Canadian Chronic Disease Surveillance System (CCDSS):

On this page

• About the Canadian Chronic Disease Surveillance System (CCDSS)
• Diseases, conditions and indicators
• Data procedures
• Provincial and territorial notes
• Guidance for data users on examining the impacts of the COVID-19 pandemic on CCDSS measures

About the Canadian Chronic Disease Surveillance System (CCDSS)

The CCDSS is a collaborative network of provincial and territorial surveillance systems, supported by the Public Health Agency of Canada (PHAC). The system collects data on all residents who are eligible for provincial or territorial health insurance. It can generate national estimates and trends over time for over 20 chronic diseases and conditions, and other selected health outcomes. To identify people with chronic diseases and conditions, provincial and territorial health insurance registry records are linked using a unique personal identifier to the corresponding physician claims, hospital separation records and prescription drug records.

Key information about the CCDSS methods and case definitions is presented below. More detailed documents are available here: CCDSS summary of methods; CCDSS case definitions; CCDSS COVID-19 guidance for data users.

Diseases, conditions and indicators

Data procedures

The following data procedures are applied on the data submitted by the provinces and territories.

• Age group aggregation for age-specific estimations or rates
The data submitted by provinces and territories by five-year age groups are aggregated using the following life course age groups: 1-19, 20-34, 35-49, 50-64, 65-79 and 80+ with a few exceptions. The data by five-year age groups are reported at the national level only.
• Confidentiality
Two different procedures are used to ensure data confidentiality and avoid residual disclosure:
• Data suppression
The estimates are not reported when the corresponding unrounded counts are less than 10. Note that all provincial/territorial unrounded counts, whether suppressed or not, are part of the total counts used to produce Canadian estimates.
• Random rounding
All provincial/territorial and Canadian counts 10 or greater are randomly rounded either up or down to an adjacent multiple of 5. Canadian counts are obtained by summing provincial/territorial counts prior to random rounding. Random rounding is only used to calculate crude estimates/rates. Age-standardized estimates/rates are based on unrounded counts.
• Data quality
The estimates with a coefficient of variation exceeding 33.3% are suppressed to ensure that the provincial/territorial data are of acceptable quality.
• Rate calculation
See CCDSS summary of methods.
• Age standardization
The estimates or rates are age-standardized to the 2011 Canadian population, using unrounded counts and five-year age groups, to adjust for differences in population age structure.

Provincial and territorial notes

More disease/condition-specific notes, including provincial/territorial specifications, are included in the CCDSS case definitions documentation.

• New Brunswick: Data for 2021–2022 and 2022–2023 are not available.
• Newfoundland and Labrador: Data before 2008–2009 are excluded.
• Northwest Territories: The introduction of the Northwest Territories Electronic Medical Record (EMR) in 2016 resulted in more complete and consistent data. Data for 2016–2017 may be slightly underestimated compared to previous years due to the system transition.
  Physician claim data were incomplete for 2021–2022 and should therefore be interpreted with caution, as a slight underestimation is suspected.
  Only hospital data are included for 2022–2023. Therefore, data are only available for acute myocardial infarction, hospitalized stroke and hip fracture.
• Nunavut: Data before 2005–2006 are excluded.
• Quebec: Data cells with counts smaller than 5 were suppressed by Quebec and substituted with random numbers. As a result, age-specific incidence and mortality rates may be randomly over or under estimated.
  The modernization of the billing system for fee-for-service medical services by the Régie de l'assurance maladie du Québec (RAMQ) in 2016 has resulted in a decrease in the entry of diagnostic codes in the fee-for-service medical services file. Data for 2016–2017 and subsequent years should therefore be interpreted with caution, as a slight underestimation is suspected.
• Yukon: Data before 2010–2011 are excluded.

Note: For more information on the interpretation of the data for specific diseases/conditions please see the CCDSS case definitions documentation and the data tool notes.

Guidance for data users on examining the impacts of the COVID-19 pandemic on CCDSS measures

Factors related to the COVID-19 pandemic including differences in healthcare seeking behaviour, the availability and use of healthcare services, as well as true changes in health status, may have impacted the CCDSS measures. As such, CCDSS estimates should be used cautiously when making inferences about population health during this period (see CCDSS COVID-19 guidance for data users).