Health Data in Practice MRes

Program Overview

The Health Data in Practice MRes program at Queen Mary University of London equips students with the skills and knowledge to apply human-centered data research to health and care data. The program covers topics such as data analysis, interpretation, communication, and ethical frameworks, preparing graduates for careers in health data science, epidemiology, and public health. The program is taught by a team of academics and practitioners and features a combination of lectures, seminars, workshops, and an independent research project.

Program Outline

Degree Overview:

The Health Data in Practice MRes is a postgraduate program offered by Queen Mary University of London in collaboration with the Wellcome Trust.

Objectives:

• Understand the ethical and legal frameworks governing health data access and use
• Gain technical skills in data analysis and interpretation
• Develop communication skills necessary to effectively present research findings and engage with stakeholders
• Prepare for doctoral study or a career in health data science

Program Description:

The Health Data in Practice MRes program is a 1-year, full-time program starting in September 2024. Students will take six taught modules and complete a 60-credit independent project module.

• Provides an introduction to epidemiology and statistics with a focus on quantitative analytic approaches
• Develops knowledge and understanding of how to design, analyze, and interpret epidemiological studies with an application to public health and clinical practice
• Covers research designs that use health data or can be conducted within health data, including cluster-randomized trials, stepped-wedge designs, trials-within-cohorts/registries, interrupted-time-series

Module 2: Effective and Efficient Evaluation

• Introduces principles of effective and efficient evaluation, exploring different uses of health data in evaluation
• Covers research designs used in evaluation, for example in recruitment, or to measure outcomes
• Examines tools such as wearables or mobile phone apps in evaluation, cost-effectiveness analyses, use of qualitative methods, and ethics of evaluation

Module 3: Qualitative Methods for Health Research

• Introduces 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
• Focuses on learning-by-doing and improving reflective practice
• Leads 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

Module 4: Introduction to Social Science Research

• Provides an introduction to social science research with a focus on quantitative analytic approaches
• Develops knowledge and understanding of how to design, analyze, and interpret social science studies with an application to public health and clinical practice
• Covers research designs that use health data or can be conducted within health data, including cluster-randomized trials, stepped-wedge designs, trials-within-cohorts/registries, interrupted-time-series

Module 5: Design for Human Interaction

• Explores designing for human interaction through lectures and practical exercises in which learners will design, prototype, and test their designs with end-users
• Includes designing and conducting user research and applying user research in design
• Examines different interaction design methodologies
• Requires learners to define a design brief, analyze the context of their design, generate and iterate on design ideas, and conduct user research to iterate on a prototype

Module 6: Neural Networks and NLP

• Introduces learners to the core principles of neural networks and natural language processing (NLP)
• Covers methods to extract and analyze different types of data from health records, social media, and wearable devices
• Explores the theoretical foundations of machine learning algorithms, with hands-on experience in designing and evaluating algorithms, and in interpreting the outputs of these algorithms

Assessment:

• Assessment will involve a combination of coursework essays, assignments, presentations, examinations, and a research project.
• The research project will be an independent piece of research relevant to one of the program's four scientific themes: Human-Data Interaction, Health Data in Practice, Effective and Efficient Evaluation, Actionable Information.

Teaching:

• The program will be taught by a team of academics and practitioners with expertise in health data science.
• The learning environment will be interactive and engaging, with a strong emphasis on student-led learning.
• The program will utilize a variety of teaching methods, including lectures, seminars, workshops, and group work.

Careers:

• The program will prepare graduates for a variety of careers in health data science, including:
• Data analyst
• Data scientist
• Research scientist
• Epidemiologist
• Public health officer

Other:

• Scholarships are available for students from low- and middle-income countries.
• Graduates of the program will be eligible to apply for the Program Transition Fund, which will support them in successfully transitioning to the next stage of their career.

Entry Requirements:

• A 2:1 or above at undergraduate level in a subject related to quantitative disciplines such as Statistics, Computer Sciences, Mathematics, Bioinformatics and Biomedical Sciences, and qualitative disciplines such as Anthropology, Ethnography and Social Sciences.
• Relevant subjects include quantitative disciplines such as Statistics, Computer Sciences, Mathematics, Bioinformatics and Biomedical Sciences, and qualitative disciplines such as Anthropology, Ethnography and Social Sciences.

Application:

• Applications for September 2024 entry will close on 5 January 2024 .
• The program is expected to start in September 2024.
• The program is not currently available as a standalone MRes in Health Data in Practice.

Full-time study:

• September 2024 | 1 year

Fees:

• Home: £4,700
• Overseas: £4,700

EU/EEA/Swiss students:

Unavailable

Register your interest:

• 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.