Fundamentals of Applied Health Data Science for Precision Medicine Research module (GM51084)

Gain the core practical skills required to access and effectively analyse real-world clinical data

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You’ll develop clinical data management skills including data processing, statistical assessment and description techniques underpinned by knowledge of data governance principles in the context of combining health data with genomic data. You’ll work with genomic data and be introduced to R statistical software and explore principles of the ethics, legalities, quality assurance, and security surrounding the use of health data.

This module will present an overview of population health and research data analytics. This refers to the process of identifying and evaluating electronic health records with the aim of reporting characteristics within defined groups of individuals (e.g. people with diabetes).

The module will give you a clear understanding of real-world processes for effectively using clinical data for research. It will provide hands-on experience with governance processes, research analysis environments and methodologies, statistical analysis tools, and genomic data.

What you will learn

In this module, you will:

  • learn data governance principles, including the ethics of data governance and security surrounding the use of health data
  • develop clinical data management skills, including data processing, statistical assessment, descriptive analysis techniques, and combining health data with genomic data
  • be introduced to R statistical software
  • review large databases using SQL Server
  • access a real-world Trusted Research Environment during practical activities

By the end of this module, you will be able to:

  • critically appraise approaches to the governance and secure processing of healthcare data
  • differentiate the sources of healthcare data and propose the logistical challenges of making use of such data for biomedical research
  • effectively clean and describe healthcare data and link it with genomic data using R statistical software
  • undertake an exemplar genome wide association study and build and use a genetic risk score using conventional bioinformatics tools
  • assess the need for successful teamwork across multiple skill and knowledge domains in Precision Medicine research
  • explain the basic array of data processing tools and techniques used in Precision Medicine research

Assignments / assessment

  • written assignment (20%)
  • written report 1,500 words (40%)
  • closed book examination (40%)

Teaching methods / timetable

  • lectures
    • lecture slides will be available to students
    • some lectures will be recorded for future review
  • practical workshops
  • tutorials
  • directed independent study

The module is taught face-to-face with some online learning activities.

A particular attribute of the module is learning through experience. This will involve practical, hands-on work with real-world healthcare data. This will allow you to apply your new found knowledge of Precision Medicine by engaging with these data in genuine, practical scenarios. 


This module is available on following courses: