Advanced Methods for the Analysis of Population-wide Administrative Health Data
Population-wide administrative health data contains information that is routinely collected during encounters with the healthcare system and provides a rich source of information for researchers. These large databases are particularly valuable for a wide range of epidemiological and longitudinal studies incorporating individual-level data.
Interests may include prevalence and incidence of diseases, tracking the health of specific population sub groups over time or monitoring trends in utilization of health services and related resources. From a wider research lens, administrative health data also provide opportunities to study health policy, social problems and societal issues not commonly available through social surveys.
The trade off to its high research value is that administrative health data is not collected for the purposes of research and therefore the data are generally more ‘messy’ and complex than traditional social science data sets. As a result, researchers require advanced methodologies to effectively analyse administrative data and apply this knowledge to foster positive health outcomes within our society.
Focus of the webinars
This webinar series aims to address this need by hosting presentations led by a variety of researchers from across Canada with expertise in specific methodologies used to advance research in the field of Population Health. Topics have been chosen based on a recent education and training survey. As we roll out the series, we welcome your feedback and related suggestions for future presentations.
These webinars will benefit researchers, analysts and health professionals interested in learning more about advanced methods used in the analysis of population-wide administrative health data.
Quantile Regression - An Introduction
January 27 2021
Ruth Croxford, ICES
Interrupted Time Series and its applications
December 2 2020
Dr Rahim Moineddin, University of Toronto, Canada
Estimating the Clinical & Economic Burden Using Prediction & Simulation Modeling: COPD in Ontario
August 19 2020
Dr. Petros Pechlivanoglou, University of Toronto, Canada
Intro to Multistate Modeling Approaches for Analyzing Population-wide Health Administrative Data
June 3 2020
Dr. Rinku Sutradhar, University of Toronto, Canada
Methods for Modelling Non-Linear Relationships
May 20 2020
Ruth Croxford, ICES
Introduction to Causal Inference: Propensity Score Analysis in Healthcare Data
May 14 2020
Dr. M. Ehsan Karim, Centre for Health Evaluation and Outcome Sciences (CHÉOS), St. Paul's Hospital
COVID-19 Canada Open Data and Visualization with R Shiny
April 28 2020
Isha Berry & Jean-Paul R. Soucy, Dalla Lana School of Public Health at the University of Toronto
Measurement in Administrative Health Data: Case Definitions, Algorithms, and Validation Studies
April 15 2020
Taylor McLinden, BC Centre for Excellence in HIV/AIDS (BC-CfE), Vancouver