:10 - Meet Megha Anand from Learn Docs 00:22 - The AI Moment in Documentation 00:33 - Introducing Copilot Highlights 01:02 - Migrating JSON Code with AI Help 01:40 - Enhancing Python Games with Copilot 02:05 - Deploying Azure Functions with VS Code 02:40 - Context Engineering for Better Prompts 03:45 - Serializing .NET Objects with AI 04:30 - Empowering Developers with Copilot 05:10 - Final Thoughts and Community Call-to-Action What You’ll Learn: - How Microsoft Learn is integrating AI into developer documentation - What Copilot Highlights are and how they work - Real-world examples of AI-assisted coding tasks - How GitHub Copilot supports context-aware development in VS Code - Tips for content developers embracing AI - Ways to contribute to Microsoft Learn docs as a community member Speakers: Megha Anand – Content Developer, Microsoft Learn Works on Visual Studio documentation and leads Copilot Highlights integration. https://www.linkedin.com/in/megha-anand-426a8033/ John Maeda – Host https://www.linkedin.com/in/johnmaeda/ https://x.com/johnmaeda Links & Resources: Learn Docs with Copilot prompt: https://aka.ms/CAIK-AIDevDocSample 🚀 Explore Microsoft Learn: https://learn.microsoft.com 📝 Visual Studio Documentation: https://learn.microsoft.com/visualstudio ⚡ GitHub Copilot: https://github.com/features/copilot 🎯 Learn Python for Beginners: https://learn.microsoft.com/training/paths/python-language/ 📚 Azure Functions with VS Code: https://learn.microsoft.com/azure/azure-functions/functions-develop-vs-code 🔍 All Cozy AI Kitchen episodes: https://aka.ms/CAIK-YTPlaylist 🔔 Subscribe for more episodes: https://aka.ms/SubscribeMicrosoftDeveloper Hashtags: #CopilotHighlights #MicrosoftLearn #VisualStudio #GitHubCopilot #AI #DeveloperDocs #Python #AzureFunctions #VSCode #DotNet #Documentation #MachineLearning #SipAndSync #MicrosoftDeveloper #CodingWithAI