The CanPath-HDRN Canada Collaboration: Enabling Multi-jurisdictional Research in Canada
ObjectiveTo highlight the partnership between the Canadian Partnership for Tomorrow’s Health (CanPath) and Health Data Research Network (HDRN Canada), which enables researchers to link CanPath’s health and lifestyle survey data to health records and related data across multiple regions. BackgroundCanPath is a population health study of over 350,000 Canadians from seven regional cohorts across all ten provinces, making it one of the world's largest population cohorts. HDRN Canada is a network of member organizations, including provincial, territorial, and pan-Canadian data centres. ApproachThis partnership leveraged collective expertise and resources to facilitate the linkage of CanPath’s harmonized data to multi-regional health and health-related administrative data held at HDRN Canada’ s data centres. Researchers can access these data for multi-regional projects through HDRN Canada’s Data Access Support Hub, which provides a single access portal. ResultsResearchers were able to successfully link CanPath’s survey data to provincial administrative health data. The collaboration’s streamlined process for data access enhances efficiency and facilitates pan-Canadian population health research. ConclusionThis collaboration demonstrates the feasibility and value of linking population health datasets while demonstrating the challenges and opportunities associated with accessing national administrative health data within a federated health data system. ImplicationsThe partnership between CanPath and HDRN Canada has significant implications for advancing population health research in Canada. By providing researchers with access to linked data from diverse sources, the partnership enables comprehensive investigations into health determinants, disease patterns, and clinical outcomes. This enhances the scope and depth of population health research in Canada, thereby leading to a better understanding of the most pressing health challenges.
Authors
- Lindsay Stewart
- Philip Awadalla (ORCID: https://orcid.org/0000-0001-9946-6393)
- Jennifer E. Vena (ORCID: https://orcid.org/0000-0002-6313-1126)
- Robyn Kydd
- Jennifer Brooks
- Parveen Bhatti (ORCID: https://orcid.org/0000-0003-1709-1781)
- Victoria A. Kirsh (ORCID: https://orcid.org/0000-0003-2422-2225)
- Jodi M. Gatley (ORCID: https://orcid.org/0000-0001-8366-8214)
- Shandra Harman
- Vikki Ho (ORCID: https://orcid.org/0000-0002-0724-7917)
- Simon Gravel (ORCID: https://orcid.org/0000-0002-9183-964X)
- Robin Urquhart (ORCID: https://orcid.org/0000-0001-8864-5716)
- Stefana Jovanovska
- Donna Turner
- Guillaume Lettre (ORCID: https://orcid.org/0000-0002-7740-3399)
- Anne Hayes (ORCID: https://orcid.org/0000-0002-2055-8269)
- Mahmoud Azimaee (ORCID: https://orcid.org/0000-0002-6704-5129)
- Katelyn Frizzell
- Carmen La
- Magda Nunes De Melo
- Mary-Ann Standing
- Eric Youngson
- Sheraz Cheema
- Nouar ElKhair
- Tim Choi
- Kendra Lester
- J.M. Hunt
- Megan Fleming
- Noah D. Frank
- Lindsey Gilbert
- Riaz Alvi
- Jason Hicks
Publication Details
- Journal
- International Journal for Population Data Science
- Published
- 2024-09-10
- DOI
- https://doi.org/10.23889/ijpds.v9i5.2813
- Primary Topic
- Health Systems, Economic Evaluations, Quality of Life
- Type
- article
- Field-Weighted Citation Impact
- 0.00