100 resultados para track records
Resumo:
A technologically innovative study was undertaken across two suburbs in Brisbane, Australia, to assess socioeconomic differences in women's use of the local environment for work, recreation, and physical activity. Mothers from high and low socioeconomic suburbs were instructed to continue with usual daily routines, and to use mobile phone applications (Facebook Places, Twitter, and Foursquare) on their mobile phones to ‘check-in’ at each location and destination they reached during a one-week period. These smartphone applications are able to track travel logistics via built-in geographical information systems (GIS), which record participants’ points of latitude and longitude at each destination they reach. Location data were downloaded to Google Earth and excel for analysis. Women provided additional qualitative data via text regarding the reasons and social contexts of their travel. We analysed 2183 ‘check-ins’ for 54 women in this pilot study to gain quantitative, qualitative, and spatial data on human-environment interactions. Data was gathered on distances travelled, mode of transport, reason for travel, social context of travel, and categorised in terms of physical activity type – walking, running, sports, gym, cycling, or playing in the park. We found that the women in both suburbs had similar daily routines with the exception of physical activity. We identified 15% of ‘check-ins’ in the lower socioeconomic group as qualifying for the physical activity category, compared with 23% in the higher socioeconomic group. This was explained by more daily walking for transport (1.7kms to 0.2kms) and less car travel each week (28.km to 48.4kms) in the higher socioeconomic suburb. We ascertained insights regarding the socio-cultural influences on these differences via additional qualitative data. We discuss the benefits and limitations of using new technologies and Google Earth with implications for informing future physical and social aspects of urban design, and health promotion in socioeconomically diverse cities.
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The parallel track model is one of the several models that are used in health promotion programmes that focus on community empowerment. It is unique in that it explicitly incorporates an empowerment approach with a top-down health programme. Since its development in 1999-2000 the model has been used in various health programmes in both developed and developing countries. The aim of this review is to examine the nature and extent of the application of this model and its contribution to promoting health. A review of the literature published between 2000 and 2011 was conducted. Nine results matched the inclusion criteria and revealed that the model has been mostly applied to disadvantaged communities to address health determinants, such as poverty and health literacy. This review found that the model had a positive impact on specific health outcomes such as health literacy and community capacity. We concluded that the parallel track model has the most potential for building capacity for community health promotion and appears to be the least useful for interventions focusing on health behaviour change within a limited time frame.
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Introduction The onset of Personally Controlled Electronic Health Records in Australia demand healthcare decision making processes to comprise, understand and accept electronic health records (EHR). Nurses play a key, central role in the healthcare decision making process and their perceptions and attitudes of EHRs are significant [1], which develop during their academic life. However, studies aimed at nursing students’ attitudes of EHRs are very limited [2-4]. A proper understanding of these attitudes and how they evolve with academic progress is important. This paper presents results from a survey conducted at a leading University in Queensland, Australia as a first step to filling this gap.
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Health care is an information-intensive business. Sharing information in health care processes is a smart use of data enabling informed decision-making whilst ensuring. the privacy and security of patient information. To achieve this, we propose data encryption techniques embedded Information Accountability Framework (IAF) that establishes transitions of the technological concept, thus enabling understanding of shared responsibility, accessibility, and efficient cost effective informed decisions between health care professionals and patients. The IAF results reveal possibilities of efficient informed medical decision making and minimisation of medical errors. Of achieving this will require significant cultural changes and research synergies to ensure the sustainability, acceptability and durability of the IAF
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This research was a step forward in developing a data integration framework for Electronic Health Records. The outcome of the research is a conceptual and logical Data Warehousing model for integrating Cardiac Surgery electronic data records. This thesis investigated the main obstacles for the healthcare data integration and proposes a data warehousing model suitable for integrating fragmented data in a Cardiac Surgery Unit.
