Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.
Real world data summer school 2017 1

We explore the existing sources of real world data, discuss common types of study and designs for its use, and look in-depth into the issues and solutions linked to big health data usage.

19 - 23 JUNE 2017
OXFORD 

 

Venue: LMH college

Pre-Programme

The course is now fully booked. If you would like to receive information about the next course, please email the course administrator at paloma.odogherty@ndorms.ox.ac.uk

AUDIENCE

Pharmacists, clinicians, academics (including statisticians, epidemiologists, and related MSc/PhD students); Industry (pharmacy or device) or Regulatory staff with an interest in the use of routinely collected data for research. 

LEARNING GOALS

  1. DATA DISCOVERY AND VALIDATION STUDIES: Gain an understanding of the existing sources of routinely collected data for epidemiological research, and on how to perform validation studies to assess their quality
  2. EPIDEMIOLOGICAL STUDY DESIGN/S: Be able to discuss common types of study for the use of such data, including cohort, case-control, and case only studies.
  3. PHARMACO- AND DEVICE EPIDEMIOLOGY: Be aware of the applications of real world data in both pharmaco and device epidemiological studies, including drug/device utilisation and safety research.
  4. PREDICTION MODELLING: Learn basic concepts on the design and evaluation of prognostic/prediction models developed using real world data.
  5. BIG DATA METHODS: Be familiar with the basics of big data methods (including machine learning), and examples of their potential applications in ‘real world’ epidemiology.
  6. "REAL WORLD” SOLUTIONS: Understand relevant issues and learn potential solutions applied to the use of ‘real world’ data: a) data management and information governance, b) interaction with industry and regulators, c) stats/methods: missing information, bias, confounding, misclassification.

 

Follow us on Twitter with hashtag #oxrwdsummerschool


With the support ofSynapse

EMIF-logo