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

Abstract

Abstract: 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 populationsubgroups. The aim of this analysis was to evaluate the use of data linkage to improve the accuracyof 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 WesternAustralia in 2004 with core population health datasets from the established Western AustralianData Linkage System. A comparative descriptive analysis of STI and BBV notification rates accordingto Aboriginality was conducted based on the original and supplemented notification datasets.Results: Using data linkage, the proportion of STI and BBV notifications with missing Aboriginalitydata was reduced by 74 per cent. Compared with excluding notifications with unknownAboriginality data from the analysis, or apportioning notifications with unknown Aboriginality basedon the proportion of cases with known Aboriginality, the rate ratios of chlamydia, syphilis andhepatitis C among Aboriginal relative to non-Aboriginal people decreased when Aboriginality datafrom 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.