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Temperate Australia sits between the heat engine of the tropics and the cold Southern Ocean, encompassing a range of rainfall regimes and falling under the influence of different climatic drivers. Despite this heterogeneity, broad-scale trends in climatic and environmental change are evident over the past 30 ka. During the early glacial period (∼30–22 ka) and the Last Glacial Maximum (∼22–18 ka), climate was relatively cool across the entire temperate zone and there was an expansion of grasslands and increased fluvial activity in regionally important Murray–Darling Basin. The temperate region at this time appears to be dominated by expanded sea ice in the Southern Ocean forcing a northerly shift in the position of the oceanic fronts and a concomitant influx of cold water along the southeast (including Tasmania) and southwest Australian coasts. The deglacial period (∼18–12 ka) was characterised by glacial recession and eventual disappearance resulting from an increase in temperature deduced from terrestrial records, while there is some evidence for climatic reversals (e.g. the Antarctic Cold Reversal) in high resolution marine sediment cores through this period. The high spatial density of Holocene terrestrial records reveals an overall expansion of sclerophyll woodland and rainforest taxa across the temperate region after ∼12 ka, presumably in response to increasing temperature, while hydrological records reveal spatially heterogeneous hydro-climatic trends. Patterns after ∼6 ka suggest higher frequency climatic variability that possibly reflects the onset of large scale climate variability caused by the El Niño/Southern Oscillation.
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Whilst alcohol is a common feature of many social gatherings, there are numerous immediate and long-term health and social harms associated with its abuse. Alcohol consumption is the world’s third largest risk factor for disease and disability with almost 4% of all deaths worldwide attributed to alcohol. Not surprisingly, alcohol use and binge drinking by young people is of particular concern with Australian data reporting that 39% of young people (18-19yrs) admitted drinking at least weekly and 32% drank to levels that put them at risk of alcohol-related harm. The growing market penetration and connectivity of smartphones may be an opportunities for innovation in promoting health-related self-management of substance use. However, little is known about how best to harness and optimise this technology for health-related intervention and behaviour change. This paper explores the utility and interface of smartphone technology as a health intervention tool to monitor and moderate alcohol use. A review of the psychological health applications of this technology will be presented along with the findings of a series of focus groups, surveys and behavioural field trials of several drink-monitoring applications. Qualitative and quantitative data will be presented on the perceptions, preferences and utility of the design, usability and functionality of smartphone apps to monitoring and moderate alcohol use. How these findings have shaped the development and evolution of the OnTrack app will be specifically discussed, along with future directions and applications of this technology in health intervention, prevention and promotion.
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The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).
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Higher Degree Research (HDR) student publications are increasingly valued by students, by professional communities and by research institutions. Peer-reviewed publications form the HDR student writer's publication track record and increase competitiveness in employment and research funding opportunities. These publications also make the results of HDR student research available to the community in accessible formats. HDR student publications are also valued by universities because they provide evidence of institutional research activity within a field and attract a return on research performance. However, although publications are important to multiple stakeholders, many Education HDR students do not publish the results of their research. Hence, an investigation of Education HDR graduates who submitted work for publication during their candidacy was undertaken. This multiple, explanatory case study investigated six recent Education HDR graduates who had submitted work to peer-reviewed outlets during their candidacy. The conceptual framework supported an analysis of the development of Education HDR student writing using Alexander's (2003, 2004) Model of Domain Learning which focuses on expertise, and Lave and Wenger's (1991) situated learning within a community of practice. Within this framework, the study investigated how these graduates were able to submit or publish their research despite their relative lack of writing expertise. Case data were gathered through interviews and from graduate publication records. Contextual data were collected through graduate interviews, from Faculty and university documents, and through interviews with two Education HDR supervisors. Directed content analysis was applied to all data to ascertain the support available in the research training environment. Thematic analysis of graduate and supervisor interviews was then undertaken to reveal further information on training opportunities accessed by the HDR graduates. Pattern matching of all interview transcripts provided information on how the HDR graduates developed writing expertise. Finally, explanation building was used to determine causal links between the training accessed by the graduates and their writing expertise. The results demonstrated that Education HDR graduates developed publications and some level of expertise simultaneously within communities of practice. Students were largely supported by supervisors who played a critical role. They facilitated communities of practice and largely mediated HDR engagement in other training opportunities. However, supervisor support alone did not ensure that the HDR graduates developed writing expertise. Graduates who appeared to develop the most expertise, and produce a number of publications reported experiencing both a sustained period of engagement within one community of practice, and participation in multiple communities of practice. The implications for the MDL theory, as applied to academic writing, suggests that communities of practice can assist learners to progress from initial contact with a new domain of interest through to competence. The implications for research training include the suggestion that supervisors as potentially crucial supporters of HDR student writing for publication should themselves be active publishers. Also, Faculty or university sponsorship of communities of practice focussed on HDR student writing for publication could provide effective support for the development of HDR student writing expertise and potentially increase the number of their peer-reviewed publications.
