Kuhnen and Rimal discuss tips and best practices regarding competent and effective implementation of artificial intelligence – generative AI, models of immense languages (LLM), predictive models and many others. They discuss how UNC Health ensures responsible acceptance of AI and Like Himss tools Analytical maturity assessment model He helped the healthcare system on this journey.
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Talking points:
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How and where UNC uses artificial intelligence and where he finds the greatest success
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Areas and cases of utilize in which he wins early winnings
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Operational and administrative applications of automation, compared to clinical applications
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How does this work to ensure responsible acceptance of AI tools
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Like his AI projects are implemented and scaled
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Early lessons stretched along the way, challenges and successes
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And useful cases UNC have not been raced yet, but he looks at the road
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Like the Himss Analytics maturity assessment model, which focuses on real -time and predictive ai data at stage 6, was helpful in this journey
More about this episode:
Himscast: Basics of data management – Lessons with Unc Health, part 1
Himsscast: Basics of data management – Lessons with Unc Health, part 2
Unc Health Care talks about how it achieved peak analytical maturity
UNC Health reaches stage 7 with advanced EMR, the possibilities of analytics
CIO CIO Unc Health Workative AI Work with Epic and Microsoft
Currently, AI management is needed, says the director of Analytics Unc Health
Creating a path for sustainable AI management
At Himss24 APAC, the adoption model for analytical maturity gets a facelift
The novel Analytics Up-to-date Himss maturity assessment model supports the implementation of wise AI