896 resultados para Health data


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Aim: The purpose of this research is to examine School Based Youth Health Nurses experience of a true health promotion approach. Background: The School Based Youth Health Nurse Program is a state-wide school nursing initiative in Queensland, Australia. The program employs more than 120 fulltime and fractional school nurses who provide health services in state high schools. The role incorporates two primary components: individual health consultations and health promotion strategies. Design/Methods: This study is a retrospective inquiry generated from a larger qualitative research project about the experience of school based youth health nursing. The original methodology was phenomenography. In-depth interviews were conducted with sixteen school nurses recruited through purposeful and snowball sampling. This study accesses a specific set of raw data about School Based Youth Health Nurses experience of a true health promotion approach. The Ottawa Charter for Health Promotion (1986) is used as a framework for deductive analysis. Results: The findings indicate school nurses have neither an adverse or affirmative conceptual experience of a true health promotion approach and an adverse operational experience of a true health promotion approach based on the action areas of the Ottawa Charter. Conclusions: The findings of this research are important because they challenge the notion that school nurses are the most appropriate health professionals to undertake a true health promotion approach. If school nurses are the most appropriate health professionals to do a true health promotion approach, there are implications for recruitment and training and qualifications. If school nurses are not, who are the most appropriate health professionals to do school health promotion? Implications for Practice: These findings can be applied to other models of school nursing in Australia which emphasises a true health promotion approach because they relate specifically to school nurses’ experience of a true health promotion approach.

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Good management, supported by accurate, timely and reliable health information, is vital for increasing the effectiveness of Health Information Systems (HIS). When it comes to managing the under resourced health systems of developing countries, information-based decision making is particularly important. This paper reports findings of a self-report survey that investigated perceptions of local health managers (HMs) of their own regional HIS in Sri Lanka. Data were collected through a validated, pre-tested postal questionnaire, and distributed among a selected group of HMs to elicit their perceptions of the current HIS in relation to information generation, acquisition and use, required reforms to the information system and application of information and communication technology (ICT). Results based on descriptive statistics indicated that the regional HIS was poorly organised and in need of reform; that management support for the system was unsatisfactory in terms of relevance, accuracy, timeliness and accessibility; that political pressure and community and donor requests took precedence over vital health information when management decisions were made; and use of ICT was unsatisfactory. HIS strengths included user-friendly paper formats, a centralised planning system and an efficient disease notification system; weaknesses were lack of comprehensiveness, inaccuracy, and lack of a feedback system. Responses of participants indicated that HIS would be improved by adopting an internationally accepted framework and introducing ICT applications. Perceived barriers to such improvements were high initial cost of educating staff to improve computer literacy, introduction of ICTs, and HIS restructure. We concluded that the regional HIS of Central Province, Sri Lanka had failed to provide much needed information support to HMs. These findings are consistent with similar research in other developing countries and reinforce the need for further research to verify causes of poor performance and to design strategic reforms to improve HIS in regional Sri Lanka.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

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This paper describes a generalised linear mixed model (GLMM) approach for understanding spatial patterns of participation in population health screening, in the presence of multiple screening facilities. The models presented have dual focus, namely the prediction of expected patient flows from regions to services and relative rates of participation by region- service combination, with both outputs having meaningful implications for the monitoring of current service uptake and provision. The novelty of this paper lies with the former focus, and an approach for distributing expected participation by region based on proximity to services is proposed. The modelling of relative rates of participation is achieved through the combination of different random effects, as a means of assigning excess participation to different sources. The methodology is applied to participation data collected from a government-funded mammography program in Brisbane, Australia.

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Chapter 5: Fertility and infertility. p52-70. This section describes patterns of fertility across Surveys 1 to 4 among the cohort of women who were born in 1973-1978. This section includes the examination of pregnancy outcomes including both live births and pregnancy losses (stillbirths, miscarriages, terminations and ectopic pregnancies). This section also examines the prevalence of self-reported problems with fertility and whether these women sought advice and/or treatment. As women age they are more likely to experience infertility and, with little other data available, the ALSWH provides an important opportunity to examine this problem and the related use of health services. 1. Pregnancy losses are common. Half of the women who report a pregnancy outcome at Survey 4 have experienced a pregnancy loss. 2. More than one third (39%) of women who have experienced a live birth by Survey 4 have also experienced a pregnancy loss. 3. For every ten women aged 28-33 years in 2006: four women had not had been pregnant, five women had a live birth (with or without a recognised pregnancy loss), and one woman had a recognised pregnancy loss only. 4. Among women who had tried to conceive or had been pregnant, one-in-six had experienced infertility. (i.e. tried unsuccessfully to get pregnant for 12 months or more) 5. The most significant factors associated with having infertility, seeking advice and using treatment were: polycystic ovary syndrome, endometriosis and miscarriage. 6. Of the women who reported infertility, two-thirds sought advice but only half used treatment. 7. Most of the women who used fertility treatment had used low cost and non-invasive methods.

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Background Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. Methods In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns: (a) a gene set, and (b) the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. Conclusions This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.

