Summer Informatics School–SISS 2017

How to use routine health data for quality improvement & research
  • Where: Austin Pearce building, Stag Hill Campus, University of Surrey, Guildford, GU2 7XH
  • Dates: 26 – 30 June 2017
  • Open to: Public, Staff, Students
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The Department of Clinical & Experimental Medicine will be hosting its fifth annual health informatics summer school from Monday 26 June to Friday 30 June This full time 5 day intensive short course is for health care professionals, researchers and analysts wanting to work with routine health data to measure quality, research and improve outcomes.

A deep understanding of health informatics is increasingly recognised as essential for those seeking to advance their careers within the health sector. Informatics is one of the fastest growing specialisms within the health sector. At its core the insight gained from the analysis of relevant, reliable and timely information enables clinicians, researchers, managers and commissioners to make informed decisions that lead to improved outcomes. Taught by highly regarded experts in the field the course will teach analytical techniques and tools on real world scenarios to generate practical insight and embed learning.

There are no entry requirements and the course is suitable and flexible enough to accommodate those with little or no statistical experience looking to find pragmatic ways of using data as well as those advanced in analytics seeking to enhance their technical skills.

The course is internationally relevant and has attracted students from Canada, the Middle East, Caribbean, and across Europe, though we use UK centric data in our case studies.


The course is intensive and primarily designed for residential students. It commences on the Monday morning and runs through to the following Friday afternoon. The course day is divided into plenary (lecture) sessions, individual computer labs; and practical sessions. Lunches, break time teas and coffees and closing dinner are provided as part of the course fee.

The course will provide an introduction to data analytics, basic statistical tests and data manipulations using R and RStudio, and the basics of epidemiology. It will also cover the nature of routine health data, the processes of data extraction, the representation of meaning, and an ontological approach to making sense of the data. It will also include an introduction to Health Economics.

Intended learning outcomes for participants will include:

By the end of this course you will be able to:

  • Find essential information to access, download and set up R for your own continued use
  • Understand how and when to use each of the four panels in the R Studio integrated development environment
  • Understand how to carry out basic data manipulations in R of simple variables, vectors, tables, data frames
  • ‘Visualise’ the data using R graphical and non graphical functions
  • Demonstrate an understanding of different data types, the differences between parametric and non parametric data, and which of the commoner statistical tests are appropriate for use with different types of data
  • Understand when to use, and how to carry out simple descriptive statistical tests, hypothesis tests, correlation and linear and logistic regression in R
  • Demonstrate an understanding of the principles of study design and sample size calculations
  • Describe the nature and origins of health care data
  • Explain the differences between structured data entries and narrative
  • Demonstrate an understanding of the varieties of clinical information found in patient records
  • Describe the factors that should be considered when extracting data from a record system
  • Understand what is meant by ‘data quality’, and the factors that impact on it
  • Explain the differences between classifications and clinical terminologies
  • Explain the differences between term based and concept based approaches
  • Understand the basics of SNOMED
  • Understand the ontological approach to identifying and handling the key concepts of a research project

Guest speakers and lecturers include:

  • Professor Simon Jones – Professor of Epidemiology and Head of Integrated Care Research at the University of Surrey; previously Chief Statistician at Dr Foster Intelligence
  • Professor Simon de Lusignan – Professor of Primary Care and Clinical Informatics at the University of Surrey; Medical Director
    of the RCGP Research and Surveillance centre; practicing GP
  • Dr John Williams – Senior Clinical Research fellow at the University of Surrey; previously Clinical Informatics adviser to HSCIC; retired GP
  • Dr Andrew McGovern – Clinical Research Fellow at the University of Surrey
  • William Hinton and Jeremy van Vlymen – Research Fellows at the University of Surrey
  • Mr Jake Jordan – Research Fellow in Health Economics at the University of Surrey


Academic/ NHS







You can book guest accommodation at the University using the link below. There is also details about the local hotels and bed and breakfasts on this webpage:

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