MSt in Healthcare Data: Informatics, Innovation and Commercialization (2021-23) | Institute of Continuing Education (ICE) skip to content

Institute of Continuing Education (ICE)

Cambridge is a world-leading centre for innovation in electronic patient and clinical trial data. This is underpinned by an extensive and vibrant community of clinicians, researchers, entrepreneurs, and commercial and public sector organisations. There is a recognised shortage of the appropriate technical and practical skills in the workforce to effectively utilise the opportunities presented by healthcare data.

This course has been designed to meet the skills gap in the management, handling and utilisation of healthcare data and to develop individuals confident in using healthcare data for innovative and/or commercial applications.

Watch a recording of the Virtual Open Day with Dr Ronan O'Leary, Cambridge University Hospitals and Dr Tom Monie, University of Cambridge.



Unit details

Course Units and Teaching Weeks

Please note that dates are provisional and may be subject to change.

Unit 1: Research Skills, Governance and Innovation (20 Credits)

Unit 1 provides the landscape to understand the breadth of patient level data in the healthcare and economic landscape in the UK and globally. It provides knowledge of the technical, legal, and ethical infrastructure which guides all research, commercial development, and healthcare quality improvement. Furthermore, it introduces key concepts from subsequent parts of the course to allow students to develop their thinking around systems engineering, statistics and data visualisation, and innovation. Students will be taught by a faculty of experts from genomics, clinical medicine, informatics, statistics, business, and engineering. Masterclass sessions will use case studies to examine the impact of healthcare data.

Teaching week: 4 - 8 October 2021


Unit 2: Data Structures, Storage and Queries (40 Credits)

Unit 2 is a 40-credit unit, the largest in the programme, and delivers all of the health informatics training needed for students to be able to independently design and execute queries of raw electronic patient record data. The practical aspects of the unit will focus on the Epic system but the theoretical components will take a platform agnostic approach to covering data structures and healthcare database design. Students completing this unit will be competent in the use of the programming and scripting languages which are used globally to analyse healthcare data. Faculty will be drawn from clinical informaticians, researchers, and commercial sector software experts. Masterclasses will explore the practical aspects of patient level data extraction and analysis.

Teaching weeks:

Week 1: 10 - 14 January 2022

Week 2: 4 - 8 April 2022


Unit 3: Finding Relationships (20 Credits)

The ability to visualise results of healthcare data research and quality improvement projects is essential yet is rarely taught. Moreover, design theory and practice is uncommonly included within health informatics courses. Unit 3 is an entirely novel, innovative approach to teaching statistics and data visualisation as it applies to healthcare data and will allow the clear presentation and explanation of novel information arising from patient level data projects. The unit will use real, healthcare data datasets to develop understanding of practical statistics primarily using R. Students will also be taught design and visualisation theory and practice and tools to enhance their ability to present results from large datasets in clear, interesting, and visually appealing ways. Faculty will be drawn from statisticians, data scientists, genomic scientists, and graphic design experts.

Teaching week: tbc October 2022, Madingley Hall


Unit 4: Healthcare Systems Improvement (20 Credits)

Healthcare faces considerable challenges and the complexity of the system mean that efforts to improve it often achieve only limited benefits and frequently have unforeseen consequences. Over the past two decades, there have been numerous calls to implement a systems approach to transform healthcare; however, there has been no clear definition of what this might mean. Engineers routinely use a systems approach to address challenging problems in complex projects and this allows them to work through the implications of each change for the project as a whole. They consider the layout of the system, defining all the elements and interconnections, to ensure that the whole system performs as required. This module will apply a systems engineering approach to the process of data driven change in healthcare environments allowing students to understand and measure the consequences of any change introduced due to analysis of complex healthcare datasets. This unit will enable students to understand healthcare systems before making data driven changes. This will allow students to become experts in balancing the differing needs of users, assessing risk, and then implementing change and assessing effectiveness of system change within hospitals, pharmaceutical companies, and health research charities.

Teaching week: tbc Jan 2023, Madingley Hall


Unit 5: Medical Technology Innovation and Commercialization

In Unit 5, we will look at a range of skills required for innovation. Firstly, we will examine the difference between “entrepreneurial” and “intrapreneurial” opportunities and the paths entrepreneurs and intrapreneurs need to walk. Secondly, we will consider the range of business models currently fashionable and interesting in the medtech data space, and how this range of business models may evolve over time. Finally, we will investigate the question of medtech innovation strategy—how medium and large players in the medtech space manage their innovation portfolios and the implications for individual innovators. By the end of the unit, students should have a good grasp of the choices in front of them in terms of commercialisation, and the critical success factors for successful innovation

Teaching week: tbc April 2023, Madingley Hall

Unit : Research Dissertation (60 credits)

The research dissertation is completed during the second year of the course.


Important note: Please be aware that the teaching dates for this course are currently provisional. Whilst we do our utmost to keep to the dates and venues detailed above, these may be subject to change.

Venues for Teaching Weeks

Madingley Hall

Cambridge Biomedical Campus

The Wellcome Genome Campus



Course dates

01 Oct 2021 to 31 Jul 2023

Course duration

2 years. Part-time

Apply by

20 May 2021

Course fee

Home: £15,456
Overseas: £28,356

Course director

Academic director


Virtual Classroom
(via Zoom or equivalent)

Qualifications / Credits

180 credits at Master of Studies

Course code