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We know that AI poses risks and also has potential for significant benefits. In January 2024, the Institute for Healthcare Improvement Lucian Leape Institute convened an expert panel to review the literature and explore these benefits and risks as they relate to consumer safety, focusing what they considered to be key uses for genAI in health care: documentation support, clinical decision support, and consumer-facing chatbots.
Policymakers around the world are considering how to best harness the transformative potential of artificial intelligence (AI) for productivity while trying to anticipate and limit associated risks.
This IHI blog explores the potential for the use of generative AI tools in quality management and it is a timely exploration. The time is now for quality managers and executives to plan to employ AI to enhance the quality system while building protection against the downsides – before they occur.
Artificial intelligence is coming at us – no matter where we sit on the human services’ spectrum. The potential care and service applications as well as risks are many and varied. When we look through the consumer safety lens – what do we see?
Quick reference guide on eight key areas where AI and Robotics change the way we work in human services.
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Health and human services’ managers, practitioners and policymakers all over the world are exploring the impact of Artificial Intelligence (AI). This commentary piece summarises a comprehensive report, co-authored by McKinsey Co. and the European EIT Health think-tank, on the potential impact of AI in healthcare. They use the European Parliament definition of AI as ‘the capability of a computer program to perform tasks or reasoning processes that we usually associate with intelligence in a human being.’
The rate of AI (Artificial Intelligence) in healthcare is growing, with immense scope for its application in healthcare – from robotic surgery and virtual nursing assistants, to preliminary diagnosis and automated image diagnosis. Where AI abuts the clinical interface, so must its governance. Therefore, governance in AI must include clinical governance.
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As we see an ever-growing utilisation of AI applications in healthcare, we stop to take a deeper look into its governance considerations, its fit within our clinical governance frameworks and what we need to consider when applying it in a clinical setting.
This webinar will include an anonymous audience interactive applied AI in healthcare scenario session to test and challenge its application in the delivery of safe, quality care.
An important aspect of clinical governance, particularly in primary and community care, is monitoring and early intervention. Particularly important in older people in the early detection of functional decline or clinical deterioration.
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