Children are more vulnerable to adverse environmental exposures. The unique ways in which they interact with their environment and their dynamic developmental physiology mean that they generally receive a higher dose of toxicant for a given level of environmental exposure. In addition, children are frequently more likely to suffer adverse health outcomes from exposures. The developmental stage of the child during which the exposure occurs has a major influence on the consequences of the exposure. For example, exposures during organogenesis may result in permanent structural changes, whereas exposures once organogenesis is complete are more likely to result in functional consequences. The immune, respiratory, and central nervous systems are immature at birth and have a prolonged period of postnatal maturation. Thus, these organ systems are vulnerable to postnatal exposures.
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 nongovernment 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.
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.
The aim of this study was to quantify the use of linked data for health and human services research in Australia since the establishment of the Population Health Research Network (PHRN) in 2009. A systematic literature search was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 checklist to search for all publications involving the use of Australian linked data between 2009-10 and 2016-17. Publications were categorised by subject, data linked and data linkage unit involved. In all, 7153 articles were identified from the initial search, and 1208 were included in the final analysis. An increase in the number of publications involving linked data was observed from 2009-10 through to 2015-16. Most articles (82%) featured data linked by at least one PHRN-funded data linkage unit. The research areas of 86% of publications were able to be classified according to the International Statistical Classification of Diseases and Related Health Problems 10th Revision Australian Modification (ICD-10-AM). The number of publications involving cross-sectoral linked data also increased. Investment in Australian data linkage infrastructure has seen an increase in the number of research publications involving the use of linked health and human services data. This study identified areas where linked data is commonly used and those where use could be improved. Data linkage is a method of bringing together information about individual people, places and events from different sources in a way that protects individual privacy. Individual jurisdictions have reported benefits from research conducted using linked data, including the generation of new knowledge and supporting improvements in the delivery of a wide range of health and human services. There has been significant investment in national data linkage infrastructure in Australia over the past 8 years. To date, there has been no systematic investigation of the effect of this investment on the use of linked population data by the research community. This paper provides evidence of the increased use of high-quality population-based linked data in research over the 8-year period studied. It demonstrates the application of data linkage across a wide range of health areas and highlights the small but growing number of studies using cross-sectoral data to investigate complex conditions. It is important to demonstrate to funders, policy makers, data custodians and researchers the value of robust data linkage capacity as an important national resource. Its use by researchers can bring enormous social and economic benefits by providing a more complete picture of the health and well-being of the community. The range of data collections routinely linked is increasing, as is the pool of researchers experienced in handling and analysing the data. Continued investment in Australia's data linkage infrastructure and the inclusion of other collections including general practice data will augment the use of this infrastructure in expanding the evidenc...
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