784 resultados para Health models
Resumo:
We are pleased to present the papers from the Australasian Health Informatics and Knowledge Management (HIKM) conference stream held on 20 January 2011 in Perth as a session of the Australasian Computer Science Week (ASCW) 2011. Formerly HIKM was named Health Data and Knowledge Management, however the inclusion of the health informatics term is timely given the current health reform. The submissions to HIKM 2011 demonstrated that Australasian researchers lead with many research and development innovations coming to fruition. Some of these innovations can be seen here, and we believe further recognition will accomplish by continuation to HIKM in the future. The HIKM conference is a review of health informatics related research, development and education opportunities. The conference papers were written to communicate with other researchers and share research findings, capturing each and every aspect of the health informatics field. They are namely: conceptual models and architectures, privacy and quality of health data, health workflow management patient journey analysis, health information retrieval, analysis and visualisation, data integration/linking, systems for integrated or coordinated care, electronic health records (EHRs) and personally controlled electronic health records (PCEHRs), health data ontologies, and standardisation in health data and clinical applications.
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The determinants and key mechanisms of cancer cell osteotropism have not been identified, mainly due to the lack of reproducible animal models representing the biological, genetic and clinical features seen in humans. An ideal model should be capable of recapitulating as many steps of the metastatic cascade as possible, thus facilitating the development of prognostic markers and novel therapeutic strategies. Most animal models of bone metastasis still have to be derived experimentally as most syngeneic and transgeneic approaches do not provide a robust skeletal phenotype and do not recapitulate the biological processes seen in humans. The xenotransplantation of human cancer cells or tumour tissue into immunocompromised murine hosts provides the possibility to simulate early and late stages of the human disease. Human bone or tissue-engineered human bone constructs can be implanted into the animal to recapitulate more subtle, species-specific aspects of the mutual interaction between human cancer cells and the human bone microenvironment. Moreover, the replication of the entire "organ" bone makes it possible to analyse the interaction between cancer cells and the haematopoietic niche and to confer at least a partial human immunity to the murine host. This process of humanisation is facilitated by novel immunocompromised mouse strains that allow a high engraftment rate of human cells or tissue. These humanised xenograft models provide an important research tool to study human biological processes of bone metastasis.
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A range of authors from the risk management, crisis management, and crisis communications literature have proposed different models as a means of understanding components of crisis. A generic component of these sources has focused on preparedness practices before disturbance events and response practices during events. This paper provides a critical analysis of three key explanatory models of how crises escalate highlighting the strengths and limitations of each approach. The paper introduces an optimised conceptual model utilising components from the previous work under the four phases of pre-event, response, recovery, and post-event. Within these four phases, a ten step process is introduced that can enhance understanding of the progression of distinct stages of disturbance for different types of events. This crisis evolution framework is examined as a means to provide clarity and applicability to a range of infrastructure failure contexts and provide a path for further empirical investigation in this area.
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The traditional hospital-based model of cardiac rehabilitation faces substantial challenges, such as cost and accessibility. These challenges have led to the development of alternative models of cardiac rehabilitation in recent years. The aim of this study was to identify and critique evidence for the effectiveness of these alternative models. A total of 22 databases were searched to identify quantitative studies or systematic reviews of quantitative studies regarding the effectiveness of alternative models of cardiac rehabilitation. Included studies were appraised using a Critical Appraisal Skills Programme tool and the National Health and Medical Research Council's designations for Level of Evidence. The 83 included articles described interventions in the following broad categories of alternative models of care: multifactorial individualized telehealth, internet based, telehealth focused on exercise, telehealth focused on recovery, community- or home-based, and complementary therapies. Multifactorial individualized telehealth and community- or home-based cardiac rehabilitation are effective alternative models of cardiac rehabilitation, as they have produced similar reductions in cardiovascular disease risk factors compared with hospital-based programmes. While further research is required to address the paucity of data available regarding the effectiveness of alternative models of cardiac rehabilitation in rural, remote, and culturally and linguistically diverse populations, our review indicates there is no need to rely on hospital-based strategies alone to deliver effective cardiac rehabilitation. Local healthcare systems should strive to integrate alternative models of cardiac rehabilitation, such as brief telehealth interventions tailored to individual's risk factor profiles as well as community- or home-based programmes, in order to ensure there are choices available for patients that best fit their needs, risk factor profile, and preferences.
