MSc Health Data Science / Course details

Year of entry: 2022

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Course unit details:
Introduction to Health Data Science

Unit code IIDS67681
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Division of Informatics, Imaging and Data Sciences
Available as a free choice unit? No


The role of the health data scientist is to be able to turn health data into useful intelligence to provide insights into past and current healthcare delivery, and to help use this intelligence to inform decision-making to shape future healthcare delivery. To be able to do this it is critical to understand: (i) how to elicit requirements of the clinical and public health objectives and processes; (ii) the different data sources available to support decision-making, and which are appropriate to use; (iii) how health data are created, collected, stored, and retrieved; (iv) types of health systems and technologies and their implementation; (v) how to handle patient data in a confidential and secure manner to ethical and quality standards that are appropriate for a modern health service; (vi) understand which techniques and methodologies are most appropriate to investigate data; and (vii) how to communicate and visualise results /ideas to various stakeholders in order to turn the insights from the data into decision-making. This unit will integrate technical and methodological skills with each of these issues and apply them to uses of data and systems in healthcare. This unit will be delivered in the context of a number of real-world case-studies drawn from research at the University of Manchester and NHS.


  • The unit aims to:
  • Examine the role that health data science plays in aiding healthcare decision-support and decision-making
  • Explore the health data landscape, including different healthcare systems and technologies
  • Introduce the key concepts and issues around data management and retrieval, including the important principles and knowledge of information governance and security
  • Investigate, and apply, different approaches to system development
  • Critically appraise system design/development/delivery, including exploring areas for improvement
  • Examine the role that stakeholders, including patients, play in designing systems, how to capture their requirements, and examine how to incorporate their requirements into system development
  • Develop the strong healthcare acumen, problem-solving skills and communication skills that are required for a health data scientist



Learning outcomes

  • 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

Teaching and learning methods

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.

Knowledge and understanding


  • 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






Intellectual skills

  • 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

Practical skills

  • 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

Transferable skills and personal qualities

  • 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

Employability skills

Group/team working
Work collaboratively within a team
Project management
Understand about resource allocation and project planning
Problem solving
Work through the problem solving cycle

Assessment methods

Method Weight
Oral assessment/presentation 70%
Practical skills assessment 30%

Feedback methods

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.

Recommended reading

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

Study hours

Scheduled activity hours
Lectures 18
Tutorials 24
Work based learning 30
Independent study hours
Independent study 78

Teaching staff

Staff member Role
Georgina Moulton Unit coordinator
Sabine Van der Veer Unit coordinator
Glen Martin Unit coordinator

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