Health Informatics with Data Science PGCert

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; these skills and awareness are currently 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. You’ll 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
• 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, Institute of Health Sciences, plus strong collaborations with Computer Science.

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; they’re involved in a variety of ongoing research projects to improve and redesign health services to better serve patients.

More information

You’ll benefit from our excellent 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.

Course details

You will study modules totalling 60 credits. These are made up of four core (compulsory) taught modules.

Key topics relating to health data include:

• Informatics and Data Science
• Foundations of Health Data
• Statistics and Modelling
• Law, Ethics and Governance

Compulsory modules

Statistics and Modelling for Health Sciences (15 credits) You'll be introduced to statistical testing, generalized linear models (GLMs) and survival models, which are the foundation for analysing observational healthcare data. By the end of the course you will be able to model various healthcare outcomes of interest on real-life datasets including 30-day mortality, treatment costs, length of stay in hospital, from NHS digital etc. The module will also convey best practice in model evaluation and validation, based on the TRIPOD and STAR-D guidelines for reporting of statistical models in medical journals.

Foundations of Health Data (15 credits) You'll learn what, when, how, why and by whom health data is collected, processed and shared in the health domain. You'll also learn the different categories of health data (e.g. prescriptions, procedures, referrals) and dimensions of health (e.g. patients and time) will be described. You'll 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.

Informatics and Data Science in Health Care and Research (15 credits) You'll be introduced to a modern conceptualisation of Health Informatics with Data Science and to the central supporting role of Health Informatics and Health Data Science in the broad and complex activities involved in delivery quality evidence driven health care. This draws on the evidence base and the research methodologies supporting innovation and research.

Law, Ethics and Governance for Health Data Science (15 credits) This module introduces you to the legal, ethical and governance frameworks that are applicable to health data science. You'll also be introduced to technical and organisational safeguards that can be used in health data science projects. You will develop their ability to analyse health data science projects with respect to their legal, ethical and governance implications and will be encouraged to consider some of the key legal, ethical and governance challenges posed by health data science.

Learning and teaching

Our course is taught through a variety of lectures, practical classes, tutorials and seminars. 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.

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.

How to apply

Application deadline 31 July 2025 for all applicants.

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.

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.

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.

Contact us

School of Medicine Postgraduate Admissions

Email: pgmed-admissions@leeds.ac.uk
Telephone:

Fees

UK: £4,250 (Total)

International: £9,750 (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 PGCert 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 or 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 or 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.

Careers support

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.