The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance
Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageou...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Swansea University
2018-10-01
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| Series: | International Journal of Population Data Science |
| Subjects: | |
| Online Access: | https://ijpds.org/article/view/433 |
| _version_ | 1797428041689858048 |
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| author | Lisa Lix James Ayles Sharon Bartholomew Charmaine Cooke Joellyn Ellison Valerie Emond Naomi Hamm Heather Hannah Sonia Jean Shannon LeBlanc J. Michael Paterson Catherine Pelletier Karen Phillips Rolf Puchtinger Kim Reimer Cynthia Robitaille Mark Smith Lawrence Svenson Karen Tu Linda VanTil Sean Waits Louise Pelletier |
| author_facet | Lisa Lix James Ayles Sharon Bartholomew Charmaine Cooke Joellyn Ellison Valerie Emond Naomi Hamm Heather Hannah Sonia Jean Shannon LeBlanc J. Michael Paterson Catherine Pelletier Karen Phillips Rolf Puchtinger Kim Reimer Cynthia Robitaille Mark Smith Lawrence Svenson Karen Tu Linda VanTil Sean Waits Louise Pelletier |
| author_sort | Lisa Lix |
| collection | DOAJ |
| description | Chronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities. |
| first_indexed | 2024-03-09T08:52:21Z |
| format | Article |
| id | doaj.art-a6b8b233bb384840b4531acfb6bc0fda |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T08:52:21Z |
| publishDate | 2018-10-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-a6b8b233bb384840b4531acfb6bc0fda2023-12-02T13:59:36ZengSwansea UniversityInternational Journal of Population Data Science2399-49082018-10-013310.23889/ijpds.v3i3.433The Canadian Chronic Disease Surveillance System: A model for collaborative surveillanceLisa Lix0James Ayles1Sharon Bartholomew2Charmaine Cooke3Joellyn Ellison4Valerie Emond5Naomi Hamm6Heather Hannah7Sonia Jean8Shannon LeBlanc9J. Michael Paterson10Catherine Pelletier11Karen Phillips12Rolf Puchtinger13Kim Reimer14Cynthia Robitaille15Mark Smith16Lawrence Svenson17Karen Tu18Linda VanTil19Sean Waits20Louise Pelletier21University of ManitobaNew Brunswick Department of HealthPublic Health Agency of Canada, OttawaInvestment and Decision Support, Nova Scotia Department of Health and WellnessPublic Health Agency of CanadaInstitut national de santé publique du QuébecUniversity of ManitobaDepartment of Health & Social Services, Government of the Northwest TerritoriesInstitut national de santé publique du QuébecDepartment of Health & Social Services, Government of the Northwest TerritoriesInstitute for Clinical Evaluative SciencesCatherine Pelletier, Public Health Agency of Canada, OttawaPrince Edward Island Department of Health and Wellness, Chief Public Health OfficeGovernment of SaskatchewanOffice of the Provincial Health Officer, BC Ministry of HealthPublic Health Agency of Canada, OttawaManitoba Centre for Health PolicyAnalytics and Performance Reporting, Alberta Health; Division of Preventive Medicine, University of Alberta; School of Public Health, University of Alberta; Department of Community Health Sciences, University of CalgaryUniversity of TorontoVeterans Affairs CanadaDepartment of Health, Government of NunavutPublic Health Agency of CanadaChronic diseases have a major impact on populations and healthcare systems worldwide. Administrative health data are an ideal resource for chronic disease surveillance because they are population-based and routinely collected. For multi-jurisdictional surveillance, a distributed model is advantageous because it does not require individual-level data to be shared across jurisdictional boundaries. Our objective is to describe the process, structure, benefits, and challenges of a distributed model for chronic disease surveillance across all Canadian provinces and territories (P/Ts) using linked administrative data. The Public Health Agency of Canada (PHAC) established the Canadian Chronic Disease Surveillance System (CCDSS) in 2009 to facilitate standardized, national estimates of chronic disease prevalence, incidence, and outcomes. The CCDSS primarily relies on linked health insurance registration files, physician billing claims, and hospital discharge abstracts. Standardized case definitions and common analytic protocols are applied to the data for each P/T; aggregate data are shared with PHAC and summarized for reports and open access data initiatives. Advantages of this distributed model include: it uses the rich data resources available in all P/Ts; it supports chronic disease surveillance capacity building in all P/Ts; and changes in surveillance methodology can be easily developed by PHAC and implemented by the P/Ts. However, there are challenges: heterogeneity in administrative databases across jurisdictions and changes in data quality over time threaten the production of standardized disease estimates; a limited set of databases are common to all P/Ts, which hinders potential CCDSS expansion; and there is a need to balance comprehensive reporting with P/T disclosure requirements to protect privacy. The CCDSS distributed model for chronic disease surveillance has been successfully implemented and sustained by PHAC and its P/T partners. Many lessons have been learned about national surveillance involving jurisdictions that are heterogeneous with respect to healthcare databases, expertise and analytical capacity, population characteristics, and priorities.https://ijpds.org/article/view/433Public Health SurveillanceChronic DiseaseMulticenter Studies as TopicInformation Systems |
| spellingShingle | Lisa Lix James Ayles Sharon Bartholomew Charmaine Cooke Joellyn Ellison Valerie Emond Naomi Hamm Heather Hannah Sonia Jean Shannon LeBlanc J. Michael Paterson Catherine Pelletier Karen Phillips Rolf Puchtinger Kim Reimer Cynthia Robitaille Mark Smith Lawrence Svenson Karen Tu Linda VanTil Sean Waits Louise Pelletier The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance International Journal of Population Data Science Public Health Surveillance Chronic Disease Multicenter Studies as Topic Information Systems |
| title | The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance |
| title_full | The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance |
| title_fullStr | The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance |
| title_full_unstemmed | The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance |
| title_short | The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance |
| title_sort | canadian chronic disease surveillance system a model for collaborative surveillance |
| topic | Public Health Surveillance Chronic Disease Multicenter Studies as Topic Information Systems |
| url | https://ijpds.org/article/view/433 |
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