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Combining the principles of health care epidemiology with hands on applications

5 days

Paid Course

Statement of Participation

20 Masters level credits

Course details

This course is taught at an intermediate to advanced level and assumes that students have completed the Introductory Analysis of Linked Health Data course or have equivalent knowledge. Advanced principles of health care epidemiology are combined with hands-on practical exercises in the implementation of computing solutions. The module provides students with a theoretical grounding on each topic, followed by a training session on the corresponding computing solutions. Students use de-identified data files in the hands-on exercises. The computing component of the module assumes a basic competence in the preparation of computing syntax for programs such as SPSS, SAS, STATA or R and familiarity with the statistical analysis of linked data files at an introductory to intermediate level.

This course is worth 20 Masters level credits.

Who should attend?

Ideal for those who wish to build on a pre-existing theoretical knowledge and skills in the analysis of linked health data.

Learning outcomes

By the end of the module, the student will be able to:

1. Critically evaluate the foundation concepts of epidemiology and data analysis

2. Critically appraise the methods for the conceptualisation and construction of valid measures and effect measures of health and social services utilisation and outcomes based on complex, multi-sourced linked data sets

3. Critically evaluate complex longitudinal research designs and how to implement them using multi-sourced linked data sets

4. Critically appraise case distribution designs and how to implement them using multi-sourced linked data sets

5. Demonstrate advanced skills in the analysis of linked mortality, institutional, pharmaceutical and primary care data

6. Construct computing syntax to prepare complex linked data files for analysis, derive exposure and outcome variables, relate numerators and denominators and produce results from advanced statistical procedures

Transferrable skills

1. Information technology
2. Database management
3. Statistical analysis
4. Information governance
5. Creative problem solving
6. Information literacy
7. Numeracy

Course dates

Monday 08 April – Friday 12 April 2024


UK non-commercial organisation (registration from Friday 01 December 2023):
£1,800.00 per delegate

UK commercial organisation (registration from Friday 01 December 2023):
£2,160.00 per delegate

International (non-commercial or commercial organisation):
£2,440.00 per delegate


Students will have the option to attend the lectures entirely online or attend classroom-based lectures held at:

Population Data Science Research Institute
Data Science Building
Swansea University
Singleton Park
SA2 8PP 

Taught by

Jointly delivered by Professor David Preen from the University of Western Australia and Dr Pete Arnold from Swansea University.

Course dates

Mon 08 Apr – Fri 12 Apr 2024

Course level


Delivered by
Swansea University

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