Providing data analytic services for national knowledge users in a federated system: learnings from two Canadian use cases

Objective and ApproachCanada’s federated health data system along with access pathways geared toward academic research, pose challenges for knowledge Users (KUs) requiring timely, pan-Canadian evidence to inform decisions. To understand challenges and explore solutions, we conducted two use cases for a pan-Canadian health technology assessment organization and a federal agency, using health administrative data at one federal and six provincial data centres. The population-based cohort studies described socio-demographics, comorbidities, treatment patterns, service utilization and costs. One focused on spinal muscular atrophy, a rare disease and the other on dementia, a complex chronic disease. ResultsAdministrative challenges included aligning varied ethical review and data access policies/procedures including requiring local and/or academic principal investigators and differing definitions of “research” vs. planning, evaluation, and monitoring. Data-related challenges included differences in structure, timeliness, and completeness across regions resulting in difficulty aligning constructs such as incident cases and episodes of care. Privacy requirements prohibited pooling jurisdictional estimates resulting in “small cells” that couldn’t be shared with KUs. ConclusionsWe provided analytic outputs from multiple regions, albeit with some differences and gaps, increasing knowledge around both diseases while developing capacity for combined analyses and gaining insight into national possibilities for data access. ImplicationsAs decision makers must rely on best available information, some data is better than none. However, to improve data-analytic services for Pan-Canadian KUs, next steps will include improving data harmonization, expanding data assets and filling data gaps, implementing common data models, and exploring options for federated and/or pooled analyses.

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Publication Details

Journal
International Journal for Population Data Science
Published
2024-09-10
DOI
https://doi.org/10.23889/ijpds.v9i5.2890
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
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article

Providing data analytic services for national knowledge users in a federated system: learnings from two Canadian use cases

Lisa Flaten, Raquel Duchen, Jeffrey A. Bakal, Natalie Troke et al.
International Journal for Population Data Science
Data Quality and Management
article

Providing data analytic services for national knowledge users in a federated system: learnings from two Canadian use cases

Lisa Flaten, Raquel Duchen, Jeffrey A. Bakal, Natalie Troke, Chandy Somayaji, Yan Wang, Jodi M. Gatley, Erik Youngson, Nathan Nickel, Zoe Hsu, Sandra Magalhães, Refik Saskin, Luke Mondor, Xueyi Chen, Charles Burchill, Daniel J. Dutton, John Knight, Lihui Liu, Andrew Goosen, Ted McDonald, Simon Youssef, C. B. M. Warren, Sonya Bowen, Sarah Magee, L. Y. L. Shen
article en

Abstract

Objective and ApproachCanada’s federated health data system along with access pathways geared toward academic research, pose challenges for knowledge Users (KUs) requiring timely, pan-Canadian evidence to inform decisions. To understand challenges and explore solutions, we conducted two use cases for a pan-Canadian health technology assessment organization and a federal agency, using health administrative data at one federal and six provincial data centres. The population-based cohort studies described socio-demographics, comorbidities, treatment patterns, service utilization and costs. One focused on spinal muscular atrophy, a rare disease and the other on dementia, a complex chronic disease. ResultsAdministrative challenges included aligning varied ethical review and data access policies/procedures including requiring local and/or academic principal investigators and differing definitions of “research” vs. planning, evaluation, and monitoring. Data-related challenges included differences in structure, timeliness, and completeness across regions resulting in difficulty aligning constructs such as incident cases and episodes of care. Privacy requirements prohibited pooling jurisdictional estimates resulting in “small cells” that couldn’t be shared with KUs. ConclusionsWe provided analytic outputs from multiple regions, albeit with some differences and gaps, increasing knowledge around both diseases while developing capacity for combined analyses and gaining insight into national possibilities for data access. ImplicationsAs decision makers must rely on best available information, some data is better than none. However, to improve data-analytic services for Pan-Canadian KUs, next steps will include improving data harmonization, expanding data assets and filling data gaps, implementing common data models, and exploring options for federated and/or pooled analyses.

International Journal for Population Data ScienceVol. 9(5)
University of New Brunswick (CA), Manitoba Health (CA), Alberta Health Services (CA), Dalhousie University (CA), Canadian Institute for Health Information (CA), Nova Scotia Health Authority (CA), Government of Newfoundland and Labrador (CA), Institute for Research and Development (LK), Newfoundland and Labrador Centre for Applied Health Research (CA), Alberta Health (CA)
Openalex Percentile: Top 82%
Data Quality and Management
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