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miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star

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QUT’s new metadata repository (data registry), Research Data Finder, has been designed to promote the visibility and discoverability of QUT research datasets. Funded by the Australian National Data Service (ANDS), it will provide a qualitative snapshot of research data outputs created or collected by members of the QUT research community that are available via open or mediated access. As a fully integrated metadata repository Research Data Finder aligns with institutional sources of truth, such as QUT’s research administrative system, ResearchMaster, as well as QUT’s Academic Profiles system to provide high quality data descriptions that increase awareness of, and access to, shareable research data. In addition, the repository and its workflows are designed to foster smoother data management practices, enhance opportunities for collaboration and research, promote cross-disciplinary research and maximize existing research datasets. The metadata schema used in Research Data Finder is the Registry Interchange Format - Collections and Services (RIF-CS), developed by ANDS in 2009. This comprehensive schema is potentially complex for researchers; unlike metadata for publications, which are often made publicly available with the official publication, metadata for datasets are not typically available and need to be created. Research Data Finder uses a hybrid self-deposit and mediated deposit system. In addition to automated ingests from ResearchMaster (research project information) and Academic Profiles system (researcher information), shareable data is identified at a number of key “trigger points” in the research cycle. These include: research grant proposals; ethics applications; Data Management Plans; Liaison Librarian data interviews; and thesis submissions. These ingested records can be supplemented with related metadata including links to related publications, such as those in QUT ePrints. Records deposited in Research Data Finder are harvested by ANDS and made available to a national and international audience via Research Data Australia, ANDS’ discovery service for Australian research data. Researcher and research group metadata records are also harvested by the National Library of Australia (NLA) and these records are then published in Trove (the NLA’s digital information portal). By contributing records to the national infrastructure, QUT data will become more visible. Within Australia and internationally, many funding bodies have already mandated the open access of publications produced from publicly funded research projects, such as those supported by the Australian Research Council (ARC), or the National Health and Medical Research Council (NHMRC). QUT will be well placed to respond to the rapidly evolving climate of research data management. This project is supported by the Australian National Data Service (ANDS). ANDS is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program and the Education Investment Fund (EIF) Super Science Initiative.

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Climate change and land use pressures are making environmental monitoring increasingly important. As environmental health is degrading at an alarming rate, ecologists have tried to tackle the problem by monitoring the composition and condition of environment. However, traditional monitoring methods using experts are manual and expensive; to address this issue government organisations designed a simpler and faster surrogate-based assessment technique for consultants, landholders and ordinary citizens. However, it remains complex, subjective and error prone. This makes collected data difficult to interpret and compare. In this paper we describe a work-in-progress mobile application designed to address these shortcomings through the use of augmented reality and multimedia smartphone technology.

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Background: Chronic leg ulcers cause long term ill-health for older adults and the condition places a significant burden on health service resources. Although evidence on effective management of the condition is available, a significant evidence-practice gap is known to exist, with many suggested reasons e.g. multiple care providers, costs of care and treatments. This study aimed to identify effective health service pathways of care which facilitated evidence-based management of chronic leg ulcers. Methods: A sample of 70 patients presenting with a lower limb leg or foot ulcer at specialist wound clinics in Queensland, Australia were recruited for an observational study and survey. Retrospective data were collected on demographics, health, medical history, treatments, costs and health service pathways in the previous 12 months. Prospective data were collected on health service pathways, pain, functional ability, quality of life, treatments, wound healing and recurrence outcomes for 24 weeks from admission. Results: Retrospective data indicated that evidence based guidelines were poorly implemented prior to admission to the study, e.g. only 31% of participants with a lower limb ulcer had an ABPI or duplex assessment in the previous 12 months. On average, participants accessed care 2–3 times/week for 17 weeks from multiple health service providers in the twelve months before admission to the study clinics. Following admission to specialist wound clinics, participants accessed care on average once per week for 12 weeks from a smaller range of providers. The median ulcer duration on admission to the study was 22 weeks (range 2–728 weeks). Following admission to wound clinics, implementation of key indicators of evidence based care increased (p<0.001) and Kaplan-Meier survival analysis found the median time to healing was 12 weeks (95% CI 9.3–14.7). Implementation of evidence based care was significantly related to improved healing outcomes (p<0.001). Conclusions: This study highlights the complexities involved in accessing expertise and evidence based wound care for adults with chronic leg or foot ulcers. Results demonstrate that access to wound management expertise can promote streamlined health services and evidence based wound care, leading to efficient use of health resources and improved health.

