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Institute of Continuing Education (ICE)


This course has been cancelled. Please register your interest by using the ‘Ask a Question’ function and we will notify you when this course, or a similar course, is next run.

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 Postgraduate Certificate has been designed to provide an introduction to the research skills, governance and innovation needed to work successfully with healthcare data. In addition students will be equipped with the skills necessary to understand how healthcare data relates to populations, health conditions and clinical outcomes and learn how to work with healthcare data in an effective manner. The course is delivered through a combination of in person teaching in Cambridge and online content through a Virtual Learning Environment. All students will need to attend the teaching sessions held in Cambridge, and these cannot be attended remotely.



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)

Teaching week: Monday 7th – Friday 11th October 2024 (tbc)

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.


Indicative content for this module includes:
•    An introduction to healthcare data and its importance
•    Overview of local, national and global initiatives for healthcare data application
•    Principles of good data management / stewardship
•    Open vs closed data and the FAIR principles
•    Governance of healthcare data use
•    Principles of quality healthcare data research
•    Basic data manipulation (data visualisation)
•    An introduction to systems engineering approaches using healthcare data
•    An introduction to innovation and commercialization

Learning Outcomes
By the end of the units the participants should be able to:
•    Describe the breadth of healthcare data available and the potential for its use in clinical innovation 
•    Discuss appropriate data management requirements for a healthcare data set, including storage and access
•    Apply appropriate ethical and governance guidelines in the acquisition and use of healthcare data
•    Plan a basic piece of research on a healthcare dataset
•    Outline how the results of a piece of research can be communicated to appropriate groups to support implementation of change
•    Know the basic principles of the systems engineering approach and routes to innovation and commercialisation

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

Teaching weeks:

Week 1: Monday 13th – Friday 17th January 2025
Week 2: Monday 14th – Friday 18th  April 2025

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.


Critical awareness of the wider implications, relationships, and impact of healthcare data (25%)
•    How are populations and diseases reflected in datasets?
•    Where and how does healthcare data impact policy and infrastructure development?
•    How do hospitals and other organisations use data?
•    What opportunities does healthcare data offer hospitals and other organisations?

Data and database structures, storage, quality, access and governance (25%)
•    How is data stored, in what ways do databases differ?
•    How do trial registries, clinical research, and audit databases differ from electronic patient records?
•    Where is data stored, particularly in the UK health and research sectors?
•    What is the appropriate governance surrounding access for healthcare data?
•    Documentation standards, data quality and the implications for interoperability and secondary use.

Data-extraction and curation (50%)
•    Converting research and quality improvement questions into database queries
•    Writing and executing SQL database queries and related quality control
•    How is a dataset ideally constructed for subsequent analysis?

Learning outcomes

By the end of this module participants should be able to:
•    Describe the various types / properties / structure / usage of multiple types of patient-level and aggregated data used in the field of healthcare
•    Describe the framework within which datasets are described, mandated / notified, implemented and reported in the NHS.
•    Describe the UK governance framework relating to the use of personal data in healthcare
•    Describe the differences between terminologies and classifications and their usage
•    Describe an approach to data stewardship and proper curation in the management of healthcare data
•    Describe the elements which underpin meaningful and safe interoperability in the context of personal healthcare data
•    Evaluate a request for data, demonstrating an understanding of all of the factors / aspects to be considered including governance, structure / quality and extraction methodology
•    Formulate a high-level approach to a database query from a specific data (research / audit etc.) question
•    Write appropriate SQL queries and extract data from a normalised database
•    Demonstrate the ability to transform / curate extracted data in preparation for more detailed analysis

Venues for Teaching Weeks


Course dates

01 Oct 2024 to 30 Jun 2025

Course duration

9 Months

Apply by

31 May 2024

Course fee

Home: £5,950
Overseas: £10,420

Course director

Academic director

Academic Directors, Course Directors and Tutors are subject to change, when necessary.


Various locations
United Kingdom

Qualifications / Credits

60 credits at Master of Studies

Course code