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Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.
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This thesis describes the use of 2- and 3-dimensional cell-based models for studying how skin cells respond to ultraviolet radiation. These methods were used to investigate skin damage and repair after exposure to radiation in the context of skin cancer development. Interactions between different skin cell types were demonstrated as being significant in protecting against ultraviolet radiation-induced skin damage. This has important implications in understanding how skin cancers occur, as well as in the development of new strategies to prevent and treat them.
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This presentation discusses topics and issues that connect closely with the Conference Themes and themes in the ARACY Report Card. For example, developing models of public space that are safe, welcoming and relevant to children and young people will impact on their overall wellbeing and may help to prevent many of the tensions occurring in Australia and elsewhere around the world. This area is the subject of ongoing international debate, research and policy formation, relevant to concerns in the ARACY Report Card about children and young people’s health and safety, participation, behaviours and risks and peer and family relationships.
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This paper details the participation of the Australian e- Health Research Centre (AEHRC) in the ShARe/CLEF 2013 eHealth Evaluation Lab { Task 3. This task aims to evaluate the use of information retrieval (IR) systems to aid consumers (e.g. patients and their relatives) in seeking health advice on the Web. Our submissions to the ShARe/CLEF challenge are based on language models generated from the web corpus provided by the organisers. Our baseline system is a standard Dirichlet smoothed language model. We enhance the baseline by identifying and correcting spelling mistakes in queries, as well as expanding acronyms using AEHRC's Medtex medical text analysis platform. We then consider the readability and the authoritativeness of web pages to further enhance the quality of the document ranking. Measures of readability are integrated in the language models used for retrieval via prior probabilities. Prior probabilities are also used to encode authoritativeness information derived from a list of top-100 consumer health websites. Empirical results show that correcting spelling mistakes and expanding acronyms found in queries signi cantly improves the e ectiveness of the language model baseline. Readability priors seem to increase retrieval e ectiveness for graded relevance at early ranks (nDCG@5, but not precision), but no improvements are found at later ranks and when considering binary relevance. The authoritativeness prior does not appear to provide retrieval gains over the baseline: this is likely to be because of the small overlap between websites in the corpus and those in the top-100 consumer-health websites we acquired.
Resumo:
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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Mathematical models of mosquito-borne pathogen transmission originated in the early twentieth century to provide insights into how to most effectively combat malaria. The foundations of the Ross–Macdonald theory were established by 1970. Since then, there has been a growing interest in reducing the public health burden of mosquito-borne pathogens and an expanding use of models to guide their control. To assess how theory has changed to confront evolving public health challenges, we compiled a bibliography of 325 publications from 1970 through 2010 that included at least one mathematical model of mosquito-borne pathogen transmission and then used a 79-part questionnaire to classify each of 388 associated models according to its biological assumptions. As a composite measure to interpret the multidimensional results of our survey, we assigned a numerical value to each model that measured its similarity to 15 core assumptions of the Ross–Macdonald model. Although the analysis illustrated a growing acknowledgement of geographical, ecological and epidemiological complexities in modelling transmission, most models during the past 40 years closely resemble the Ross–Macdonald model. Modern theory would benefit from an expansion around the concepts of heterogeneous mosquito biting, poorly mixed mosquito-host encounters, spatial heterogeneity and temporal variation in the transmission process.
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In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modelling interactions between such species, we often make use of the mean field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean field approximation is only used in appropriate settings. In circumstances where the mean field approximation is unsuitable we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper we provide a method that overcomes many of the failures of the mean field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multi-species case, and show results specific to a two-species problem. We compare averaged discrete results to both the mean field approximation and our improved method which incorporates spatial correlations. We note that the mean field approximation fails dramatically in some cases, predicting very different behaviour from that seen upon averaging multiple realisations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behaviour in all cases, thus providing a more reliable modelling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.
