Abstract
Cancer care is complex and exists within the broader healthcare system. The CanIMPACT team sought to enhance primary cancer care capacity and improve integration between primary and cancer specialist care, focusing on breast cancer. In Canada, all medically-necessary healthcare is publicly funded but overseen at the provincial/territorial level. The CanIMPACT Administrative Health Data Group's (AHDG) role was to describe inter-sectoral care across five Canadian provinces: British Columbia, Alberta, Manitoba, Ontario and Nova Scotia. This paper describes the process used and challenges faced in creating four parallel administrative health datasets. We present the content of those datasets and population characteristics. We provide guidance for future research based on 'lessons learned'. The AHDG conducted population-based comparisons of care for breast cancer patients diagnosed from 2007-2011. We created parallel provincial datasets using knowledge from data inventories, our previous work, and ongoing bi-weekly conference calls. Common dataset creation plans (DCPs) ensured data comparability and documentation of data differences. In general, the process had to be flexible and iterative as our understanding of the data and needs of the broader team evolved. Inter-sectoral data inconsistencies that we had to address occurred due to differences in: 1) healthcare systems, 2) data sources, 3) data elements and 4) variable definitions. Our parallel provincial datasets describe the breast cancer diagnostic, treatment and survivorship phases and address ten research objectives. Breast cancer patient demographics reflect inter-provincial general population differences. Across provinces, disease characteristics are similar but underlying health status and use of healthcare services differ. Describing healthcare across Canadian jurisdictions assesses whether our provincial healthcare systems are delivering similar high quality, timely, accessible care to all of our citizens. We have provided a description of our experience in trying to achieve this goal and, for future use, we include a list of 'lessons learned' and a list of recommended steps for conducting this kind of work. KEY FINDINGS: The conduct of inter-sectoral research using linked administrative health data requires a committed team that is adequately resourced and has a set of clear, feasible objectives at the start.Guiding principles include: maximization of sectoral participation by including single-jurisdiction expertise and making the most inclusive data decisions; use of living documents that track all data decisions and careful consideration about data quality and availability differences.Inter-sectoral research requires a good understanding of the local healthcare system and other contextual issues for appropriate interpretation of observed differences.