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From human biomonitoring data that are increasingly collected in the United States, Australia, and in other countries from large-scale field studies, we obtain snap-shots of concentration levels of various persistent organic pollutants (POPs) within a cross section of the population at different times. Not only can we observe the trends within this population with time, but we can also gain information going beyond the obvious time trends. By combining the biomonitoring data with pharmacokinetic modeling, we can re-construct the time-variant exposure to individual POPs, determine their intrinsic elimination half-lives in the human body, and predict future levels of POPs in the population. Different approaches have been employed to extract information from human biomonitoring data. Pharmacokinetic (PK) models were combined with longitudinal data1, with single2 or multiple3 average concentrations of a cross-sectional data (CSD), or finally with multiple CSD with or without empirical exposure data4. In the latter study, for the first time, the authors based their modeling outputs on two sets of CSD and empirical exposure data, which made it possible that their model outputs were further constrained due to the extensive body of empirical measurements. Here we use a PK model to analyze recent levels of PBDE concentrations measured in the Australian population. In this study, we are able to base our model results on four sets5-7 of CSD; we focus on two PBDE congeners that have been shown3,5,8-9 to differ in intake rates and half-lives with BDE-47 being associated with high intake rates and a short half-life and BDE-153 with lower intake rates and a longer half-life. By fitting the model to PBDE levels measured in different age groups in different years, we determine the level of intake of BDE-47 and BDE-153, as well as the half-lives of these two chemicals in the Australian population.

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The present study examined Queensland Transcultural Mental Health Centre (QTMHC) client characteristics in order to provide a better understanding for development of future health service delivery models. Archived data that was collected for 1499 clients over two years period (2007-2009) was analysed using descriptive statistics and Chi squares. The results indicated that clients were referred from a range of sources and were generally adults. There were more women than men, who sought services. At least half of the clients had language barriers and relied on bilingual workers. Most frequently expressed mental health issues were mood disorder symptoms, followed by symptoms of schizophrenia and psychosis and anxiety. Acculturation strains and stressors were described as the most common psychosocial issues. Mental health and psychosocial issues differed for age, gender and world regions from which the CALD clients originated. The findings provided an understanding of clients who seek services at QTMHC. Various ways in which transcultural services and data bases can be further improved are discussed.

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Living with substance users negatively impacts upon family members in many ways, and distress is common. Despite these deep and wide-ranging impacts, supportive interventions for family members in their own right are rarely available. Thailand has substantial and growing problems with substance use, and there is very little support or family members of drug users, especially in community setting. The Thai Family Support (TFS) program was designed for implementation in primary health care units (PCUs) in Thailand. TFS was based on two approaches with existing empirical support in Western contexts—the 5-step method and CRAFT—with adaptations to a Thai setting that included integration with Buddhist practices. Its aims were to increase well-being of family members, reduce mental distress, improve family relationships between family members, and engage substance users in behaviour change. A small-scale randomised controlled trial on TFS with a Delayed Treatment control was conducted, with assessments at 8 weeks (Post 1) and 20-24 weeks (Post 2). Structured interviews with participants and PCU staff and an examination of five case studies augmented the quantitative results. Mixed Model Analyses were applied to quantitative outcomes, and thematic analysis was used for qualitative data. Thirty-six participants (18 in each of Immediate and Delayed Conditions) were recruited. A significant difference at Baseline between the two conditions was observed on the Thai GHQ-28 and Gender, but it was not possible to statistically control for these effects. There was a significant Time by Condition interaction on the Thai GHQ-28, WHOQOL-BREF-THAI and FAS, reflecting greater improvements in the Immediate condition by Post 1, but with the Delayed condition meeting or exceeding that effect by Post 2. On FES Cohesion and Conflict, there were falls across conditions at Post 2, but only Cohesion also showed a Time by Condition interaction, and that effect was consistent with a delayed impact of treatment. Overall, TFS by PCU staff in the Delayed Condition gave similar results to TFS conducted by the researcher, supporting the viability of its dissemination to standard health services. Qualitative data also confirmed the quantitative results. Most participants reported physiological and psychological improvements even though their substance-using relative did not change their drug use behaviour. After completing TFS, participants reported increased knowledge, group support and sharing feeling, having positive patient-professional relationship, having greater knowledge of substance abuse and social support. In particular, they changed their behaviour towards the substance user, resulting in improvements to family relationships. PCU staff gave similar responses on the efficacy of TFS, and saw it as feasible for routine use, although some implementation challenges were identified. The cultural adaptation and in particular the religious activities, were recognised by participants and PCU staff as an important component of TFS to support psychological health and well-being. Findings from this study showed the impact of substance use on family members and difficulties that they experienced when living with the substance users, resulting distresses and burden that may develop severe mental health disease. Drug use policies should be modified to support family members and response to their needs effectively for early prevention. This study also gave preliminary support for application of the TFS program in rural primary care settings and identified some policies that will be required for it to be disseminated more broadly.

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This article focuses on the relationship between private insurance status and dental service utilisation in Australia using data between 1995 and 2001. This article employs joint maximum likelihood to estimate models of time since last dental visit treating private ancillary health insurance (PAHI) as endogenous. The sensitivity of results to the choice between two different but related types of instrumental variables is examined. We find robust evidence in both 1995 and 2001 that individuals with a PAHI policy make significantly more frequent dental consultations relative to those without such coverage. A comparison of the 1995 and 2001 results, however, suggests that there has been an increasing role of PAHI in terms of the frequency of dental consultations over time. This seems intuitive given the trends in the price of unsubsidised private dental consultations. In terms of policy, our results suggest that while government measures to increase private health insurance coverage in Australia has been successful to a significant degree, it may have come at some cost in terms of socio-economic inequality as the privately insured are provided much better access to care and financial protection.

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A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.