Study options
- Starting in
- September 2025
- Location
- Whitechapel
- Fees
- Home: £12,250
Overseas: £24,250
EU/EEA/Swiss students
What you'll study
Unlock the power of data to transform healthcare.
The MSc Health Data in Practice offers a cutting-edge, human-centred approach to health and care data, equipping you with the tools and insights needed to drive innovation in real-world setting. Immerse yourself in an interdisciplinary curriculum that integrates statistics, epidemiology, health informatics, health inequalities, and qualitative research methods, allowing you to harness multidisciplinary approaches to design impactful study and inform critical decision-making.
Through this MSc, you will gain a comprehensive foundation in quantitative analysis, qualitative methods, the context and provenance of health data, and practical data management, preparing you to solve the most pressing health data challenges.
You’ll also develop critical professional competencies, including analytical thinking, problem-solving, and clear communication - skills that are essential for thriving in the fast-evolving field of health data science.
Teaching from our expert faculty will ensure that you experience a holistic education that fuses key disciplines, empowering you to use data-driven insights to revolutionise healthcare outcomes.
Our MSc in Health Data in Practice will train a new generation of leaders in the health data fields, prepared to make significant contributions in the NHS, public and private sectors. Join us and be at the forefront of transforming healthcare through data science.
Structure
- Six compulsory modules
- Two option modules
- Research dissertation
Compulsory/Core modules
The module will include case studies to explore contemporary policy debates and the influence of quantitative research studies on public health and primary care policy and government intervention programmes. The advantages and disadvantages of different study designs and their application to different research questions will be covered. Students will gain skills in summarising quantitative data, including routine morbidity and mortality measures and interpreting the results of commonly used statistical techniques.
This module will provide an introduction to epidemiology and statistics with a focus on quantitative analytic approaches. Develop the knowledge and understanding necessary to design, analyse and interpret epidemiological studies with an application to public health and clinical practice. Gain practical skills in using statistical software to clean data, perform statistical analyses and display data. Learn to interpret findings crucial for evidence-based healthcare research, critically evaluate research and contribute to advancements in public health. This module equips students with the expertise to tackle complex health challenges through advanced epidemiological approaches and statistical modelling.
The module will introduce learners to principles of effective and efficient evaluation, exploring different uses of health data in evaluation, for example in recruitment, or to measure outcomes. It will cover research designs that use health data or can be conducted within health data, including randomised controlled trials, cluster-randomised and stepped-wedge designs, trials-within-cohorts/registries, interrupted-time-series, systematic reviews. Cost-effective analyses and ethics of evaluation will also be covered.
This course will equip students with practical skills for analysing routinely collected electronic health records (EHRs) data. During the course, the students will learn about the provenance of EHRs data, how to identify exposures and outcomes, how to apply analytical approaches in EHRs data, and how to conduct research studies using EHRs. The course will focus on a range of techniques for answering causal questions in EHRs such as propensity score methods, trial emulation, and case-only designs. The course will also cover developing and evaluating risk prediction models to support clinical decision-making, and provide hands-on experience with real-world EHRs data throughout.
In this module, students will work on a piece of independently produced research relevant to one of the programmes four scientific themes (Human-Data Interaction, Health Data in Practice, Effective and Efficient Evaluation, and Actionable Information). Students will be assisted in topic choice and guided through the process by one of the scientific theme leads but will be expected to collect data themselves, or organise access to it, and write the thesis independently. Potential topics will be identified in consultation with scientific theme leads and other academic staff involved with the programme, and a list will be made available early in Semester 2. The scientific theme leads will endeavour to facilitate student preferences. Some topics may be broad enough to accommodate more than one student at a time.
The module provides an introduction to health data in practice with a focus on health care delivery challenges and patient and population health outcomes from an interdisciplinary perspective. It will provide students with a grounding in legal and ethical frameworks governing health data access and use, and the role of patient, health professional and public engagement for delivering the full potential of health data sciences for public benefit.
This module provides students with essential knowledge and skills about Applied Research Methods. The general aim is to equip students with transferable skills that can be either used towards completing an empirical project or conducting a systematic review.
Elective modules
This module will examine the theories and evidence underpinning social inequalities in health (defined as the unfair and avoidable differences in health status). It will consider structural/material and psychosocial theories, and hypothesis about social drift, self-selection, and genetics. Attention is given to the WHO Commission on Social Determinants of Health. Sources of data and measurement of scale of inequalities between and within groups are addressed. The module will consider association with income and distribution of money, resources, and power at global, national, and local level. Policy interventions and their different approaches will be explored including universal and targeted or selective approaches to reducing inequalities by reducing the inequitable distribution of power, money, and resources.
