Clinical AIACADEMY
The learning path

MODULE 7 / 8

Working with Large Language Models (LLMs) in Clinical Practice

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Section 1 of 10

In this module

Topics to explore:

  • Explain what large language models (LLMs) are and how they generate text
  • Define hallucination in the context of LLMs and describe why it occurs
  • Identify safe versus high-risk clinical use cases for LLMs
  • Apply basic prompt engineering principles to get more reliable LLM outputs
  • Describe the data protection risks of using commercial LLMs with patient information
  • Outline the key elements an institutional LLM policy should address

Slide 1 – LLMs Are Already in Your Workplace

Whether your institution has approved them or not, large language models (LLMs) — tools like ChatGPT, Claude, Gemini, and Microsoft Copilot — are already being used by healthcare professionals every day.

They're being used to draft clinic letters, summarise research papers, answer clinical questions, and generate documentation.

This module is not about whether you should use them. It's about using them safely, understanding where they fail, and knowing what your institution needs to have in place to govern their use.