Module manager: Ruth Evans
Email: r.p.evans@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2025/26
As per programme entry requirements
This module is not approved as an Elective
This module introduces students to what, when, how, why and by whom health data is collected, processed and shared in the health domain. The different categories of health data (e.g. prescriptions, procedures, referrals) and dimensions of health (e.g. patients and time) will be described. Students will then be introduced to some of the key data sources and data flows in the health domain and will consider how the provenance of data can impact data quality and subsequent usage. Data standards will be described as a mechanism to achieve syntactic and semantic interoperability in the health domain.
The purpose of this module is to:
- Give students an understanding of the heterogeneity, scale and complexity of data that is collected, processed and shared in the health domain
- Provide students with knowledge of how data standards can be used to reduce ambiguity and increase interoperability in the health domain
- Equip students with an understanding of data provenance and data quality, and how they impact on subsequent usage
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Articulate the different categories and dimensions of health data
2. Demonstrate a sophisticated understanding of the key data sources and flows in the health domain
3. Critically analyse the provenance of health data and evaluate the potential impact on data quality
4. Demonstrate a sophisticated understanding of the different ways in which health data is used to drive decisions in the health domain
5. Critically evaluate the role of data standards in syntactic and semantic interoperability
6. Critically interpret key data standards that are used to represent health data
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:
1. Demonstrate how a research question may be refined to inform the planning of a research study using existing datasets
2. Use appropriate online sources to find detailed relevant information about health datasets
3. Critically appraise sources of health data for research and demonstrate understanding of their suitability for addressing a specific research question
Considerations when working with large datasets: Research questions and routine data; Clinical terminology and classification; Data provenance; Data linkage; Bias and error; Standardisation and interoperability
Perspectives on working with routinely collected data from (or in) different contexts: Primary care; Secondary care; Mental health; Health economics; Cohorts and registries; International settings.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 24 | 1 | 24 |
| Seminar | 6 | 1 | 6 |
| Independent online learning hours | 6 | ||
| Private study hours | 114 | ||
| Total Contact hours | 30 | ||
| Total hours (100hr per 10 credits) | 150 | ||
Lectures and seminars will be interactive, including group discussion and problem-based exercises. There will be plenty of opportunity for rapid face-to-face feedback and clarification from the tutors during classes.
There will be a group presentation, prepared as a group learning task and delivered by students at the end of the teaching week. This will be based on a similar task to the summative report and provides an opportunity for verbal feedback from staff and peers.
A draft outline of the written coursework will be submitted for formative assessment, so students will gain individual feedback directly applicable to their preparation for the summative work.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Coursework | Formative coursework - Group presentation | 0 |
| Coursework | Formative coursework - Draft outline of summative report (500 words) | 0 |
| Coursework | Summative coursework - Summative report based on a real-world scenario, considering potential data sources for research (3,000 words) | 100 |
| Total percentage (Assessment Coursework) | 100 | |
Students who fail the first attempt at the summative coursework will be offered an opportunity to resubmit. The resubmission will take the same format as the first attempt.
The reading list is available from the Library website
Last updated: 08/05/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team