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Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage

BACKGROUND: Routinely collected infectious disease surveillance data provide a valuable means to monitor the health of populations. Notifiable disease surveillance systems in Australia have consistently reported high levels of completeness for the demographic data fields of age and sex, but low leve...

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Autores principales: Mak, Donna B, Watkins, Rochelle E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2429908/
https://www.ncbi.nlm.nih.gov/pubmed/18510777
http://dx.doi.org/10.1186/1472-6963-8-118
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author Mak, Donna B
Watkins, Rochelle E
author_facet Mak, Donna B
Watkins, Rochelle E
author_sort Mak, Donna B
collection PubMed
description BACKGROUND: Routinely collected infectious disease surveillance data provide a valuable means to monitor the health of populations. Notifiable disease surveillance systems in Australia have consistently reported high levels of completeness for the demographic data fields of age and sex, but low levels of completeness for Aboriginality data. Significant amounts of missing data associated with case notifications can introduce bias in the estimation of disease rates by population subgroups. The aim of this analysis was to evaluate the use of data linkage to improve the accuracy of estimated notification rates for sexually transmitted infections (STIs) and blood borne viruses (BBVs) in Aboriginal and non-Aboriginal groups in Western Australia. METHODS: Probabilistic methods were used to link disease notification data received in Western Australia in 2004 with core population health datasets from the established Western Australian Data Linkage System. A comparative descriptive analysis of STI and BBV notification rates according to Aboriginality was conducted based on the original and supplemented notification datasets. RESULTS: Using data linkage, the proportion of STI and BBV notifications with missing Aboriginality data was reduced by 74 per cent. Compared with excluding notifications with unknown Aboriginality data from the analysis, or apportioning notifications with unknown Aboriginality based on the proportion of cases with known Aboriginality, the rate ratios of chlamydia, syphilis and hepatitis C among Aboriginal relative to non-Aboriginal people decreased when Aboriginality data from data linkage was included. CONCLUSION: Although there is still a high incidence of STIs and BBVs in Aboriginal people, incompleteness of Aboriginality data contributes to overestimation of the risk associated with Aboriginality for these diseases. Data linkage can be effectively used to improve the accuracy of estimated disease notification rates.
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spelling pubmed-24299082008-06-14 Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage Mak, Donna B Watkins, Rochelle E BMC Health Serv Res Research Article BACKGROUND: Routinely collected infectious disease surveillance data provide a valuable means to monitor the health of populations. Notifiable disease surveillance systems in Australia have consistently reported high levels of completeness for the demographic data fields of age and sex, but low levels of completeness for Aboriginality data. Significant amounts of missing data associated with case notifications can introduce bias in the estimation of disease rates by population subgroups. The aim of this analysis was to evaluate the use of data linkage to improve the accuracy of estimated notification rates for sexually transmitted infections (STIs) and blood borne viruses (BBVs) in Aboriginal and non-Aboriginal groups in Western Australia. METHODS: Probabilistic methods were used to link disease notification data received in Western Australia in 2004 with core population health datasets from the established Western Australian Data Linkage System. A comparative descriptive analysis of STI and BBV notification rates according to Aboriginality was conducted based on the original and supplemented notification datasets. RESULTS: Using data linkage, the proportion of STI and BBV notifications with missing Aboriginality data was reduced by 74 per cent. Compared with excluding notifications with unknown Aboriginality data from the analysis, or apportioning notifications with unknown Aboriginality based on the proportion of cases with known Aboriginality, the rate ratios of chlamydia, syphilis and hepatitis C among Aboriginal relative to non-Aboriginal people decreased when Aboriginality data from data linkage was included. CONCLUSION: Although there is still a high incidence of STIs and BBVs in Aboriginal people, incompleteness of Aboriginality data contributes to overestimation of the risk associated with Aboriginality for these diseases. Data linkage can be effectively used to improve the accuracy of estimated disease notification rates. BioMed Central 2008-05-30 /pmc/articles/PMC2429908/ /pubmed/18510777 http://dx.doi.org/10.1186/1472-6963-8-118 Text en Copyright © 2008 Mak and Watkins; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mak, Donna B
Watkins, Rochelle E
Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage
title Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage
title_full Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage
title_fullStr Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage
title_full_unstemmed Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage
title_short Improving the accuracy of Aboriginal and non-Aboriginal disease notification rates using data linkage
title_sort improving the accuracy of aboriginal and non-aboriginal disease notification rates using data linkage
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2429908/
https://www.ncbi.nlm.nih.gov/pubmed/18510777
http://dx.doi.org/10.1186/1472-6963-8-118
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