Linked Health Data: Short course in Health Data Linkage & Analysis
Unlock the power of linked health data to drive better health outcomes.
This hands-on short course is designed for professionals and students seeking to deepen their understanding of how health data linkage works—and how to apply it in real-world research and service improvement.
Participants will gain theoretical knowledge and practical skills in managing and analysing large, complex health datasets.
Course Highlights
- Explore the principles and practice of health data linkage
- Learn to design epidemiological studies using linked data
- Develop programming skills in R for real-world applications
- Understand data quality assurance and interpretation techniques
- Work with real linked health datasets in guided exercises
Who Should Enrol
This course is ideal for:
- Health statisticians, data analysts, and epidemiologists
- PhD candidates in health-related disciplines
- Medical professionals interested in health data analysis
Why Choose This Course?
Unlike other offerings focusing solely on theory, this course provides practical, hands-on training using real linked health data. You’ll learn to transform complex datasets into actionable insights that inform policy and improve health services.
Course Format
- 15 hours of pre-recorded lectures
- 5 hours of live webinars with expert educators
- 15 hours of self-directed learning activities
- Online discussion boards for peer and expert support
Topics
Introduction to Health Data Linkage
- Purpose and benefits of linking health datasets
- Overview of data sources (e.g., hospital, cancer registry, ambulance)
Data Linkage Methodologies
- Deterministic vs probabilistic linkage
- Linkage systems and infrastructure (e.g., CheReL, PLIDA)
Study Design Using Linked Data
- Applying epidemiological principles
- Constructing study populations and cohorts
Data Management & Preparation
- Cleaning and structuring large datasets
- Handling missing data and inconsistencies
Programming for Linked Data
- Writing R
- Deriving exposure and outcome variables
- Creating numerators and denominators
Statistical Analysis of Linked Data
- Techniques for analysing trends and outcomes
- Interpreting results and assessing reliability
Quality Assurance & Validation
- Checking linkage accuracy
- Ensuring consistency in definitions and coding
Ethics, Privacy & Governance
- Data security and confidentiality
- Legal and ethical considerations in data use
Real-World Applications
- Case studies using actual linked health datasets
- Translating findings into policy and practice
Learning Outcomes
- -Understand the theory of data linkage methods and features of comprehensive data linkage systems, sufficient to know the sources and limitations of linked health data sets
- -Apply epidemiological principles to the design of studies using linked data
- -Construct numerators and denominators for the analysis of disease trends and health care utilisation and outcomes
- -Assess the accuracy and reliability of data sources
- -Check data linkages and assure the quality of the study process, eg. consistency of definitions, missing data
- -List the issues to be considered when analysing large, linked data files
- -Write syntax to prepare linked data files for analysis, derive exposure and outcome variables, relate numerators and denominators, and produce results from statistical procedures.
Course delivery method
Online asynchronous. This course will open online on Monday 25 October 2026. One hour live webinars will run the below dates from1.00pm - 2,00pm.
Friday 30 October
Friday 6 November
Friday 13 November
Friday 20 November
Friday 27 November
This course will close online on Monday 30 November 2026.
Additional Information
For terms and conditions, please view here.
Participants must successfully complete at least 75% of the Program content to be eligible for completion recognition. Progression through the content will be tracked, and participants will be required to submit a self-declaration at the conclusion of the Program confirming that this completion threshold has been met. This declaration may be independently verified by the University if required.
Upon successful completion of the Program, participants will be issued with a Certificate of Completion from the University of Sydney.