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EVENT: Introductory Analysis of Linked Health Data

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Today's date is Friday, October 23, 2020
Introductory Analysis of Linked Health Data : Summer School - 5 day intensive unit Other events...
This is an intensive five-day unit on the theory and practice of analysis of large sets of linked administrative health data at an introductory to intermediate level.

Rapid growth in data linkage projects has led to a shortfall in analyst skills. Some researchers understand epidemiological principles, but are unfamiliar with the specialised computing skills needed to analyse linked data files. Others have a strong grasp of computing concepts, but lack an adequate theoretical base to design high quality applications to answer research questions. This unit endeavours to fill a gap in research training opportunities to cater to these two areas of need.

Unit outline

Professor Holman provides a theoretical grounding in the classroom on each topic, followed by a training session on the corresponding computing solutions. Students use fictitious but realistic linked data files in the hands-on exercises. A lecturer will be available in the computing laboratory session each afternoon and conducts an end-of-day tutorial for those who need additional assistance.

In preparation for the teaching week you will be sent pre-reading on 30 November 2013.

Learning objectives

The unit acquaints health researchers, clinical practitioners and managers with the theory and skills needed to analyse linked health data at the introductory to intermediate level. Upon completion the participant will:

- possess an overview of the theory of data linkage methods and features of comprehensive data linkage systems, sufficient to understand the sources and limitations of linked health data sets

- understand the principles of epidemiologic measurement and research methods for the conceptualisation and construction of numerators and denominators used in the analysis of disease trends and health care utilisation and outcomes

- understand sources of error in epidemiologic measurement, the difference between confounding and effect modification, and use of regression models in risk adjustment in health services research

- be able to perform statistical analyses on linked longitudinal health data

- be able to conceptualise and perform the manipulation of large linked data files

- be able to write syntax to prepare linked data files for analysis, derive exposure and outcome variables, relate numerators and denominators and produce results from statistical procedures

Unit prerequisites

Basic familiarity with computing syntax used in programs such as SPSS, SAS or Stata and methods of basic statistical analysis of fixed-format data files.

There are no formal prerequisites in epidemiology for the course. However, it is recommend that participants who have not previously completed an introductory course in epidemiology, familiarise themselves with the basic principles and terms used in that discipline. A working knowledge of statistical concepts, including regression models, used in data analysis in the medical and social sciences is assumed.

This unit is available for postgraduate students as a 6 point unit. It is also available for professional development. Fees apply, please visit our website for details.
Speaker(s) Winthrop Professor D'Arcy Holman
Location Clifton Street Building, Nedlands Campus
Contact Fiona Maley <[email protected]> : 6488 1299
URL https://www.sph.uwa.edu.au/courses/winter-spring-summer-school/health-data
Start Mon, 09 Dec 2013 08:30
End Fri, 13 Dec 2013 16:30
RSVP RSVP is required.
Submitted by Fiona Maley <[email protected]>
Last Updated Mon, 24 Feb 2014 11:05
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