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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 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.
 

Course delivery: We plan to deliver our postgraduate and MSt qualifications in-person in the academic year 2021-22. Please note that this will be reviewed in line with the latest public health guidance available at the time. If required, to ensure the health and safety of students, we may look to utilise alternative teaching formats and will contact students if we expect changes to the course delivery.

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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.

Content

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
 

Teaching week: Monday 4th October 2021 – Friday 8th 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.

Content

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
 

Teaching weeks:

Week 1: Monday 10th January 2022 – Friday 14th January 2022
Week 2: Monday 4th April 2022 – Friday 8th April 2022

 

 

Important note: Please be aware that these dates are 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

Documents

Unless otherwise stated, teaching and assessment for ICE courses are in English. If your first language is not English, please refer to our Information for Applicants pages for further guidance.

Course dates

01 Oct 2021 to 31 Jul 2022

Course duration

1 Year

Apply by

20 May 2021

Course fee

Home: £5,152
Overseas: £9,452

Course director

Academic director

Venue

Various locations
Cambridge
United Kingdom

Qualifications / Credits

60 credits at Master of Studies

Course code

HDPGC601