Real World Data Epidemiology: Oxford Summer School
Monday, 19 June 2017 to Friday, 23 June 2017
Lady Margaret Hall, Oxford
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.
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
- 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
- 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.
- 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.
- PREDICTION MODELLING: Learn basic concepts on the design and evaluation of prognostic/prediction models developed using real world data.
- 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.
- "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.