Project Spotlight: Developing a Framework for AI Scribe Evaluation
Building on our evaluation projects, CoDE is leading the creation of a robust, standardised framework for assessing Clinical AI Scribe technology.
Project Overview
As the market for AI scribe tools expands, there is an urgent need for clear, practical frameworks to ensure quality, consistency, and patient safety. Our work focuses on establishing standardised criteria and processes that organisations can use to evaluate AI scribes prior to implementation and throughout their lifecycle.
Framework Goals
Define Clear Evaluation Standards: Establish evidence-based measures for accuracy, completeness, reliability, and clinical safety.
Support Procurement and Deployment: Provide healthcare organisations with a structured approach for assessing and selecting AI scribe systems.
Enable Ongoing Quality Assurance: Develop monitoring tools to track real-world performance and support continuous improvement.
Principles Behind the Framework
Clinician-Centred: Ensuring that evaluation criteria align with real-world clinical needs and workflows.
Evidence-Based: Grounded in rigorous research and practical testing.
Adaptable: Designed to evolve as AI technologies and healthcare contexts change.
Why This Matters
As AI scribes become increasingly integrated into healthcare, a strong evaluation and quality assurance framework is critical to safeguard clinical standards, maintain patient trust, and maximise the benefits of these transformative technologies.
Our Approach
To develop this framework, CoDE is bringing together a diverse group of clinical leaders, digital transformation experts, health informaticians, and operational specialists from across the region. By drawing on a wide range of expertise and frontline experience, we aim to build a practical, scalable model that reflects the realities of clinical practice. This collaborative approach ensures that the framework will be robust, clinically relevant, and future-proofed for the rapid evolution of AI technologies.