Suchergebnisse

IntroductionThe enrolment data for Medicare, the Australian universal health insurance provider, covers almost the entire population. Medicare data are commonly used for data linkage, usually to access national medical and pharmaceutical data. However, the enrolment data also enable the identification of geographical cohorts for studies analysing exposure to environmental hazards.
Objectives and ApproachOne example of this was the ACT Asbestos Health Study examining the health risks associated with living in houses insulated with loose-fill asbestos in the Australian Capital Territory. The Medicare Enrolment File contains the personal details and addresses of all people enrolled since 1984, including all updates to these details. We linked these data to a register of ~1100 affected properties, with subsequent linkage to the national death index and the Australian Cancer Database. We estimated Standardized Incidence Ratios (SIR) for selected cancers in people living in these houses to obtain a measure of exposure to environmental risk within the population.
ResultsAfter intensive cleaning and standardisation, nearly all (99.8%) of the affected addresses were linked. There were over one million people who had at least one ACT address between 1983 and 2013, and 2% of these had lived at an affected address and classified as exposed. The adjusted incidence of mesothelioma in exposed males was 2·5 times that of unexposed males (SIR 2·54, 95% CI 1·02–5·24), and there were some statistically significant results. The study population, number of deaths and cancers of interest were validated against the ACT census and registry figures. There were some limitations in coverage due to the period of available data, the frequency of address updates, and records with postal rather than residential addresses, but these were tested by sensitivity analyses.
Conclusion/ImplicationsThe study demonstrates the power of data linkage to (a) obtain a measure of exposure to an environmental risk within a population, and (b) obtain outcomes for the resulting case and control cohorts. This method could be applied in other risk studies where exposure is based on geography.

Background The health risks associated with living in houses insulated with asbestos are unknown. Loose-fill asbestos was used to insulate some houses in the Australian Capital Territory (ACT). We compared the incidence of mesothelioma and other cancers in residents of the ACT who did and did not live in these houses. Methods Our cohort study included all ACT residents identified using Medicare enrolment data. These data were linked to addresses of affected residential properties in the ACT to ascertain exposure. We followed up residents by linking data to the Australian Cancer Database and National Death Index. Outcomes were diagnosis of mesothelioma and selected other cancers. Effects were estimated for males and females separately using standardised incidence ratios (SIRs), adjusting for age and calendar time of diagnosis. Findings Between Nov 1, 1983, and Dec 31, 2013, 1 035 578 ACT residents were identified from the Medicare database. Of these, 17 248 (2%) had lived in an affected property, including seven (2%) of 285 people diagnosed with mesothelioma. The adjusted incidence of mesothelioma in males who had lived at an affected property was 2·5 times that of unexposed males (SIR 2·54, 95% CI 1·02–5·24). No mesotheliomas were reported among females who had lived at an affected property. Among individuals who had lived at an affected property, there was an elevated incidence of colorectal cancer in women (SIR 1·73, 95% CI 1·29–2·26) and prostate cancer in men (1·29, 1·07–1·54); colorectal cancer was increased, although not significantly, in males (SIR 1·32, 95% CI 0·99–1·72), with no significant increase in the other cancers studied. Interpretation Residential asbestos insulation is likely to be unsafe. Our findings have important health, social, financial, and legal implications for governments and communities in which asbestos has been used to insulate houses. ; This work was funded by the ACT Government.

IntroductionRecent advances in Australia mean that it is possible to link national clinical registries with government held administrative datasets. However, formal evaluations of such activities and the potential impact for research are lacking.
Objectives and ApproachWe aimed to assess the feasibility and accuracy of linking registrants from the Australian Stroke Clinical Registry (AuSCR) with the Medicare enrolment file. Following data custodian and ethics approvals, personal linkage identifiers were submitted to the Australian Institute of Health and Welfare (AIHW). De-identified data from AuSCR and the AIHW were submitted into the Secure Unified Research Environment and merged using project specific person-based IDs. We calculated the proportion of patients linked with the Medicare enrolment file that were present in the associated Medicare and medication dispensing datasets and the proportion with claims after their date of death. Logistic regression was used to identify factors associated with a non-merged patient.
Results17,980 AuSCR registrants (January 2010-July 2014) were submitted for linkage (median age 76 years; 46% female; 67% ischaemic stroke; 16% TIA). Of these, 93% were merged with Medicare (N=16,648) and 95% with subsidised medication dispensing claims data (N=17,079). In those who died, 127 (0.8%) had one or more Medicare claim and 411 (2.4%) had one or more medications dispensed after their death date. Asian born registrants were less likely to be merged with Medicare (adjusted Odds Ratio [aOR]: 0.54; 95% Confidence Interval [CI]: 0.40, 0.72) than Australian born registrants. Those aged ≥85 years were less likely to be merged with Medicare data than those aged <65 years (aOR 0.24; 95% CI: 0.19, 0.29) but were more likely to be merged with dispensing data (aOR: 2.22 (95% CI: 1.73, 2.84).
Conclusion/ImplicationsLinkage between a national clinical quality registry and the Medicare spine is feasible. These linkages will provide novel insights into post-stroke care.

Harmful algal blooms (HABs) cause harm to human health or hinder sustainable use of the marine environment in Blue Economy sectors. HABs are temporally and spatially variable and hence their mitigation is closely linked to effective early warning. The European Union (EU) Interreg Atlantic Area project "PRIMROSE", Predicting Risk and Impact of Harmful Events on the Aquaculture Sector, was focused on the joint development of HAB early warning systems in different regions along the European Atlantic Area. Advancement of the existing HAB forecasting systems requires development of forecasting tools, improvements in data flow and processing, but also additional data inputs to assess the distribution of HAB species, especially in areas away from national monitoring stations, usually located near aquaculture sites. In this contribution, we review different novel technologies for acquiring HAB data and report on the experience gained in several novel local data collection exercises performed during the project. Demonstrations include the deployment of autonomous imaging flow cytometry (IFC) sensors near two aquaculture areas: a mooring in the Daoulas estuary in the Bay of Brest and pumping from a bay in the Shetland Islands to an inland IFC; and several drone deployments, both of Unmanned Aerial Vehicles (UAV) and of Autonomous Surface vehicles (ASVs). Additionally, we have reviewed sampling approaches potentially relevant for HAB early warning including protocols for opportunistic water sampling by coastguard agencies. Experiences in the determination of marine biotoxins in non-traditional vectors and how they could complement standard routine HAB monitoring are also considered.

IntroductionRecent advances in data linkage infrastructure in Australia mean that data can be linked based on various identifiers across datasets. In a first for Australia, we tested the feasibility of linking data between a clinical quality disease registry with Australian and state government health data across multiple jurisdictions.
Objectives and ApproachTo determine whether high quality linked data for stroke can be obtained using a non-government managed registry (Australian Stroke Clinical Registry, AuSCR), national death registry data (Australian government), and hospital admission and emergency presentation data (state governments) to assess the accuracy of consistent variables across the different datasets. We used a cohort design with probabilistic data linkage to merge patient-level records. Descriptive statistics presented for matching concordance and Cohen's kappa for concordance across demographic variables. The sensitivity and specificity of in-hospital deaths collected in the AuSCR was assessed against national death registrations.
ResultsThere were 16,214 registrants in the study cohort. Their identifiers in the AuSCR from 2009-2013 were linked with death, emergency department and hospital discharge data from April 2004 to December 2016. In total, 99% of the AuSCR registrants were linked to one or more datasets; 98\% were linked with emergency presentation (80%) and/or admission (95%) data. Linkage to national death registrations identified 4,183 death; 1440 of these were identified as in-hospital deaths in both data sets demonstrating that in-hospital death classification in AuSCR had a 98.7% sensitivity and 99.6% specificity. Concordance between common demographic variables was excellent (kappa 0.84 for aboriginal status and kappa 0.99 for sex).
Conclusion/ImplicationsThe majority of AuSCR registrants were accurately linked to the Australian and state government datasets. Linkage quality was excellent and there was high concordance between common variables. The ability to reliably merge the datasets assures future comprehensive analyses of stroke care, ongoing health care resource utilisation and patient outcomes.

OBJECTIVE: To describe the challenges of obtaining state and nationally held data for linkage to a non-government national clinical registry. METHODS: We reviewed processes negotiated to achieve linkage between the Australian Stroke Clinical Registry (AuSCR), the National Death Index, and state held hospital data. Minutes from working group meetings, national workshop meetings, and documented communications with health department staff were reviewed and summarised. RESULTS: Time from first application to receipt of data was more than two years for most state data-sets. Several challenges were unique to linkages involving identifiable data from a non-government clinical registry. Concerns about consent, the re-identification of data, duality of data custodian roles and data ownership were raised. Requirements involved the development of data flow methods, separating roles and multiple governance and ethics approvals. Approval to link death data presented the fewest barriers. CONCLUSION: To our knowledge, this is the first time in Australia that person-level data from a clinical quality registry has been linked to hospital and mortality data across multiple Australian jurisdictions. Implications for Public Health: The administrative load of obtaining linked data makes projects such as this burdensome but not impossible. An improved national centralised strategy for data linkage in Australia is urgently needed.

OBJECTIVES: To determine the feasibility of linking data from the Australian Stroke Clinical Registry (AuSCR), the National Death Index (NDI), and state-managed databases for hospital admissions and emergency presentations; to evaluate data completeness and concordance between datasets for common variables. DESIGN, SETTING, PARTICIPANTS: Cohort design; probabilistic/deterministic data linkage of merged records for patients treated in hospital for stroke or transient ischaemic attack from New South Wales, Queensland, Victoria, and Western Australia. MAIN OUTCOME MEASURES: Descriptive statistics for data matching success; concordance of demographic variables common to linked databases; sensitivity and specificity of AuSCR in-hospital death data for predicting NDI registrations. RESULTS: Data for 16 214 patients registered in the AuSCR during 2009-2013 were linked with one or more state datasets: 15 482 matches (95%) with hospital admissions data, and 12 902 matches (80%) with emergency department presentations data were made. Concordance of AuSCR and hospital admissions data exceeded 99% for sex, age, in-hospital death (each κ = 0.99), and Indigenous status (κ = 0.83). Of 1498 registrants identified in the AuSCR as dying in hospital, 1440 (96%) were also recorded by the NDI as dying in hospital. In-hospital death in AuSCR data had 98.7% sensitivity and 99.6% specificity for predicting in-hospital death in the NDI. CONCLUSION: We report the first linkage of data from an Australian national clinical quality disease registry with routinely collected data from several national and state government health datasets. Data linkage enriches the clinical registry dataset and provides additional information beyond that for the acute care setting and quality of life at follow-up, allowing clinical outcomes for people with stroke (mortality and hospital contacts) to be more comprehensively assessed.