Purpose:It has been argued that rare diseases should be recognized as a public health priority. However, there is a shortage of epidemiological data describing the true burden of rare diseases. This study investigated hospital service use to provide a better understanding of the collective health and economic impacts of rare diseases.Methods:Novel methodology was developed using a carefully constructed set of diagnostic codes, a selection of rare disease cohorts from hospital administrative data, and advanced data-linkage technologies. Outcomes included health-service use and hospital admission costs.Results:In 2010, cohort members who were alive represented approximately 2.0% of the Western Australian population. The cohort accounted for 4.6% of people discharged from hospital and 9.9% of hospital discharges, and it had a greater average length of stay than the general population. The total cost of hospital discharges for the cohort represented 10.5% of 2010 state inpatient hospital costs.Conclusions:This population-based cohort study provides strong new evidence of a marked disparity between the proportion of the population with rare diseases and their combined health-system costs. The methodology will inform future rare-disease studies, and the evidence will guide government strategies for managing the service needs of people living with rare diseases.Genet Med advance online publication 22 September 2016

Measures of the gap in living standards, life expectancy, education, health and employment between Indigenous and non-Indigenous Australians are primarily derived from administrative data sources. However, Indigenous identification in these data sources is affected by administrative practices, missing data, inconsistency, and error. As these factors have changed over time, assessing whether the gap between Indigenous and non-Indigenous Australians has changed over time, based on data unadjusted for these sources of error can potentially lead to misguided conclusions. Combining administrative data on the same individuals collected from different sources provides a method by which a more consistent derived Indigenous status can be applied across all records for an individual within a linked data environment. We used the Western Australian Data Linkage system to produce derived Indigenous statuses for individuals using a range of algorithms. We found that these algorithms reduced the amount of missing data and improved within-individual consistency. Based on these findings, we recommend our Multi-Stage Median algorithm be used as the standard indicator of Indigenous status for any reporting based on administrative datasets when multiple datasets are available for linkage, and that algorithmic approaches also be considered for improving the quality of other demographic variables from administrative data sources.

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Genetic marker technologies, such as marker-assisted selection, parentage identification, and gene introgression can be applied to livestock selection programs. Highly saturated genetic maps are now available for cattle, swine, and sheep to provide the genetic framework for developing MAS programs. These programs rely on three phases for commercialization of the technology: the detection phase, in which quantitative trait loci are located and their effects on the phenotype measured; the evaluation phase, in which the markers are evaluated in commercial populations; and the implementation phase, in which markers are combined with phenotypic and pedigree information in genetic evaluation for predicting the genetic merit of individuals within the population. Predicting the economic impact of genetic technologies is a complex process that requires quantitative prediction and economic analysis. Evaluating the impact of these benefits across an industry can be achieved through a process in which gains from implementation of a genetic technology are assessed at the individual, enterprise, and industry levels. A pattern of annual benefits and costs can be predicted using gene flows that can be evaluated by conventional economic analysis.

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BackgroundStatistical time series derived from administrative data sets form key indicators in measuring progress in addressing disadvantage in Aboriginal and Torres Strait Islander populations in Australia. However, inconsistencies in the reporting of Indigenous status can cause difficulties in producing reliable indicators. External data sources, such as survey data, provide a means of assessing the consistency of administrative data and may be used to adjust statistics based on administrative data sources.MethodsWe used record linkage between a large-scale survey (the Western Australian Aboriginal Child Health Survey), and two administrative data sources (the Western Australia (WA) Register of Births and the WA Midwives’ Notification System) to compare the degree of consistency in determining Indigenous status of children between the two sources. We then used a logistic regression model predicting probability of consistency between the two sources to estimate the probability of each record on the two administrative data sources being identified as being of Aboriginal and/or Torres Strait Islander origin in a survey. By summing these probabilities we produced model-adjusted time series of neonatal outcomes for Aboriginal and/or Torres Strait Islander births.ResultsCompared to survey data, information based only on the two administrative data sources identified substantially fewer Aboriginal and/or Torres Strait Islander births. However, these births were not randomly distributed. Births of children identified as being of Aboriginal and/or Torres Strait Islander origin in the survey only were more likely to be living in urban areas, in less disadvantaged areas, and to have only one parent who identifies as being of Aboriginal and/or Torres Strait Islander origin, particularly the father. They were also more likely to have better health and wellbeing outcomes. Applying an adjustment model based on the linked survey data increased the estimated number of Aboriginal and/or Torres Strait Islander births in WA by around 25%, however this increase was accompanied by lower overall proportions of low birth weight and low gestational age babies.ConclusionsRecord linkage of survey data to administrative data sets is useful to validate the quality of recording of demographic information in administrative data sources, and such information can be used to adjust for differential identification in administrative data.

Genetic improvement of aquaculture species offers a substantial opportunity for increased production ef®ciency, health, product quality and, ultimately, pro®tability in aquacultural enterprises. Technologies exist that can be implemented immediately to improve multiple traits that have economic value, while simultaneously accounting for inbreeding effects. Genetic improvement techniques for delivering genetic gain include formal de®nition of the breeding objective, estimation of genetic parameters that describe populations and their differences, evaluation of additive and non-additive genetic merit of individuals or families and de®ning the structure of a breeding programme in terms of mating plans. Novel genetic technologies involving the use of DNAbased tools are also under development for a range of aquaculture species. These gene marker technologies can be used for identi®cation and monitoring of lines, families and individuals, monitoring and control of inbreeding, diagnosis of simply inherited traits and genetic improvement through selection for favourable genes and gene combinations. The identi®cation of quantitative trait loci (QTL), and direct or linked markers for them, will facilitate marker-assisted selection in aquaculture species, enabling improvement in economically important traits, particularly those that are dif®cult to breed for, such as food conversion ef®ciency and disease resistance.