COURSE: Introductory Analysis of Linked Health Data
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Introductory Analysis of Linked Health Data : School of Population Health - Summer School 2009 unit |
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This is an intensive five-day course 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 endeavours to fill a gap in research training opportunities to cater to these two areas of need.
Course 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 on CD-ROM in the hands-on exercises. Professor Preen is available in the computing laboratory session each afternoon and conducts an end-of-day tutorial for those who need additional assistance.
Learning objectives
The course 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
This is an intensive five-day six-point unit and prerequisites/recommendations apply.
Please visit our website for further information including enrolment details.
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