Program Overview

HLSC505 - Health Data Fundamentals

Year

2022

Credit Points

10

Campus Offering

No unit offerings are currently available for this unit.

Prerequisites

Nil

Unit Rationale, Description, and Aim

The rapidly emerging digital health landscape requires fundamental knowledge relating to data, data use, and digital ecosystems. In addition, there is a need for professionals working in health to understand how data can be used to improve service provision and person-centeredness. Health data represent the greatest asset supporting value-based health care within a digital health ecosystem. Health data supports individual patient health journeys, person-centered care, work, and communication flows. Secondary use of health data informs decision-making, resource management, analytics, reporting, funding, and policy development. Health data fundamentals refer to specialized components of the new interdisciplinary science now known as digital health. These include health data, their attributes, collection, storage, stewardship, governance, semantics, and the ethical use as components of any data supply chain within a digital health ecosystem.

Learning Outcomes

To successfully complete this unit, you will be able to demonstrate that you have achieved the learning outcomes detailed in the table below. Each outcome is informed by a number of graduate capabilities 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.

• Explain the importance of the adoption and use of data standards within a digital health ecosystem (GA5)
• Describe the health data supply chain and data use at every level within a national digital health ecosystem (GA5)
• Analyse information and communication flows required to support people's health journeys and the data supply chain (GA4)
• Critically evaluate the link between the adoption of health data standards and health data exchange protocols relative to data integrity and ethical use of data (GA3, GA8)

Graduate Attributes

• GA3: Apply ethical perspectives in informed decision-making
• GA4: Think critically and reflectively
• GA5: Demonstrate values, knowledge, skills, and attitudes appropriate to the discipline and/or profession
• GA8: Locate, organize, analyze, synthesize, and evaluate information

Content

Topics will include:

• Health languages and their attributes suitable for a digital era
• Health data standards, including data specification for the data supply chain, maintaining data integrity, stewardship
• Coding and classification systems, ownership, use cases, and implementation
• Terminologies, degrees of data expressivity, and formalisms
• Domain ontologies, reference information models
• Data modeling, templates, presentation formats
• Data collection, accurate little data, data value sets
• Data storage methods and data supply chains
• Registries, data lakes, data hubs, and warehouses
• Managing digital data access, transfers, linkages, querying
• Big data, ethical data retrieval, primary and secondary use, legislation
• Data/information governance at all levels

Learning and Teaching Strategy and Rationale

This unit uses an active learning approach to support students in the exploration of knowledge essential to the discipline. Students are provided with choice and variety in how they learn and will have access to self-paced learning modules, readings, webinars, discussion forums, and assessment tasks.

Assessment Strategy and Rationale

The assessment strategy for this unit allows students to demonstrate a critical mindset in evaluating the impact of data and information management strategies associated with the delivery of person-centered health services.

Overview of Assessments

• Assessment Task 1: Requires students to apply their critical knowledge of concepts and skills learned throughout this unit of study. The purpose of this assessment task is to evaluate the student's grasp of the complexities associated with data standards within any healthcare organization and setting supporting individual health journeys. (25%)
• Assessment Task 2: Requires students to apply knowledge learned in their exploration of how data attributes and characteristics interact with various health informatics data exchange standards, and reflect on retaining data sharing semantics and information computability. (30%)
• Assessment Task 3: Requires students to apply their critical knowledge of concepts and skills learned throughout the unit and produce a case study report. The case study can be based on the student's work situation where applicable, or a defined example case study. (45%)

Representative Texts and References

• Australian Institute of Health and Welfare. (2018). Metadata standards.
• Celi, L. A., Majumder, M. S., Ordońez, P., Osorio, J. S., Paik, K. E., & Somai, M. (Eds.). (2020). Leveraging data sciences for global health. Springer (Open Access)
• Cimino, J. J. (1998). Desiderata for controlled medical vocabularies in the twenty-first century. Methods of Information in Medicine, 37(4-5), 394-403. doi: 10.1055/S-
• Hovenga, E. J. S., & Grain, H. (Eds.). (2013). Health information governance in a digital environment. Studies in Health Technology Informatics 193. IOS Press.
• International Organization for Standardization. (2019). ISO/TS 21526:2019. Health informatics Metadata repository requirements (MetaRep). International Organization for Standardization
• Kubben, P., Dumontier, M., & Dekker, A. (Eds.). (2019). Fundamentals of clinical data science. Springer (Open Access)
• Standards Australia. (2005). AS : The language of health concept representation. Standards Australia
• Standards Australia. (2015). IOS/IEC 11179-1:2015. Information technology Metadata registries (MDR). Standards Australia