Demand for individuals qualified in health informatics and data science is on the rise. The demand for healthcare services is currently exceeding supply worldwide, and health providers and leading multinationals are heavily investing in information technology to generate solutions.
Our forward-thinking course provides insightful training into how modern applications of data and informatics in health management and planning can both use and generate evidence to influence policy and practice.
Created by experienced academics and professionals, our course is designed for both recent graduates and professionals looking to advance their careers. The course will develop your knowledge and understanding of health informatics, health data science techniques, and real-world application of research methods – skills that are highly sought after by employers.
We combine health, data and social science expertise with a research focus to develop knowledge, skills and awareness of sources and uses of evidence in healthcare.
Developing research capacity in health informatics and data science is a priority area internationally. Staff contribute expertise to the Research Methods Incubator of the UK National Institute for Health and Social Care Research (NIHR) Academy. With us you will be actively involved in listening to and informing the informatics and data science agenda for health.
Leading expertise
- Learn from experts in health informatics and data science, including in machine learning and AI (for MSc and PGDip only).
- Multidisciplinary research expertise is embedded within the curriculum.
- Learn from a curriculum informed by the latest understanding and practice, with academic teams in the Faculty of Medicine and Health, and the Institute of Health Sciences; and strong collaborations with Computer Science.
Flexible learning (for MSc and PGDip only)
- Both full and part-time options are available so you can apply your learning as you complete the programme.
- Create a bespoke learning journey and choose optional modules to reflect your own interests.
- Tailor your degree to your specific career ambitions, or the needs of your professional sector, including a choice of research projects (for MSc only).
To prepare you for these unique challenges ahead, we’ll support you to:
- Explore a new and innovative approach to health informatics, statistics and computer science that focuses on patient benefit and evidence-based, high-quality healthcare.
- Address human and technical challenges in healthcare and health data science.
- Develop your knowledge of fundamental statistical, social and governance concepts.
- Study a multidisciplinary approach to health informatics.
Through years of teaching and research, we’ve developed a strong reputation, both nationally and internationally, in health informatics and data science. Our staff are actively engaged in delivering education and skills training, and are involved in a variety of ongoing research projects to improve and redesign health services to better serve patients.
More information
You will benefit from our location too. The Leeds Teaching Hospitals NHS Trust is the largest UK hospital Trust. Leeds is also the headquarters for many Department of Health and Social Care organisations, including NHS England. Guest speakers from regional and national organisations, such as the Office of the National Data Guardian and the NHS West Yorkshire Integrated Care Board, contribute engaging talks to the course. Leeds is also home to a thriving digital economy, including leading healthcare technology providers TPP (SystmOne) and EMIS.
[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable
Candidates will be required to study the following compulsory modules:
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| YCHI5081M | Statistics and Modelling for Health Sciences | 15 | Semester 1 (Sep to Jan) | PFP |
| YCHI5082M | Foundations of Health Data | 15 | Semester 1 (Sep to Jan) | PFP |
| YCHI5083M | Human Factors in Health Data Science | 15 | Semester 2 (Jan to Jun) | PFP |
| YCHI5085M | Informatics and Data Science in Health Care and Research | 15 | Semester 1 (Sep to Jan) | PFP |
| YCHI5086M | Law, Ethics and Governance for Health Data Science | 15 | Semester 2 (Jan to Jun) | PFP |
| YCHI5087M | Artificial Intelligence and Machine Learning in Health | 15 | Semester 2 (Jan to Jun) | PFP |
| YCHI5091M | Research Project | 60 | 1 Sep to 31 Aug (12mth) | PFP |
Candidates will be required to study 30 credits from the following optional modules:
Candidates will be required to study 30 credits from the following optional modules:
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| MEDR5250M | Applied Qualitative Health Research | 15 | Semester 2 (Jan to Jun) | PFP |
| MEDR5260M | Introduction to Health Economics | 15 | Semester 2 (Jan to Jun) | PFP |
| NUFF5065M | Key Issues in International Health | 15 | Semester 1 (Sep to Jan) | PFP |
| NUFF5550M | Monitoring and Evaluation of Health Programmes | 15 | 1 Feb to 28 Feb (1mth) | PFP |
| YCHI5084M | Visualisation for Health Data | 15 | Semester 1 (Sep to Jan) | PFP |
Last updated: 16/04/2025 12:45:50
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