Low-Fidelity Simulation for Digital Health and Health Informatics Education
Low-fidelity simulation is an educational approach that uses simple, accessible learning activities to replicate real-world digital health scenarios without relying on expensive technology. In nursing informatics education, this includes structured case studies, role-play, decision-making exercises, and simulated digital workflows that reflect contemporary clinical environments. These methods allow students to explore how data, electronic health records, artificial intelligence, and digital decision-support systems influence clinical care. Low-fidelity approaches are particularly valuable where resources are limited, enabling scalable and inclusive digital health education across diverse learning contexts.
Why is digital health and health informatics education a priority?
Healthcare systems are rapidly adopting digital technologies, including AI-enabled clinical decision support, telehealth, and data-driven care models. However, many health professional programs lack accessible ways to teach these capabilities. Traditional high-fidelity simulation environments can be costly and difficult to scale. Without new approaches, students may graduate without the skills required to safely engage with digital health systems.
Low-fidelity simulation offers a practical solution—supporting authentic learning experiences that build digital literacy, critical thinking, and professional judgement while remaining adaptable to diverse educational settings.
What was the purpose of this fellowship?
The fellowship aimed to develop a practical approach to teaching digital health and health informatics through low-fidelity simulation. The project sought to:
- explore educator and stakeholder perspectives on digital health capability development
- identify authentic learning activities reflecting contemporary clinical practice
- design curriculum resources aligned with nursing informatics competencies
- support educators to integrate digital health learning into existing courses
The work focused particularly on supporting undergraduate nursing education while generating approaches that can be adapted across health disciplines.
What were the fellowship outcomes?
The fellowship produced several outcomes supporting digital health capability development in health professional education. Key outputs include:
- a conceptual framework for low-fidelity digital health simulation
- curriculum design principles for integrating informatics learning into nursing education
- a suite of example teaching activities and authentic assessment strategies
- engagement with educators across the Faculty to explore implementation opportunities
The project also contributed to strengthening conversations around how digital health capability can be developed across health programs in sustainable and scalable ways.
What resources were developed?
Resources currently in development through the fellowship include:
- A Low-Fidelity Digital Health Simulation Framework
- Example teaching activities for nursing informatics and digital health
- Authentic assessment strategies aligned with clinical digital practice
- Curriculum design guidance for integrating informatics learning outcomes
These resources will support educators seeking practical ways to introduce digital health learning without requiring specialised simulation laboratories or advanced technology.
How does the work from this fellowship inform future practice?
This fellowship provides a foundation for integrating digital health capability development across post-graduate health professional education in Australian settings. The framework supports educators to embed digital health learning in existing curricula while remaining adaptable to different institutional contexts. Future work will focus on:
- evaluating student learning outcomes
- expanding interdisciplinary applications
- developing educator networks for sharing digital health teaching practices
Over time, this approach aims to support the preparation of health professionals who can safely and critically engage with emerging digital and AI-enabled healthcare systems.