In this module we address the fundamental public health question of how best to finance and organise health systems in order to achieve universal health coverage and the effective delivery of comprehensive PHC. We will be particularly concerned with the ways in which health care systems differ from the perspective of access to services among different social groups within the population, and also with the distributive effects of different organising principles such as market and public control. The relationship between health systems and the Primary Health Care Approach will be covered, as well as key debates around the interface between aid, global health governance and national health systems. This module will also cover the essential economic theories used to inform health systems policy.
The module will introduce learners to key microeconomic concepts and principles, their relevance to the health economy and the need for alternative approaches to priority setting and resource allocation. The module will then discuss key health economic analytical frameworks to inform resource allocation in health, exploring methods of economic evaluation, health policy evaluation, economic analysis of public health interventions, and analysis of inequalities in health and health care. Throughout the module, the focus will be on developing learners¿ ability to critically appraise, conceptualize, design, and carry out appropriate health economic analyses.
This module explores patient-generated data from health social media, teaching students how to collect and analyse such data to gain a deeper understanding of patient perspectives, social determinants, and unmet needs behind numerical data. By leveraging health social media analytics, students will uncover insights into patient care experiences, identify opportunities for quality improvement, monitor real-world health events, explore inequalities, evaluate drug safety, and assess perceptions that may influence patient engagement with health services and self-care practices. Methodological approaches include qualitative and quantitative analytics tailored to health social media data, with a focus on ethics and information governance. Clinical and public health applications emphasise understanding patients' perspectives to improve patient care.
This module will introduce learners to the principles of interpretive research and to a broad range of qualitative research practice including: interviews; focus groups; ethnographic approaches; participatory research methods; qualitative synthesis; mixed- methods designs. The importance of integrating theory and ensuring ethical practice in the design, conduct and analysis of research will be emphasised throughout. The module will lead learners through the research cycle from formulation of research idea to ensuring research impact with a focus on learning-by-doing and improving reflective practice.
This module provides students with practical application of Applied Research Methods. The general aim is to equip students with transferable skills that can be either used towards completing an empirical project or conducting a systematic review. There is no taught component in this module, except for 4 hours of tutorial sessions delivered on alternate weeks. These 4 sessions will be complementary to 5 tutorial sessions delivered in Semester 2 for Psychological Therapies:Paradigms and Systems and Psychological Therapies: applications and Effectiveness. The aim of these 4 tutorial sessions is to provide academic support for their completion of their Pilot study.
If you study full-time, you will take 3 compulsory modules and 1 elective module from a selection in each semester. If you study part-time, this will be spread across the two years.
Assessment
- 67% Modules
- 33% Dissertation
Assessment takes a number of different forms including coursework essays, assignments and presentations, and examinations. You will need to achieve an overall pass in the taught element in order to progress to your dissertation.
Dissertation
Undertake a supervised 60-credit dissertation focused on an area of health data in practice
Teaching
You will be taught through a combination of lectures, hands-on workshops, and small group seminars. The seminars are designed to encourage interactive discussion around health data topics and may include student-led presentations, group exercises, and practical data analysis sessions. Teaching will take place at the Whitechapel Campus, with access to state-of-the-art facilities for health data analysis.
The programme places a strong emphasis on practical experience with health data, and you will engage with real-world case studies from a range of healthcare areas, including primary care, public health, and clinical specialties. You will also have opportunities to participate in health data seminars and professional events, enabling you to build connections with experts in the field.
We collaborate with NHS partners, health research institutes, and organisations across east London and beyond, providing opportunities for research, practical placements, and community-focused projects. Students are encouraged to engage with both local and national health data initiatives to apply their learning in real-world contexts.
If you study full-time, you will typically have one one-hour lecture and one two-hour practical workshop or seminar per module, per week. Part-time students will take two core modules and two specialist modules in their first year; and complete the remaining two core modules, two elective modules, and their dissertation in the second year.
Where you'll learn
Facilities
At Queen Mary you will have access to a number of advanced facilities, some of which are designated exclusively to postgraduate students. These include:
- the Blizard Building, which has state of-the-art facilities for students and staff including open-plan research laboratories, office space, a 400-seater lecture theatre and a café, and several seminar rooms
- the newly refurbished Garrod building which includes study and social spaces for Faculty of Medicine and Dentistry students
- medical libraries located at The Royal London and St Bart's hospitals and at the Queen Mary Mile End campus
- access to the Postgraduate Reading Room
- research access to the British Library.
