Visualising linked health data to explore health events around preventable hospitalisations in NSW Australia

Objective: To explore patterns of health service use in the lead-up to, and following, admission for a ‘preventable’ hospitalisation. Setting: 266 950 participants in the 45 and Up Study, New South Wales (NSW) Australia Methods: Linked data on hospital admissions, general practitioner (GP) visits and other health events were used to create visual representations of health service use. For each participant, health events were plotted against time, with different events juxtaposed using different markers and panels of data. Various visualisations were explored by patient characteristics, and compared with a cohort of non-admitted participants matched on sociodemographic and health characteristics. Health events were displayed over calendar year and in the 90 days surrounding first preventable hospitalisation. Results: The visualisations revealed patterns of clustering of GP consultations in the lead-up to, and following, preventable hospitalisation, with 14% of patients having a consultation on the day of admission and 27% in the prior week. There was a clustering of deaths and other hospitalisations following discharge, particularly for patients with a long length of stay, suggesting patients may have been in a state of health deterioration. Specialist consultations were primarily clustered during the period of hospitalisation. Rates of all health events were higher in patients admitted for a preventable hospitalisation than the matched non-admitted cohort. Conclusions: We did not find evidence of limited use of primary care services in the lead-up to a preventable hospitalisation, rather people with preventable hospitalisations tended to have high levels of engagement with multiple elements of the healthcare system. As such, preventable hospitalisations might be better used as a tool for identifying sicker patients for managed care programmes. Visualising longitudinal health data was found to be a powerful strategy for uncovering patterns of health service use, and such visualisations have potential to be more widely adopted in health services research

Using weighted hospital service area networks to explore variation in preventable hospitalization

Objective: To demonstrate the use of multiple-membership multilevel models, which analytically structure patients in a weighted network of hospitals, for exploring between-hospital variation in preventable hospitalizations. Data Sources: Cohort of 267,014 people aged over 45 in NSW, Australia. Study Design: Patterns of patient flow were used to create weighted hospital service area networks (weighted-HSANs) to 79 large public hospitals of admission. Multiple-membership multilevel models on rates of preventable hospitalization, modeling participants structured within weighted-HSANs, were contrasted with models clustering on 72 hospital service areas (HSAs) that assigned participants to a discrete geographic region. Data Collection/Extraction Methods: Linked survey and hospital admission data. Principal Findings: Between-hospital variation in rates of preventable hospitalization was more than two times greater when modeled using weighted-HSANs rather than HSAs. Use of weighted-HSANs permitted identification of small hospitals with particularly high rates of admission and influenced performance ranking of hospitals, particularly those with a broadly distributed patient base. There was no significant association with hospital bed occupancy. Conclusion: Multiple-membership multilevel models can analytically capture information lost on patient attribution when creating discrete health care catchments. Weighted-HSANs have broad potential application in health services research and can be used across methods for creating patient catchments

Spin-dependent recombination in Czochralski silicon containing oxide precipitates

Electrically detected magnetic resonance is used to identify recombination centers in a set of Czochralski grown silicon samples processed to contain strained oxide precipitates with a wide range of densities (~ 1e9 cm-3 to ~ 7e10 cm-3). Measurements reveal that photo-excited charge carriers recombine through Pb0 and Pb1 dangling bonds and comparison to precipitate-free material indicates that these are present at both the sample surface and the oxide precipitates. The electronic recombination rates vary approximately linearly with precipitate density. Additional resonance lines arising from iron-boron and interstitial iron are observed and discussed. Our observations are inconsistent with bolometric heating and interpreted in terms of spin-dependent recombination. Electrically detected magnetic resonance is thus a very powerful and sensitive spectroscopic technique to selectively probe recombination centers in modern photovoltaic device materials.Comment: 8 pages, 8 figure

Do hospitals influence geographic variation in admission for preventable hospitalisation? A data linkage study in New South Wales, Australia

Objective: Preventable hospitalisations are used internationally as a performance indicator for primary care, but the influence of other health system factors remains poorly understood. This study investigated between-hospital variation in rates of preventable hospitalisation. Setting: Linked health survey and hospital admissions data for a cohort study of 266 826 people aged over 45 years in the state of New South Wales, Australia. Method: Between-hospital variation in preventable hospitalisation was quantified using cross-classified multiple-membership multilevel Poisson models, adjusted for personal sociodemographic, health and area-level contextual characteristics. Variation was also explored for two conditions unlikely to be influenced by discretionary admission practice: emergency admissions for acute myocardial infarction (AMI) and hip fracture. Results: We found significant between-hospital variation in adjusted rates of preventable hospitalisation, with hospitals varying on average 26% from the state mean. Patients served more by community and multipurpose facilities (smaller facilities primarily in rural areas) had higher rates of preventable hospitalisation. Community hospitals had the greatest between-hospital variation, and included the facilities with the highest rates of preventable hospitalisation. There was comparatively little between-hospital variation in rates of admission for AMI and hip fracture. Conclusions: Geographic variation in preventable hospitalisation is determined in part by hospitals, reflecting different roles played by community and multipurpose facilities, compared with major and principal referral hospitals, within the community. Care should be taken when interpreting the indicator simply as a performance measure for primary care

Shoot growth of woody trees and shrubs is predicted by maximum plant height and associated traits

