This unit introduces the topic of linked health data analysis. It will usually run in late June and mid November. The topic is very specialised and will not be relevant to most MPH students. The modular structure of the unit provides students with a theoretical grounding in the classroom on each topic, followed by hands-on practical exercises in the computing lab using de-identified linked NSW data files. The computing component assumes a basic familiarity with SAS computing syntax and methods of basic statistical analysis of fixed-format data files. Contents include: an overview of the theory of data linkage methods and features of comprehensive data linkage systems, sufficient to know the sources and limitations of linked health data sets; design of linked data studies using epidemiological principles; construction of numerators and denominators used for the analysis of disease trends and health care utilisation and outcomes; assessment of the accuracy and reliability of data sources; data linkage checking and quality assurance of the study process; basic statistical analyses of linked longitudinal health data; manipulation of large linked data files; writing syntax to prepare linked data files for analysis, derive exposure and outcome variables, relate numerators and denominators and produce results from statistical procedures at an introductory to intermediate level. The main assignment involves the analysis of NSW linked data, which can be completed only in the Sydney School of Public Health Computer Lab, and is due 10 days after the end of the unit.
block/intensive mode 5 days 9am-5pm
Reflective journal (30%) and 1x data analysis assignment (70%)
Notes will be distributed in class.
For data privacy and security reasons, the analysis required to complete the major assignment can only be performed on the computers in the Sydney School of Public Health Computer Lab. The computer lab is made available to students 24/7 for ten days after the end of the unit for the purpose of completing this assessment task.
Basic familiarity with SAS computing syntax and methods of basic statistical analysis of fixed-format data files
(PUBH5010 or BSTA5011 or CEPI5100) and (PUBH5211 or PUBH5217 or BSTA5004)