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The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research

Authors :
Lindsey Todd Dahl
Jennifer D Walker
Michael Schull
P. Alison Paprica
James Ted McDonald
Frank Gavin
Jean-Francois Ethier
Brent Diverty
Kimberlyn McGrail
Alan Katz
Juliana Wu
Source :
International Journal of Population Data Science, Vol 5, Iss 1 (2020)
Publication Year :
2020
Publisher :
Swansea University, 2020.

Abstract

Administrative health data is recognized for its value for conducting population-based research that has contributed to numerous improvements in health. In Canada, each province and territory is responsible for administering its own publicly funded health care program, which has resulted in multiple sets of administrative health data. Challenges to using these data within each of these jurisdictions have been identified, which are further amplified when the research involves more than one jurisdiction. The benefits to conducting multi-jurisdictional studies has been recognized by the Canadian Institutes of Health Research (CIHR), which issued a call in 2017 for proposals that address the challenges. The grant led to the creation of Health Data Research Network Canada (HDRN), with a vision is to establish a distributed network that facilitates and accelerates multi-jurisdictional research in Canada. HDRN received funding for seven years that will be used to support the objectives and activities of an initiative called the Strategy for Patient-Oriented Research Canadian Data Platform (SPOR-CDP). In this paper, we describe the challenges that researchers face while using, or considering using, administrative health data to conduct multi-jurisdictional research and the various ways that the SPOR-CDP will attempt to address them. Our objective is to assist other groups facing similar challenges associated with undertaking multi-jurisdictional research.

Details

Language :
English
ISSN :
23994908
Volume :
5
Issue :
1
Database :
Directory of Open Access Journals
Journal :
International Journal of Population Data Science
Publication Type :
Academic Journal
Accession number :
edsdoj.84522b138094f0fb96d6c734f55259e
Document Type :
article
Full Text :
https://doi.org/10.23889/ijpds.v5i1.1374