| Summary: | The aim of this thesis is to demonstrate how the use of administrative health data (AHD) has evolved over time to be a valuable resource for quantifying disease burden. AHD are defined as data routinely collected for the purposes of payment, monitoring, priority setting, and evaluation of the provision of health services. While the primary purpose of AHD is not research, and researchers typically do not have a direct role in their collection, they represent a rich source of data for secondary analyses. The thesis presents and critiques 12 peer-reviewed publications to demonstrate how the use of AHD has evolved for better understanding the burden of disease. Each publication shows a natural evolution in thinking, and sophistication of methods that help to illustrate how secondary data can be used to augment primary data collection methods. The development of evidence using different methods, particularly when there are consistent results, works to strengthen our understanding of any given health issue. The thesis defines AHD, as well as its strengths and limitations, and how these data can be considered ‘big data’. Next, historical developments on secondary use and AHD are provided starting with the work of John Graunt, and ending with the present author. The value of AHD is explored critically through the following themes: role of mortality and hospitalisation data; development of algorithms for improving the accuracy of AHD for determining the presence of disease (case definition algorithms); strength and value of longitudinal designs; identification of rare health events; assessing the burden of co-morbidities; assessing health outcomes; and finally how AHD can support policy development. Future directions for research are highlighted, as well as how AHD can be used to inform policy, resource allocation, and practice.
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