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Information privacy is a critical success/failure factor in information technology supported healthcare (eHealth). eHealth systems utilise electronic health records (EHR) as the main source of information, thus, implementing appropriate privacy preserving methods for EHRs is vital for the proliferation of eHealth. Whilst information privacy may be a fundamental requirement for eHealth consumers, healthcare professionals demand non-restricted access to patient information for improved healthcare delivery, thus, creating an environment where stakeholder requirements are contradictory. Therefore, there is a need to achieve an appropriate balance of requirements in order to build successful eHealth systems. Towards achieving this balance, a new genre of eHealth systems called Accountable-eHealth (AeH) systems has been proposed. In this paper, an access control model for EHRs is presented that can be utilised by AeH systems to create information usage policies that fulfil both stakeholders’ requirements. These policies are used to accomplish the aforementioned balance of requirements creating a satisfactory eHealth environment for all stakeholders. The access control model is validated using a Web based prototype as a proof of concept.
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Purpose To observe the incidence rates of hamstring strain injuries (HSIs) across different competition levels and ages during the Penn Relays Carnival. Methods Over a 3-year period all injuries treated by the medical staff were recorded. The type of injury, anatomic location, event in which the injury occurred, competition level and demographic data were documented. Absolute and relative HSI (per 1000 participants) were determined and odds ratios (OR) were calculated between genders, competition levels and events. Results Throughout the study period 48,473 athletes registered to participate in the Penn Relays Carnival, with 118 HSIs treated by the medical team. High school females displayed lesser risk of HSI than high school males (OR = 0.55, p = 0.021), and masters athletes were more likely than high school (OR = 4.26, p < 0.001) and college (OR = 3.55, p = 0.001) level athletes to suffer a HSI. The 4x400m relay displayed a greater likelihood of HSI compared to the 4x100m relay (OR = 1.77, p = 0.008). Conclusions High school males and masters levels athletes are most likely to suffer HSI, and there is higher risk in 400m events compared to 100m events.
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We present an approach to automatically de-identify health records. In our approach, personal health information is identified using a Conditional Random Fields machine learning classifier, a large set of linguistic and lexical features, and pattern matching techniques. Identified personal information is then removed from the reports. The de-identification of personal health information is fundamental for the sharing and secondary use of electronic health records, for example for data mining and disease monitoring. The effectiveness of our approach is first evaluated on the 2007 i2b2 Shared Task dataset, a widely adopted dataset for evaluating de-identification techniques. Subsequently, we investigate the robustness of the approach to limited training data; we study its effectiveness on different type and quality of data by evaluating the approach on scanned pathology reports from an Australian institution. This data contains optical character recognition errors, as well as linguistic conventions that differ from those contained in the i2b2 dataset, for example different date formats. The findings suggest that our approach compares to the best approach from the 2007 i2b2 Shared Task; in addition, the approach is found to be robust to variations of training size, data type and quality in presence of sufficient training data.