Campus
Your postgraduate learning experience is enhanced by our fantastic location in Whitechapel, in east London. This is the main home of Queen Mary University of London's Faculty of Medicine and Dentistry, close to The Royal London Hospital. Whitechapel is a vibrant area, famous for its street market, variety of curry houses and the Whitechapel Gallery.
The campus has its own library, state-of-the-art labs at the Blizard Institute and social and study spaces in the newly refurbished Garrod Building, including the students’ union.
You can also use all the facilities at the Mile End campus, which is ten minutes up the road.
About the Institute
Wolfson Institute of Population Health
This course is based at the Wolfson Institute of Population Health, which delivers internationally recognised research and teaching in population health. The Wolfson Institute is a part of Queen Mary University of London’s faculty of medicine and dentistry.
The work of our researchers and educators has had a significant impact on lives across the world. We provide integrated teaching and training opportunities delivered by leaders in the field. By sharing knowledge and pushing the boundaries of research, we will continue to advance population health and preventive medicine on a global scale.
Queen Mary is a member of the Russell Group of leading research universities in the UK and the Faculty of Medicine and Dentistry proudly holds an Athena Swan Gold Award in recognition of our commitment to gender equality.
Career paths
The MSc Health Data in Practice will equip you with the skills and knowledge needed to excel in leadership and strategic roles across the NHS, public health bodies, and private sector organisations, including health tech companies, consultancies, and pharmaceutical firms.
In the NHS, you could pursue roles such as health data analyst, clinical informatics specialist, or digital transformation lead, supporting evidence-based decision-making and improving patient outcomes. In the private sector, opportunities include positions in health data consultancy, digital health innovation, and health analytics.
You will develop career-ready skills such as advanced data analysis, problem-solving, and clear communication - critical for success in this fast-evolving field.
- 97% of Institute postgraduate taught graduates are in employment or further study 15 months after graduation (2021/22)
- 79% of Institute postgraduate taught graduates are in highly skilled work or graduate study (2021/22)
Fees and funding
Full-time study
September 2025 | 1 year
- Home: £12,250
- Overseas: £24,250
EU/EEA/Swiss students
Unconditional deposit
Home: Not applicable
Overseas: £2000
Information about deposits
Part-time study
September 2025 | 2 years
- Home: £6,150
- Overseas: £12,150
EU/EEA/Swiss students
Unconditional deposit
Home: Not applicable
Overseas: £2000
Information about deposits
Queen Mary alumni can get a £1000, 10% or 20% discount on their fees depending on the programme of study. Find out more about the Alumni Loyalty Award
Funding
There are a number of ways you can fund your postgraduate degree.
- Scholarships and bursaries
- Postgraduate loans (UK students)
- Country-specific scholarships for international students
Our Advice and Counselling service offers specialist support on financial issues, which you can access as soon as you apply for a place at Queen Mary. Before you apply, you can access our funding guides and advice on managing your money:
Entry requirements
UK
Degree requirements
A 2:1 or above at undergraduate level in a related discipline. Relevant subjects include quantitative disciplines such as Statistics, Computer Sciences, Mathematics, Bioinformatics and Biomedical Sciences, and qualitative disciplines such as Epidemiology and Public Health.
Applications from those with less quantitatively oriented Natural Sciences degrees, such as Biology and Medicine, are welcome if they have focused on the more quantitative elements of those degrees.
Other routes
Applicants with a 2:2 degree with relevant content and at least one year of relevant experience, for instance work in industry, analytics, diagnostic labs, scientific research etc, may be considered on an individual basis.
Find out more about how to apply for our postgraduate taught courses.
International
English language requirements
The English language requirements for our programmes are indicated by English bands, and therefore the specific test and score acceptable is based on the band assigned to the academic department within which your chosen course of study is administered. Note that for some academic departments there are programmes with non-standard English language requirements.
The English Language requirements for entry to postgraduate taught and research programmes in the Wolfson Institute falls within the following English band:
Band 4: IELTS (Academic) minimum score 6.5 overall with 6.0 in each of Writing, Listening, Reading and Speaking
We accept a range of English tests and qualifications categorised in our English bands for you to demonstrate your level of English Language proficiency. See all accepted English tests that we deem equivalent to these IELTS scores.
Visas and immigration
Find out how to apply for a student visa.