51ÊÓƵ

Workshop DescriptionÌý
This workshop introduces students to the basics of artificial intelligenceÌý(AI)Ìýin healthcare and its applications. Students learn what AI is in plain language, how it has evolved across the healthcare system, where it is being used today by providers and payers. They will learnÌýwhat ethical and practical considerations shape its responsible use. The session closes with a guided case study on claimsÌýautomationÌýso students can see AI at work in a real healthcare workflow.Ìý

Who Should AttendÌý

• Students new to artificial intelligence who want a clear, non-technical starting pointÌý

• Students inÌýtheÌýhealthcareÌýadministrationÌýprogramÌýÌý

• Entry-level healthcare workers and career changers exploring how AI is changing day-to-day rolesÌý

What’s IncludedÌý

• Introduction to the World of AI in HealthcareÌý

• Foundational knowledge on AI's evolution in healthcare, including key milestones, ethical considerations, and real-world impactÌý

• Case study: claims automationÌý

PrerequisitesÌý
None.Ìý

Workshop DetailsÌý
Live online through Microsoft Teams. The session runs as a single 90-minute block with a short break, and emphasizes active participation through chat, polls, and guided discussion.Ìý

WhatÌýYou’llÌýLearnÌý

• WhatÌýAIÌýis and is not, explained in everyday language with the key terms used in healthcare settingsÌý

• How AI has evolved in healthcare, from early clinical decision support and electronic records to today’s predictive analytics and generative AI toolsÌý

• Where AI shows up across the healthcare system, including provider organizations, insurers and other intermediaries, and patient-facing toolsÌý

• Common real-world applications such as documentation support, imaging and diagnosticÌýassistance, scheduling, risk prediction, and administrative automationÌý

• Why healthcare data is different, and what privacy, security, and consent mean when that data is used to train and run AI modelsÌý

• Core ethical considerations, including bias and systematic error, transparency, competing interests, and the need for human oversightÌý

• How AI supports claims automation end to end, from eligibility verification and coding review to denial prediction and appeals supportÌý

• How to review AI-generated output critically and recognize when a human decision isÌýrequiredÌý

• Where entry-level healthcare roles fit into AI-supported workflowsÌýÌý

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Session Details*Ìý

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*Session details are subject to change.