September to December 2021
This course examines the basics of what administrative data are:
- where they come from
- how they can be used for research
- what the data produced for research projects look like
- the skills needed to work with them
- basic statistical analysis of these data
This course also provides an overview of ethics and privacy issues related to research uses of administrative data.
- Articulate privacy issues and protections as they relate to the analysis of administrative health data for research purposes.
- Articulate a clear and "research-ready" research question appropriate to administrative health data.
- Create a data dictionary.
- Create an analytic data set—with one record per person—from administrative data.
- Navigate within and use Population Data BC's Secure Research Environment.
- Use SAS statistical software both for data management and for (relatively simple) data analysis.
- Write methodology that supports reproducibility of the analyses undertaken.
- Present findings showing policy relevance of your research.
Admission to the PSC in Population Health Data Analysis or permission of the Faculty Advisor.
Instructor: Kim Nuernberger
Kim Nuernberger is a Senior Analyst for the Canadian Institute for Health Information (CIHI). She brings to this course more than 10 years of experience as a health data analyst, much of it working with large administrative health data sets. Her experience spans a broad range of health service issues covering the life course and representing everything from contraception to the provision and delivery of appropriate long-term care services. A strong advocate of lifelong learning, Kim completed a Master of Arts degree in Sociology from the University of Victoria in 2005 and solidified her skills in health research through completion of the Professional Specialization Certificate in Population Health Data Analysis. Most recently she has been involved in a collaborative project involving researchers based at the University of Victoria and the Fraser Health Authority examining patterns and predictors of long-term care use through administrative and clinical data. This project has involved extensive use of SAS and other statistical software to link anonymized data sets and employ a wide variety of statistical techniques.