MSc Health Data Science

For entry in the academic year beginning September 2026, the tuition fees are as follows:

• MSc (full-time)
  UK students (per annum): £15,800
  International, including EU, students (per annum): £35,700
• PGDip (full-time)
  UK students (per annum): £12,600
  International, including EU, students (per annum): £28,600
• PGDip (part-time)
  UK students (per annum): £6,300
  International, including EU, students (per annum): £14,300
• PGCert (full-time)
  UK students (per annum): £6,300
  International, including EU, students (per annum): £14,300
• PGCert (part-time)
  UK students (per annum): £3,150
  International, including EU, students (per annum): £7,150

Further information for EU students can be found on our dedicated EU page.

The course fees include all the tuition, technical support and examinations required for the course. All fees for entry will be subject to yearly review. Courses lasting more than one year may be subject to incremental rises per annum. For general fees information please visit: postgraduate fees . Always contact the department if you are unsure which fee applies to your qualification award and method of attendance.

The University permits applicants with comparable previous experience to submit an application for consideration of AP(E)L Accreditation Prior (Experiential) Learning. The maximum AP(E)L is 15 credits to a PGCert, 45 credits to a PGDip and 60 credits to a MSc.

If your AP(E)L application is successful, the University charges £30 for every 15 credits of AP(E)L. The overall tuition fee is adjusted and then the administrative charge is applied.

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

For the latest scholarship and bursary information please visit the fees and funding page .

The Catherine Chisholm scholarship is applicable to students from selected countries for this course. Find out more details on the scholarship page .

The University of Manchester is proud to offer six fully-funded scholarships to Women from Brunei, Cambodia, Indonesia, Lao PDR, Myanmar, the Philippines, Singapore, Thailand or Timor-Leste completing specific master's courses in STEM subjects. Please visit the STEM scholarship page for more information.

The role of the health data scientist is to turn health data into insights into past and current healthcare delivery, and to help use these insights for informing decisions about healthcare delivery in the future. To be able to do this, it is critical to understand: (i) the different types of health information systems and technologies and how they are used for care delivery; (ii) how health data is created, collected, stored, and retrieved; (iii) the different data sources available to support decision-making, and how to determine which ones are appropriate to use; (iv) how to handle patient data in a confidential and secure manner to ethical and quality standards that are appropriate for a modern health service; (v) which techniques and methodologies are most appropriate to investigate data; (vi) how to elicit requirements of health professionals and other stakeholders, in line with their objectives and processes; and (vii) how to communicate and visualise results for various stakeholders, so that it provides them with meaningful insights from the data.

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In this unit, you will learn about socio-technical and methodological approaches for going from health data to insights for informing decisions about healthcare delivery. You will apply these approaches to uses of data and systems in healthcare, illustrated with real-world case-studies drawn from projects and research done in clinical practice settings. 

You will do this by covering three main areas:

1. Health Information Systems and the Health Data Landscape 
2. Handling and Investigating Health Data 
3. Health Data Visualisation to Support Stakeholders’ Decision Making
    

• ​​​​Health data landscape, data models/ architecture, data storage and retrieval technologies and data linkage methodologies/principles
• Information governance and security
• Health Information Systems and Technologies (e.g., social and mobile health technologies, architectures, networks, internet, cloud)
• System design cycle and methodologies
• Stakeholder requirements gathering
• Principles of data visualisation/ communicating data to stakeholders
• Application of system design cycle to create a data visualisation/dashboard
• Communication/presentation styles

This unit will be delivered in a blended format: e-Learning preparation material will impart basic and core knowledge whilst the face-to-face (F2F) workshops will formalise the content and encourage attendees to draw upon their own reading and experience. Specifically, the F2F workshops will be delivered as workshops, where each block will cover a key section of the module/ learning material. The F2F sessions will consist of lecture/structured discussion, group problem-based activities, and real-world case studies (drawn from University of Manchester research-driven projects and current NHS projects).

Throughout the module, students will be placed in groups. They will work in these groups for problem-based activities (formative assessment), as well as allowing the students to actively participate in the different stages of systems design of a ‘informatics’ solution (data visualisation) to a specific healthcare delivery problem (COPD/asthma). At the end of the unit, students are asked to present this in a ‘dragons den’ (contributing 30% of the overall assessment mark).  In addition, at regular times in the F2F workshops students will present back to other students and tutors to show and share thinking.

Following each F2F session, students will be asked to reflect upon their learning using the online space (e.g. forums), and reflect on the material.

• Discuss the health data landscape and the pathway from data collection, interpretation, analysis, visualization and decision-making
• Understand the different approaches to system development, including how to turn user/stakeholder requirements into development processes
• Discuss the range of technologies available to produce, store and retrieve data
• Evaluate the technical, ethical and legal problems associated with the use of health data
• Discuss and understand concepts in data modelling

• Critically review a system/technology or data modelling plan and make suggestions for improvement
• Explore, capture and communicate system requirements related to stakeholder needs 
• Apply systems methodologies to a healthcare problem
• Produce visual and textual documentation to communicate the design of a system in a formal and structured way
• Identify and appraise data sources used to support healthcare decision making

• Elicit information from various stakeholders of a systems requirements gathering exercise, and communicate the results
• Use systems methodologies to design a technological solution to a healthcare problem, or a data visualisation/dashboard

• Communicate effectively both in written and verbal format to both non-technical and technical audiences (including in public) 
• Be able to plan a project, including appreciation of resource allocation 
• Work though the problem-solving cycle 
   

Formative assessment and feedback to students is a key fature of the on-line learning materials for this unit.  Students will be required to engage in a wide range of interactive exercises to enhance their learning and test their developing knowledge and skills.  In addition, there will be a series of supervised pratical hands-on exericses that will allow for verbal feedback.

Davies, A, Mueller, J, Developing Medical Apps and mHealth Interventions: A guide for researchers, physicians and informaticians. Springer