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The scope of the collection is:
Data in the Causes of Death collection include demographic items, as well as Causes of Death information, which is coded according to the International Classification of Diseases (ICD). ICD is the international standard classification for epidemiological purposes and is designed to promote international comparability in the collection, processing, classification, and presentation of cause of death statistics. The classification is used to classify diseases and causes of disease or injury as recorded on many types of medical records as well as death records. The ICD has been revised periodically to incorporate changes in the medical field. The 10th revision of ICD (ICD-10) is used for the 2009 data.
Causes of death publications rely on the completion of the ABS Deaths collection, which is published within 11 months of the end of the reference period e.g. 2009 deaths were released in November 2010. Following this release, Causes of Death, Doctor Certified Deaths are published annually and released within 12 months of the reference period. For example, 2009 data are released in December 2010.
Due to the need to undertake additional intensive work on coroner certified referred deaths, a second publication containing Causes of Death data on all deaths, including those certified by a Coroner, is published annually and released within approximately 15 months of the end of the reference period.
Causes of Death, Doctor Certified deaths statistics are released with a view to ensuring that they are fit for purpose when released. To meet user requirements for timely data it is often necessary to obtain information from the administrative source before all information for the reference period is available. A balance needs to be maintained between accuracy (completeness) of data and timeliness, taking account of the different needs of users.
Non-sample errors are the main influence on accuracy in datasets such as this which are a complete census of the population rather than a sample. Non-sample error arises from inaccuracies in collecting, recording and processing the data. The most significant of these errors are: mis-reporting of data items; deficiencies in coverage; non-response to particular questions; and processing errors.
Every effort is made to minimise error by working closely with data providers, the careful design of forms, training of processing staff, and efficient data processing procedures. Quality assurance procedures are employed within ABS to reconcile and validate counts.
Use of the supporting documentation released with the statistics is important for assessing coherence within the dataset and when comparing the statistics with data from other sources. Changing business rules over time and/or across data sources can affect consistency and hence interpretability of statistical output. The Explanatory Notes in each issue contain information pertinent to this particular release which may impact on comparison over time.
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