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We live in an era of Big Data, where the routine capture of digital health information offers unprecedented opportunities to improve population health. Health Informatics is the science of managing, linking, and analysing large datasets to generate insights. By the end of the course, students will understand how to translate complex health data into rigorous, ethically sound research designs, preparing for careers in health research, epidemiology, and public health, or further study in Health Informatics or Data Science.
| Study Type | Postgraduate | Level | 5 |
|---|---|---|---|
| Term | Second Term | Credit Points | 15 credits (7.5 ECTS credits) |
| Campus | Aberdeen | Sustained Study | No |
| Co-ordinators |
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The aim of this course is to enable students to develop a critical and applied understanding of Health Informatics as a discipline that underpins contemporary health research, service planning, and policy evaluation. Students will explore how routinely collected digital health data can be harnessed to improve health outcomes, reduce inequalities, and inform evidence-based decision-making across healthcare systems. Emphasis is placed on cultivating both conceptual and practical competencies — from understanding complex data infrastructures to designing ethically robust, methodologically sound studies that make responsible use of linked health data.
The course provides a detailed introduction to the principles and practices that define health informatics research. Students will examine key data sources within the UK and internationally, with a particular focus on administrative and clinical datasets used in population health research, such as cancer registries, hospital episode statistics, and prescribing databases. Through guided exploration of real-world examples, students will develop the ability to evaluate the strengths and limitations of these data sources, including issues of completeness, representativeness, and data quality.
A core theme running throughout the course is data linkage — the process of combining records from different datasets to provide a more comprehensive view of patient pathways, disease trajectories, and treatment outcomes. Students will gain an applied understanding of linkage principles.
Another central focus of the course is research governance and ethics. Students will critically evaluate the frameworks that regulate the use of health data in research, including UK GDPR, the Common Law Duty of Confidentiality, and the operation of Trusted Research Environments (Safe Havens).
Methodologically, the course introduces students to the full data lifecycle, from study conceptualisation to data specification. Students will learn how to translate a public health or clinical problem into a measurable research question, develop a PICO framework, and apply causal reasoning tools such as Directed Acyclic Graphs (DAGs) to visualise relationships between exposures, outcomes, and confounders. They will then apply these concepts to the design of a realistic data linkage study, including the preparation of a data specification sheet detailing the variables, coding frameworks, and linkage fields required for analysis.
Teaching will be supported by a combination of lectures, interactive workshops, and applied assessment tasks that mirror real-world data research processes. For example, students will practise constructing research questions that can be answered using linked administrative data, designing causal frameworks to guide analytic strategies, and preparing mock applications for access to health data through a Safe Haven. These exercises will allow students to integrate methodological, ethical, and governance considerations into a coherent research design — preparing them for further study or professional roles in health informatics, epidemiology, and population data science.
Information on contact teaching time is available from the course guide.
| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | 38 | Feedback Weeks | 41 | |
| Feedback |
Assessment 2 will build on the first assessment and ask students to plan a Data Linkage Research Study that enables them to answer the research question developed in the Assessment 1. For Assessment 2 they are asked to update the RQ, PICO and DAG following the feedback received for Assessment 1. Students will again be asked to write a report (1250 words) based on the template they will be provided with. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Understand and apply health informatics in research and to public health and care |
| Procedural | Create | Create a data specification for a data linkage study |
| Procedural | Evaluate | Understand and apply the principles of data linkage |
| Reflection | Evaluate | Evaluate key data resources for understanding health |
| Reflection | Evaluate | Understand and evaluate the ethical, confidentiality, data protection and information governance issues relating to Health Informatics Research and population statistics |
| Assessment Type | Summative | Weighting | 50 | |
|---|---|---|---|---|
| Assessment Weeks | 32 | Feedback Weeks | 35 | |
| Feedback |
Assessment 1 will ask students to develop a research question, PICO and a DAG, and write a short report (750 words) following the template that will be provided. Written individual feedback will be provided to each student within 3 weeks of submission. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Procedural | Apply | Understand and apply health informatics in research and to public health and care |
| Procedural | Create | Create a data specification for a data linkage study |
| Procedural | Evaluate | Understand and apply the principles of data linkage |
There are no assessments for this course.
| Assessment Type | Summative | Weighting | 100 | |
|---|---|---|---|---|
| Assessment Weeks | Feedback Weeks | |||
| Feedback |
The resit assessment will combine assessments 1 and 2, and students will be asked to develop a research question, PICO and a DAG using a different dataset, and then to plan a Data Linkage Research Study that enables them to answer the research question developed. Students will be asked to write a report (2000 words) based on the template they will be provided with. Their result will be provided within the usual timeframe for resit assessments. Oral feedback can be provided at the student’s request. |
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
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| Knowledge Level | Thinking Skill | Outcome |
|---|---|---|
| Reflection | Evaluate | Understand and evaluate the ethical, confidentiality, data protection and information governance issues relating to Health Informatics Research and population statistics |
| Procedural | Create | Create a data specification for a data linkage study |
| Procedural | Apply | Understand and apply health informatics in research and to public health and care |
| Procedural | Evaluate | Understand and apply the principles of data linkage |
| Reflection | Evaluate | Evaluate key data resources for understanding health |
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