Report from the Canadian Chronic Disease Surveillance System: Hypertension in Canada, 2010

2010 ◽  
Keyword(s):  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Disease Surveillance System

scholarly journals LO021: Use of health services among non-institutionalized frail elderly with fracture: preliminary results

CJEM ◽  
2016 ◽  
Vol 18 (S1) ◽  
pp. S37-S37
Author(s):  
V. Fillion ◽  
S. Jean ◽  
M. Sirois ◽  
P. Gamache
Keyword(s):  
Chronic Disease ◽  
General Practitioner ◽  
Health Services ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Administrative Databases ◽  
Assessment Index ◽  
Preliminary Results ◽  
Disease Surveillance System ◽  
Use Of Health Services

Introduction: Frail older adults experience an increased risk of a number of adverse health outcomes such as comorbidity, disability, dependency, institutionalization, falls, fractures, hospitalization, and mortality. Identification of frail adults is important. The objective of this study is to examine the association between frailty and use of health services (emergency, general practitioner, hospitalization) prior to and following a visit for a fracture in non-institutionalized seniors. Methods: This study is a population-based cohort build from the Quebec Integrated Chronic Disease Surveillance System, an innovative chronic disease surveillance system linking five health care administrative databases. Algorithms using data from this system are accurate and reliable for identifying fractures. The sample includes 179,734 seniors ≥ 65 years old, non-institutionalized in the year before the fracture. Their frailty status was measured using the elderly risk assessment index. Poisson regression models were used to compare use of health services (emergency, general practitioner, hospitalization) 1 year before and 1 year after a visit for a fracture (adjusting for age, sex, comorbidities, social deprivation, material deprivation and site of fracture). Results: Overall, preliminary results show that the use of health services increased significantly in the year following the fracture in frail non-institutionalized elderly vs the non-frail one (p < 0.05). Conclusion: This study suggests that frail seniors with a fracture require more health services after their incident fracture. Furthermore, using a frailty assessment index in health administrative databases can help identify seniors that are at high risk of needing more health services and, therefore, improve their care.

scholarly journals The Canadian Chronic Disease Surveillance System: A model for collaborative surveillance

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Lisa Lix ◽  
James Ayles ◽  
Sharon Bartholomew ◽  
Charmaine Cooke ◽  
Joellyn Ellison ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Health Agency ◽  
Population Based ◽  
Population Characteristics ◽  
Administrative Databases ◽  
Distributed Model ◽  
Case Definitions ◽  
Disease Surveillance System

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.

scholarly journals The Canadian Chronic Disease Surveillance System: A Distributed Surveillance Model

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Lisa Lix ◽  
Kim Reimer
Keyword(s):  
Health Insurance ◽  
Chronic Disease ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Feasibility Studies ◽  
Mental Illnesses ◽  
Population Characteristics ◽  
Case Definitions ◽  
Disease Surveillance System ◽  
Disease Case

ObjectiveTo describe the process, benefits, and challenges of implementinga distributed model for chronic disease surveillance across thirteenCanadian jurisdictions.IntroductionThe Public Health Agency of Canada (PHAC) established theCanadian Chronic Disease Surveillance System (CCDSS) in 2009 tofacilitate national estimates of chronic disease prevalence, incidence,and health outcomes. The CCDSS uses population-based linkedhealth administrative databases from all provinces/territories (P/Ts)and a distributed analytic protocol to produce standardized diseaseestimates.MethodsThe CCDSS is founded on deterministic linkage of threeadministrative health databases in each Canadian P/T: health insuranceregistration files, physician billing claims, and hospital dischargeabstracts. Data on all residents who are eligible for provincial orterritorial health insurance (about 97% of the Canadian population) arecaptured in the health insurance registration files. Thus, the CCDSScoverage is near-universal. Disease case definitions are developed byexpert Working Groups after literature reviews are completed andvalidation studies are undertaken. Feasibility studies are initiatedin selected P/Ts to identify challenges when implementing thedisease case definitions. Analytic code developed by PHAC is thendistributed to all P/Ts. Data quality surveys are routinely conductedto identify database characteristics that may bias disease estimatesover time or across P/Ts or affect implementation of the analytic code.The summary data produced in each P/T are approved by ScientificCommittee and Technical Committee members and then submitted toPHAC for further analysis and reporting.ResultsNational surveillance or feasibility studies are currently ongoing fordiabetes, hypertension, selected mental illnesses, chronic respiratorydiseases, heart disease, neurological conditions, musculoskeletalconditions, and stroke. The advantages of the distributed analyticprotocol are (Figure 1): (a) changes in methodology can be easilymade, and (b) technical expertise to implement the methodology is notrequired in each P/T. Challenges in the use of the distributed analyticprotocol are: (a) heterogeneity in healthcare databases across P/Tsand over time, (b) the requirement that each P/T use the minimum setof data elements common to all jurisdictions when producing diseaseestimates, and (c) balancing disclosure guidelines to ensure dataconfidentiality with comprehensive reporting. Additional challenges,which include incomplete data capture for some databases and poormeasurement validity of disease diagnosis codes for some chronicconditions, must be continually addressed to ensure the scientificrigor of the CCDSS methodology.ConclusionsThe CCDSS distributed analytic protocol offers one model fornational chronic disease surveillance that has been successfullyimplemented and sustained by PHAC and its P/T partners. Manylessons have been learned about national chronic disease surveillanceinvolving jurisdictions that are heterogeneous with respect tohealthcare databases, expertise, and population characteristics.

scholarly journals Trends in chronic disease incidence rates from the Canadian Chronic Disease Surveillance System

2019 ◽  
Vol 39 (6/7) ◽  
pp. 216-224 ◽  
Author(s):  
Naomi C. Hamm ◽  
Louise Pelletier ◽  
Joellyn Ellison ◽  
Lana Tennenhouse ◽  
Kim Reimer ◽  
...  
Keyword(s):  
Chronic Disease ◽  
Likelihood Ratio ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Disease Incidence ◽  
Incidence Rates ◽  
Population Characteristics ◽  
Linear Predictor ◽  
Disease Surveillance System ◽  
Over Time

Introduction The Public Health Agency of Canada’s Canadian Chronic Disease Surveillance System (CCDSS) produces population-based estimates of chronic disease prevalence and incidence using administrative health data. Our aim was to assess trends in incidence rates over time, trends are essential to understand changes in population risk and to inform policy development. Methods Incident cases of diagnosed asthma, chronic obstructive pulmonary disease (COPD), diabetes, hypertension, ischemic heart disease (IHD), and stroke were obtained from the CCDSS online infobase for 1999 to 2012. Trends in national and regional incidence estimates were tested using a negative binomial regression model with year as a linear predictor. Subsequently, models with year as a restricted cubic spline were used to test for departures from linearity using the likelihood ratio test. Age and sex were covariates in all models. Results Based on the models with year as a linear predictor, national incidence rates were estimated to have decreased over time for all diseases, except diabetes; regional incidence rates for most diseases and regions were also estimated to have decreased. However, likelihood ratio tests revealed statistically significant departures from a linear year effect for many diseases and regions, particularly for hypertension. Conclusion Chronic disease incidence estimates based on CCDSS data are decreasing over time, but not at a constant rate. Further investigations are needed to assess if this decrease is associated with changes in health status, data quality, or physician practices. As well, population characteristics that may influence changing incidence trends also require exploration.

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