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- Articles and reports: 11-522-X201300014268Description:
Information collection is critical for chronic-disease surveillance to measure the scope of diseases, assess the use of services, identify at-risk groups and track the course of diseases and risk factors over time with the goal of planning and implementing public-health programs for disease prevention. It is in this context that the Quebec Integrated Chronic Disease Surveillance System (QICDSS) was established. The QICDSS is a database created by linking administrative files covering the period from 1996 to 2013. It is an attractive alternative to survey data, since it covers the entire population, is not affected by recall bias and can track the population over time and space. In this presentation, we describe the relevance of using administrative data as an alternative to survey data, the methods selected to build the population cohort by linking various sources of raw data, and the processing applied to minimize bias. We will also discuss the advantages and limitations associated with the analysis of administrative files.
Release date: 2014-10-31 - Articles and reports: 91F0015M1997003Geography: Canada, Province or territoryDescription:
For historical reasons, the best known life tables and those most often used are period tables. They are built using death rates by age for a short period of observation (often a single year) and have as their purpose to represent the status of mortality for this period. The survivors and deaths appearing in their columns are in a way abstractions rather than reality. It is thus erroneous to believe that the life table for a given year (for example, 1995) serves in any way whatever to predict the rate at which those born that year will pass away and, hence, of the average length of the life that they have just begun. With rare exceptions, the average number of years lived by individuals has always been longer than the life expectancy found in the life table constructed for the year of their birth. This is due to the fact that period tables are established using the risks of death by age prevailing in that year. But the ceaseless battle against death reduces these risks year after year for these ages and, by growing older, people benefit from these successive gains.
To reconstitute (or foresee) the rate at which the members of a cohort have (or will) really pass away, it is necessary to deploy very long series of death rates by age and to possess reliable indicators of missing data, and then to adjust them to establish the actual experience of the persons in a cohort. Built in exactly the same way as period tables, these tables are naturally called cohort tables, but comparing observations of their parameters yields conclusions of a different kind.
Release date: 1997-10-01
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Articles and reports (2)
Articles and reports (2) ((2 results))
- Articles and reports: 11-522-X201300014268Description:
Information collection is critical for chronic-disease surveillance to measure the scope of diseases, assess the use of services, identify at-risk groups and track the course of diseases and risk factors over time with the goal of planning and implementing public-health programs for disease prevention. It is in this context that the Quebec Integrated Chronic Disease Surveillance System (QICDSS) was established. The QICDSS is a database created by linking administrative files covering the period from 1996 to 2013. It is an attractive alternative to survey data, since it covers the entire population, is not affected by recall bias and can track the population over time and space. In this presentation, we describe the relevance of using administrative data as an alternative to survey data, the methods selected to build the population cohort by linking various sources of raw data, and the processing applied to minimize bias. We will also discuss the advantages and limitations associated with the analysis of administrative files.
Release date: 2014-10-31 - Articles and reports: 91F0015M1997003Geography: Canada, Province or territoryDescription:
For historical reasons, the best known life tables and those most often used are period tables. They are built using death rates by age for a short period of observation (often a single year) and have as their purpose to represent the status of mortality for this period. The survivors and deaths appearing in their columns are in a way abstractions rather than reality. It is thus erroneous to believe that the life table for a given year (for example, 1995) serves in any way whatever to predict the rate at which those born that year will pass away and, hence, of the average length of the life that they have just begun. With rare exceptions, the average number of years lived by individuals has always been longer than the life expectancy found in the life table constructed for the year of their birth. This is due to the fact that period tables are established using the risks of death by age prevailing in that year. But the ceaseless battle against death reduces these risks year after year for these ages and, by growing older, people benefit from these successive gains.
To reconstitute (or foresee) the rate at which the members of a cohort have (or will) really pass away, it is necessary to deploy very long series of death rates by age and to possess reliable indicators of missing data, and then to adjust them to establish the actual experience of the persons in a cohort. Built in exactly the same way as period tables, these tables are naturally called cohort tables, but comparing observations of their parameters yields conclusions of a different kind.
Release date: 1997-10-01
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