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.
| Original language | English |
|---|---|
| Article number | 8 |
| Journal | International Journal of Population Data Science |
| Volume | 3 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Sept 21 2018 |
Bibliographical note
Funding Information:This study was funded by the Canadian Institutes of Health Research (grant # 128272). The opinions, results and conclusions reported in this paper are those of the authors and are independent from the funder. This study is supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and information provided by Cancer Care Ontario (CCO). The opinions, results, views, and conclusions reported in this paper are those of the authors and do not necessarily reflect those of CCO. No endorsement by CCO is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI. We gratefully acknowledge CancerCare Manitoba for their on-going support and Manitoba Health for the provision of data. The results and conclusions presented are those of the authors. No official endorsement by Manitoba Health is intended or should be inferred. Nova Scotia data were provided by Health Data Nova Scotia and the Nova Scotia Department of Health and Wellness, however, the observations and opinions expressed
Funding Information:
The authors would also thank Emma Shu, Marlo Whitehead, and Yan Zhang for conducting data processing and statistical analyses. This study was funded by the Canadian Institutes of Health Research (grant # 128272). The opinions, results and conclusions reported in this paper are those of the authors and are independent from the funder. This study is supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and information provided by Cancer Care Ontario (CCO). The opinions, results, views, and conclusions reported in this paper are those of the authors and do not necessarily reflect those of CCO. No endorsement by CCO is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI. We gratefully acknowledge CancerCare Manitoba for their on-going support and Manitoba Health for the provision of data. The results and conclusions presented are those of the authors. No official endorsement by Manitoba Health is intended or should be inferred. Nova Scotia data were provided by Health Data Nova Scotia and the Nova Scotia Department of Health and Wellness, however, the observations and opinions expressed
Publisher Copyright:
November 2018 © The Authors. Open Access under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en)
ASJC Scopus Subject Areas
- Demography
- Information Systems
- Health Informatics
- Information Systems and Management
