Health Informatics with Data Science MSc
Year of entry 2024
- Start date
- September 2024
- Delivery type
- On campus
- Duration
- 12 months full time
- 36 months part time
- Entry requirements
- A bachelor degree with a 2:1 (hons) in a relevant subject e.g. Social Sciences, STEMM, Nursing (or equivalent) OR previous work experience (minimum 2 years) of handling and/or analysing data.
Full entry requirements - English language requirements
- IELTS 7.0 overall, with no less than 6.5 in each component
- UK fees
- £12,250 (Total)
- International fees
- £27,500 (Total)
- Contact
- pgmed-admissions@leeds.ac.uk
Course overview
Demand for professionals qualified in health informatics and data science is on the rise.The need for healthcare services is currently exceeding supply worldwide, and health providers and leading multinationals are heavily investing in information technology to provide solutions.
Our forward-thinking course provides insightful training into how modern applications of data and informatics in health management and planning can 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.
Course highlights
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.
- 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
- 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.
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 with a social science perspective as well as health economics and behavioural sciences.
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 Medical Research Council Regulatory Support Centre, contribute engaging talks to the course. Leeds is also home to a thriving digital economy, including leading healthcare technology providers TPP (SystmOne) and EMIS.
Course details
You will study modules totalling 180 credits. These are made up of six core (compulsory) taught modules and a research project, plus two optional modules from a range offered in Health Informatics, Data Science or Health Sciences.
Key topics relating to health data include:
- Informatics and Data Science
- Foundations of Health Data
- Statistics and Modelling
- Human Factors
- Law, Ethics and Governance
- Machine Learning
- AI
A choice of optional modules allows you to tailor your study to areas of interest. The research project will be your opportunity to apply your learning to practice, to work with a supervisor and customise a project within an area that is relevant to your own personal and professional development. This is an opportunity to demonstrate focused expertise to transform your career outlook.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.
Year 1 compulsory modules
| Module Name | Credits |
|---|---|
| Statistics and Modelling for Health Sciences | 15 |
| Foundations of Health Data | 15 |
| Human Factors in Health Data Science | 15 |
| Informatics and Data Science in Health Care and Research | 15 |
| Law, Ethics and Governance for Health Data Science | 15 |
| Artificial Intelligence and Machine Learning in Health | 15 |
| MSc Health Informatics Project | 60 |
Learning and teaching
Our course is taught through a variety of lectures, practical classes, tutorials, seminars and supervised research projects. We supplement face-to-face classes with extensive use of our virtual learning environment, meaning that materials will be available to support your studies at your own pace and in your own time.
In addition to group learning, you’ll also be able to use University facilities for independent study. These include computing facilities and four campus libraries as well as access to an extensive collection of online journals.
On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.
Assessment
The modules are assessed by a variety of methods including essays, reports and presentations. Some of the modules involve planning and executing analysis and validation of modelling using real-world health datasets.
Your results for every module contribute to your final degree classification and you must pass all compulsory and optional modules for course progression or award.
Applying
Entry requirements
A 2:1 in a relevant undergraduate degree e.g. Social Sciences, STEMM, Nursing (or equivalent) OR previous work experience (minimum 2 years) of handling and/or analysing health data.
This is an academically rigorous course. Applicants with other qualifications may be accepted if they can demonstrate suitable professional experience. Contact the admissions office if you are unsure of your eligibility.
We accept a range of international equivalent qualifications. For information contact the Admissions Team.
The course is also available as an intercalated MSc programme to students who have completed three years of a medical degree and are ranked in the top 50% of their year of study.
English language requirements
IELTS 7.0 overall, with no less than 6.5 in each component. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks).
We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional.
You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.
How to apply
Application deadline is 31 July 2024 for all applicants.
Please note that this is a very popular programme. If we receive a significant number of applications, and we are unable to process applications within our 6-week turnaround time, we may have to temporarily suspend the receipt of new applications until we are able to meet our turnaround target.
The ‘Apply’ link at the top of this page takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
Documents and information you’ll need:
- Evidence of work experience in supporting statement or CV as specified in entry requirements, if no relevant first degree.
- References not required as standard, although the programme leader may request a targeted reference on a case basis, especially in instances of non-standard entry
- If not already present, a CV which covers all relevant work experience in detail will be requested for non-standard applications.
- A Supporting Statement is required, covering three question prompts which must be addressed
Applicants are asked to answer the following questions in their Supporting Statement:
1) How have your previous studies and/or work experience prepared you for this course?
2) What knowledge/skills do you expect to acquire from this course?
3) What are your expectations from this course in relation to your future career?
Applications are considered on the basis of the applicant’s qualifications and experience.
Applications may close before the deadline date if numbers accepted reach capacity.
Part-time variant
The part-time variant of this programme is not suitable for international applicants who require a student visa. International applicants who do not require a student visa may be able to access the part-time variant of this programme by special arrangement. Please contact admissions for further information.
Admissions policy
School of Medicine Taught Postgraduate Policy 2024
This course is taught by
Contact us
School of Medicine Postgraduate Admissions
Email: pgmed-admissions@leeds.ac.uk
Telephone:
Fees
UK: £12,250 (Total)
International: £27,500 (Total)
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Find out more at Masters funding overview.
Studying in the School of Medicine at Leeds is an amazing opportunity, but we know that the cost can be difficult for many people to meet. If you are keen to join us, a range of funding opportunities are available.
DSE Award
Developing research capacity in Health Data Science (HDS) is a strategic priority for the UK National Institute for Health and Care Research (NIHR) Academy.
Their DSE Award is “a post-doctoral level funding opportunity aimed at supporting early to mid-career researchers in gaining specific skills and experience to underpin the next phase of their research career.”
It is open to applicants from clinical and non-clinical backgrounds and can be used to fund MSc-level modules or full courses in HDS. The Leeds MSc in Health Informatics with Data Science fully addresses the key skill areas identified in Annex C of the NIHR Academy’s guidance document here.
Career opportunities
97% of our recent Health Informatics with Data Science graduates feel they've taken meaningful next steps since university.
This exciting course provides superb training for:
- graduates looking to specialise in health informatics of health data science
- health service employees seeking to enhance their careers by gaining skills in data science
Our graduates have gone on to have successful cross-industry careers in health management, analytics and informatics, with some founding businesses in digital health and others pursuing research degrees. Our graduates are employed in a wide range of roles at various levels of seniority, in health, industry, government and NGOs.