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Objective Evaluate the effectiveness and robustness of Anonym, a tool for de-identifying free-text health records based on conditional random fields classifiers informed by linguistic and lexical features, as well as features extracted by pattern matching techniques. De-identification of personal health information in electronic health records is essential for the sharing and secondary usage of clinical data. De-identification tools that adapt to different sources of clinical data are attractive as they would require minimal intervention to guarantee high effectiveness. Methods and Materials The effectiveness and robustness of Anonym are evaluated across multiple datasets, including the widely adopted Integrating Biology and the Bedside (i2b2) dataset, used for evaluation in a de-identification challenge. The datasets used here vary in type of health records, source of data, and their quality, with one of the datasets containing optical character recognition errors. Results Anonym identifies and removes up to 96.6% of personal health identifiers (recall) with a precision of up to 98.2% on the i2b2 dataset, outperforming the best system proposed in the i2b2 challenge. The effectiveness of Anonym across datasets is found to depend on the amount of information available for training. Conclusion Findings show that Anonym compares to the best approach from the 2006 i2b2 shared task. It is easy to retrain Anonym with new datasets; if retrained, the system is robust to variations of training size, data type and quality in presence of sufficient training data.
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Transition zones between bridge decks and rail tracks suffer early failure due to poor interaction between rail vehicles and sudden changes of stiffness. This has been an ongoing problem to rail industry and yet still no systematic studies appear to have been taken to maintain a gradually smoothening transmission of forces between the bridge and its approach. Differential settlement between the bridge deck and rail track in the transition zone is the fundamental issue, which negatively impacts the rail industry by causing passenger discomfort, early damage to infrastructure and vehicle components, speed reduction, and frequent maintenance cycles. Identification of mechanism of the track degradation and factors affecting is imperative to design any mitigation method for reducing track degradation rate at the bridge transition zone. Unfortunately this issue is still not well understood, after conducting a numbers of reviews to evaluate the key causes, and introducing a wide range of mitigation techniques. In this study, a comprehensive analysis of the available literature has been carried out to develop either a novel design framework or a mitigation technique for the bridge transition zone. This paper addresses three critical questions in relation to the track degradation at transition zone: (1) what are the causes of bridge transition track degradation?; (2) what are the available mitigation techniques in reducing the track degradation rate?; (3) what are the factors affecting on poor performance of the existing mitigation techniques?. It is found that the absence of soil-water response, dynamic loading response, and behaviour of geotechnical characteristics under long-term conditions in existing track transition design frameworks critically influence on the failures of existing mitigation techniques. This paper also evaluates some of the existing design frameworks to identify how each design framework addresses the track degradation at the bridge transition zone.
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This paper gives an overview of the INEX 2008 Ad Hoc Track. The main goals of the Ad Hoc Track were two-fold. The first goal was to investigate the value of the internal document structure (as provided by the XML mark-up) for retrieving relevant information. This is a continuation of INEX 2007 and, for this reason, the retrieval results are liberalized to arbitrary passages and measures were chosen to fairly compare systems retrieving elements, ranges of elements, and arbitrary passages. The second goal was to compare focused retrieval to article retrieval more directly than in earlier years. For this reason, standard document retrieval rankings have been derived from all runs, and evaluated with standard measures. In addition, a set of queries targeting Wikipedia have been derived from a proxy log, and the runs are also evaluated against the clicked Wikipedia pages. The INEX 2008 Ad Hoc Track featured three tasks: For the Focused Task a ranked-list of nonoverlapping results (elements or passages) was needed. For the Relevant in Context Task non-overlapping results (elements or passages) were returned grouped by the article from which they came. For the Best in Context Task a single starting point (element start tag or passage start) for each article was needed. We discuss the results for the three tasks, and examine the relative effectiveness of element and passage retrieval. This is examined in the context of content only (CO, or Keyword) search as well as content and structure (CAS, or structured) search. Finally, we look at the ability of focused retrieval techniques to rank articles, using standard document retrieval techniques, both against the judged topics as well as against queries and clicks from a proxy log.