Mount Sinai Health System

Mount Sinai Health System Streamlines Clinical Workflows with AI Assistant

Mount Sinai Health System · Clinical documentation · Microsoft

Mount Sinai Health System is rolling out Dragon Copilot, Microsoft's advanced AI clinical assistant, across its hospitals and clinics. The platform integrates natural language, ambient listening, and generative AI on Microsoft Cloud for Healthcare to automate documentation, surface vital patient information, and reduce administrative workload. This system-wide phased deployment aims to address clinician burnout and inefficiencies in patient care documentation. The solution embeds directly into the clinical workflow, enabling voice-driven, ambient note-taking and simplifying complex administrative tasks. Initial deployment is in select departments, expanding to all clinical environments in 2026. The rollout includes comprehensive training, feedback, and evaluation measures to ensure secure and equitable AI integration. Mount Sinai's adoption is a key milestone in their digital transformation and serves as a model for responsible AI use in academic medicine.

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Mount Sinai Health System Advances Healthcare Analytics

Mount Sinai Health System · Clinical analytics · Microsoft

Mount Sinai Health System partnered with Microsoft Azure to develop artificial intelligence solutions aimed at improving patient outcomes and streamlining healthcare operations. This collaboration introduced 14 AI models that address significant challenges like predicting patient falls and malnutrition rates. By combining Microsoft Azure’s scalability and Mount Sinai’s expertise, this partnership pushes the boundaries of healthcare innovation through big data and data science.

TRAIN consortium ensures responsible AI for major US healthcare systems

Cleveland Clinic · Federated learning · Microsoft

A consortium of leading US healthcare providers, joined by Microsoft as the technology enabler, has established the Trustworthy & Responsible AI Network (TRAIN) to operationalize responsible and ethical use of artificial intelligence in healthcare delivery. Members include Cleveland Clinic, Duke Health, Johns Hopkins Medicine, Mass General Brigham, Mount Sinai Health System, Northwestern Medicine, and others. The network aims to enhance the quality, safety, and trustworthiness of AI by sharing best practices, registering clinical AI for operational use, providing tools to measure AI outcomes, and creating a federated outcomes registry. The collaboration targets improvement of clinical care quality, reduction of risks from AI deployment, and provision of practical tools to healthcare organizations nationwide for managing AI implementations and mitigating bias. Through this concerted effort, TRAIN promotes safe, reliable, and equitable use of AI, thus improving patient outcomes and establishing trust in the adoption of advanced technology in health settings.

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