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.

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.

Course details for the Real World Epidemiology third Oxford summer school are presented alongside a photograph of the course venue, Lady Margaret Hall at the University of Oxford. The photograph shows a red brick building alongside a lawn filled with wildflowers. The course was to be held 25-29 June 2018, was organised by the Centre for Statistics in Medicine and the Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences, and was sponsored by SYNAPSE Research Management Partners and the EMIF.

25 - 29 JUNE 2018
OXFORD

Venue: LMH college

Programme

Book your place here.

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 CHARACTERIZATION: Gain an understanding of the existing sources of routinely collected data for epidemiological research, and on how to characterize whether they are fit for purpose to answer your research question/s
    2. EPIDEMIOLOGICAL STUDY DESIGN/S: Be able to discuss common and advanced study designs and their implementation using real world data.
    3. PHARMACO- AND DEVICE EPIDEMIOLOGY: Be aware of the applications of real world data in both pharmaco and device epidemiology, including drug/device utilisation, comparative effectiveness, and post-marketing safety research.
    4. PREDICTION MODELLING: Learn basic concepts on the design and evaluation of prognostic/prediction models developed using real world data.
    5. “REAL WORLD” SOLUTIONS: Understand relevant issues and learn potential solutions applied to the use of ‘real world’ epidemiology: a) data management, information governance, b) missing information and multiple imputation, and c) interaction with industry and regulators
    6. BIG DATA METHODS: Be familiar with the basics of big data methods, including a) machine learning, b) principles of common data models for multi-database studies, and c) digital epidemiology/patient data collection.

     

     

    Follow us on Twitter with hashtag #oxrwdsummerschool

    With the support of

    Synapse

    EMIF-logo

    CSM logo

     

     

     

     

    Forthcoming events

    The Oxford-Aspetar-La Trobe Young Athlete’s Hip Webinar Series

    Friday, 20 November 2020 to Sunday, 24 October 2021

    The Young Athlete’s Hip Research (YAHiR) Collaboration

    OCTRU New Starter Training *ONLINE*

    Tuesday, 19 October 2021, 10am to 11.30am @ Microsoft Teams

    Please note this session will be run online over Microsoft Teams - further details will be sent directly to attendees.

    How OPENARMS can help you with PPI - (Informal presentation & discussion) *ONLINE*

    Tuesday, 19 October 2021, 2pm to 3pm @ Microsoft Teams

    Please note this session will be run online over Microsoft Teams - future details will be sent directly to attendees.

    OCTRU New Starter Training *ONLINE*

    Tuesday, 02 November 2021, 10am to 11.30am @ Microsoft Teams

    Please note this session will be run online over Microsoft Teams - further details will be sent directly to attendees.

    OCTRU Trials Expertise Session: Trial Committees and Groups *ONLINE*

    Wednesday, 10 November 2021, 10am to 11am @ Microsoft Teams

    Please note this session will be run online over Microsoft Teams - further details will be sent directly to attendees.

    OCTRU New Starter Training *ONLINE*

    Tuesday, 16 November 2021, 10am to 11.30am @ Microsoft Teams

    Please note this session will be run online over Microsoft Teams - further details will be sent directly to attendees.