1. The rate of elongation and thickening of individual branches (shoots) varies across plant species. This variation is important for the outcome of competition and other plant-plant interactions. Here we compared rates of shoot growth across 44 species from tropical, warm temperate, and cool temperate forests of eastern Australia.2. Shoot growth rate was found to correlate with a suite of traits including the potential height of the species, xylem-specific conductivity, leaf size, leaf area per xylem cross-section, twig diameter (at 40 cm length), wood density and modulus of elasticity.3. Within this suite of traits, maximum plant height was the clearest correlate of growth rates, explaining 50 to 67% of the variation in growth overall (p p 4. Growth rates were not strongly correlated with leaf nitrogen or leaf mass per unit leaf area.5. Correlations between growth and maximum height arose both across latitude (47%, p p p p < 0.0001), reflecting intrinsic differences across species and sites

The effect of oxide precipitates on minority carrier lifetime in n-type silicon

Supersaturated levels of interstitial oxygen in Czochralski silicon can lead to the formation of oxide precipitates. Although beneficial from an internal gettering perspective, oxygen-related extended defects give rise to recombination which reduces minority carrier lifetime. The highest efficiency silicon solar cells are made from n-type substrates in which oxide precipitates can have a detrimental impact on cell efficiency. In order to quantify and to understand the mechanism of recombination in such materials, we correlate injection level-dependent minority carrier lifetime data measured with silicon nitride surface passivation with interstitial oxygen loss and precipitate concentration measurements in samples processed under substantially different conditions. We account for surface recombination, doping level, and precipitate morphology to present a generalised parameterisation of lifetime. The lifetime data are analysed in terms of recombination activity which is dependent on precipitate density or on the surface area of different morphologies of precipitates. Correlation of the lifetime data with interstitial oxygen loss data shows that the recombination activity is likely to be dependent on the precipitate surface area. We generalise our findings to estimate the impact of oxide precipitates with a given surface area on lifetime in both n-type and p-type silicon

Climate shapes community flowering periods across biomes

Aim: Climate shapes the composition and function of plant communities globally, but it remains unclear how this influence extends to floral traits. Flowering phenology, or the time period in which a species flowers, has well-studied relationships with climatic signals at the species level but has rarely been explored at a cross-community and continental scale. Here, we characterise the distribution of flowering periods (months of flowering) across continental plant communities encompassing six biomes, and determine the influence of climate on community flowering period lengths. Location: Australia. Taxon: Flowering plants. Methods: We combined plant composition and abundance data from 629 standardised floristic surveys (AusPlots) with data on flowering period from the AusTraits database and additional primary literature for 2983 species. We assessed abundance-weighted community mean flowering periods across biomes and tested their relationship with climatic annual means and the predictability of climate conditions using regression models. Results: Combined, temperature and precipitation (annual mean and predictability) explain 29% of variation in continental community flowering period. Plant communities with higher mean temperatures and lower mean precipitation have longer mean flowering periods. Moreover, plant communities in climates with predictable temperatures and, to a lesser extent, predictable precipitation have shorter mean flowering periods. Flowering period varies by biome, being longest in deserts and shortest in alpine and montane communities. For instance, desert communities experience low and unpredictable precipitation and high, unpredictable temperatures and have longer mean flowering periods, with desert species typically flowering at any time of year in response to rain. Main conclusions: Current climate conditions shape flowering periods across biomes, with implications for phenology under climate change. Shifts in flowering periods across climatic gradients reflect changes in plant strategies, affecting patterns of plant growth and reproduction as well as the availability of floral resources for pollinators across the landscape

Sociodemographic and Health Characteristics, Rather Than Primary Care Supply, are Major Drivers of Geographic Variation in Preventable Hospitalizations in Australia

ACKNOWLEDGMENTS: The authors thank the many thousands of people participating in the 45 and Up Study. The authors also thank the Sax Institute, the NSW Ministry of Health, and the NSW Register of Births, Deaths, and Marriages for allowing access to the data, and the Centre for Health Record Linkage for conducting the probabilistic linkage of records.Peer reviewedPublisher PD

Quantitative copper measurement in oxidized p-type silicon wafers using microwave photoconductivity decay

We propose a method to measure trace copper contamination in p-type silicon using the microwave photoconductivity decay (μ-PCD) technique. The method is based on the precipitation of interstitial copper, activated by high-intensity light, which results in enhanced minority carrier recombination activity. We show that there is a quantitative correlation between the enhanced recombination rate and the Cu concentration by comparing μ-PCD measurements with transient ion drift and total reflection x-ray fluorescence measurements. The results indicate that the method is capable of measuring Cu concentrations down to 10exp10cm−3. There are no limitations to wafer storage time if corona charge is used on the oxidized wafer surfaces as the charge prevents copper outdiffusion. We briefly discuss the role of oxide precipitates both in the copperprecipitation and in the charge carrier recombination processes.Peer reviewe

Sexual dimorphism in trait variability and its eco-evolutionary and statistical implications

Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioural traits. Sex differences in trait variability, however, are yet to receive similar recognition. In medical science, mammalian females are assumed to have higher trait variability due to estrous cycles (the ‘estrus-mediated variability hypothesis’); historically in biomedical research, females have been excluded for this reason. Contrastingly, evolutionary theory and associated data support the ‘greater male variability hypothesis’. Here, we test these competing hypotheses in 218 traits measured in >26,900 mice, using meta-analysis methods. Neither hypothesis could universally explain patterns in trait variability. Sex bias in variability was trait-dependent. While greater male variability was found in morphological traits, females were much more variable in immunological traits. Sex-specific variability has eco-evolutionary ramifications, including sex-dependent responses to climate change, as well as statistical implications including power analysis considering sex difference in variance