Unit rationale, description and aim
Health data is foundational to safe, effective and interoperable digital health systems, and the ability to understand, model and govern these data is essential for health and ICT professionals. Students will develop core high-level competencies in health data structures, standards, terminologies, system architectures and governance frameworks, supporting evidence-based decision making, digital transformation and the safe use of health technologies in clinical and organisational settings. Through the study of digital health ecosystems, electronic health records, interoperability standards, data models, ontologies, storage platforms and governance systems, they will learn how data are created, managed, exchanged and safeguarded across the health sector, with the unit integrating practical and strategic perspectives to support the application of standards, enhance system usability and ensure ethical and legislative compliance in the use of health information.
By engaging with real-world case studies, emerging technologies and contemporary data practices, students will develop the knowledge required to contribute effectively to digital health design, implementation and policy development. The aim of this unit is to enable students to understand and apply health data standards that support safe, interoperable and future-ready digital health systems.
Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
Describe the components and functions of digital h...
Learning Outcome 01
Analyse system architectures, interoperability app...
Learning Outcome 02
Apply clinical guidelines, terminologies, ontologi...
Learning Outcome 03
Critically evaluate technology evolution, system l...
Learning Outcome 04
Content
Topics will include:
· Digital Health Ecosystems and Infrastructure
· Electronic Health Records and Clinical Information Systems
· Systems Architecture, Interoperability and Standards Frameworks
· Technology Evolution, Systems Life Cycles and Safety
· Open Systems, Databases and Technical Approaches
· Terminologies, Languages, Ontologies and Information Models
· Data Management, Storage Platforms and Access Pathways
· Big Data, Governance, Ethics and Legislative Frameworks
Assessment strategy and rationale
The assessment strategy in this unit is designed to measure achievement of all learning outcomes while building professional capability in health data standards, interoperability and governance. To pass this unit, students must complete all assessment tasks, demonstrate achievement of every learning outcome, and obtain a minimum aggregate mark of 50% for the unit.
This strategy has been selected to ensure students develop the analytical and evaluative skills required to work effectively with health data in various digital health environments. Effective learning in this field requires the gradual development of foundational knowledge, followed by the application of more advanced reasoning and decision-making, reflecting the realities of designing, implementing and governing digital health systems.
The first assessment task focuses on establishing core skills by requiring students to examine and interpret data standards, terminologies and models within a defined digital health context. The second assessment task supports deeper critical engagement by asking students to analyse a real or simulated case study involving interoperability, data management or governance issues across the health data supply chain. Together, these tasks provide authentic opportunities for students to demonstrate achievement of each learning outcome and to receive meaningful feedback that supports ongoing learning and professional development.
Overview of assessments
Assessment Task 1: Case Study Report 1 Students ...
Assessment Task 1: Case Study Report 1
Students will apply their understanding of health informatics data standards to show how data semantics and computability are maintained, then use this knowledge to produce a brief case study report based on a real or provided scenario. The task assesses their ability to apply theory to practical health service delivery problems.
50%
Assessment Task 2: Case Study Report 2 T...
Assessment Task 2: Case Study Report 2
This assessment requires students to apply their knowledge of EHR attributes and health informatics standards, reflecting on how these influence desired EHR functionalities. Students will then use this understanding to produce a case study report, based on their workplace or a provided scenario, demonstrating their ability to apply theoretical concepts and practical skills to real-life business problems.
50%
Learning and teaching strategy and rationale
The learning and teaching strategy in this unit is designed to support both conceptual understanding and practical capability in health data standards and informatics. A combination of online modules, case studies, and applied exercises are used to introduce key concepts and demonstrate their relevance in real digital health environments. This learning approach enables students to connect theoretical knowledge with current industry practice and emerging technologies.
Online modules provide opportunities for students to develop skills in analysing data standards, modelling health information and evaluating governance requirements. These self-paced learning methods encourage problem solving and critical thinking, which are essential for work in complex digital health settings. This strategy is best suited to the unit because it supports progressive skill development, real-world application and the ability to translate data standards into safe and interoperable digital health solutions.