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Electricity is the cornerstone of modern life. It is essential to economic stability and growth, jobs and improved living standards. Electricity is also the fundamental ingredient for a dignified life; it is the source of such basic human requirements as cooked food, a comfortable living temperature and essential health care. For these reasons, it is unimaginable that today's economies could function without electricity and the modern energy services that it delivers. Somewhat ironically, however, the current approach to electricity generation also contributes to two of the gravest and most persistent problems threatening the livelihood of humans. These problems are anthropogenic climate change and sustained human poverty. To address these challenges, the global electricity sector must reduce its reliance on fossil fuel sources. In this context, the object of this research is twofold. Initially it is to consider the design of the Renewable Energy (Electricity) Act 2000 (Cth) (Renewable Electricity Act), which represents Australia's primary regulatory approach to increase the production of renewable sourced electricity. This analysis is conducted by reference to the regulatory models that exist in Germany and Great Britain. Within this context, this thesis then evaluates whether the Renewable Electricity Act is designed effectively to contribute to a more sustainable and dignified electricity generation sector in Australia. On the basis of the appraisal of the Renewable Electricity Act, this thesis contends that while certain aspects of the regulatory regime have merit, ultimately its design does not represent an effective and coherent regulatory approach to increase the production of renewable sourced electricity. In this regard, this thesis proposes a number of recommendations to reform the existing regime. These recommendations are not intended to provide instantaneous or simple solutions to the current regulatory regime. Instead, the purpose of these recommendations is to establish the legal foundations for an effective regulatory regime that is designed to increase the production of renewable sourced electricity in Australia in order to contribute to a more sustainable and dignified approach to electricity production.
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Background Research is a major driver of health care improvement and evidence-based practice is becoming the foundation of health care delivery. For health professions to develop within emerging models of health care delivery, it would seem imperative to develop and monitor the research capacity and evidence-based literacy of the health care workforce. This observational paper aims to report the research capacity levels of statewide populations of public-sector podiatrists at two different time points twelve-months apart. Methods The Research Capacity & Culture (RCC) survey was electronically distributed to all Queensland Health (Australia) employed podiatrists in January 2011 (n = 58) and January 2012 (n = 60). The RCC is a validated tool designed to measure indicators of research skill in health professionals. Participants rate skill levels against each individual, team and organisation statement on a 10-point scale (one = lowest, ten = highest). Chi-squared and Mann Whitney U tests were used to determine any differences between the results of the two survey samples. A minimum significance of p < 0.05 was used throughout. Results Thirty-seven (64%) podiatrists responded to the 2011 survey and 33 (55%) the 2012 survey. The 2011 survey respondents reported low skill levels (Median < 4) on most aspects of individual research aspects, except for their ability to locate and critically review research literature (Median > 6). Whereas, most reported their organisation’s skills to perform and support research at much higher levels (Median > 6). The 2012 survey respondents reported significantly higher skill ratings compared to the 2011 survey in individuals’ ability to secure research funding, submit ethics applications, and provide research advice, plus, in their organisation’s skills to support, fund, monitor, mentor and engage universities to partner their research (p < 0.05). Conclusions This study appears to report the research capacity levels of the largest populations of podiatrists published. The 2011 survey findings indicate podiatrists have similarly low research capacity skill levels to those reported in the allied health literature. The 2012 survey, compared to the 2011 survey, suggests podiatrists perceived higher skills and support to initiate research in 2012. This improvement coincided with the implementation of research capacity building strategies.
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Background. As a society, our interaction with the environment is having a negative impact on human health. For example, an increase in car use for short trips, over walking or cycling, has contributed to an increase in obesity, diabetes and poor heart health and also contributes to pollution, which is associated with asthma and other respiratory diseases. In order to change the nature of that interaction, to be more positive and healthy, it is recommended that individuals adopt a range of environmentally friendly behaviours (such as walking for transport and reducing the use of plastics). Effective interventions aimed at increasing such behaviours will need to be evidence based and there is a need for the rapid communication of information from the point of research, into policy and practice. Further, a number of health disciplines, including psychology and public health, share a common mission to promote health and well-being. Therefore, the objective of this project is to take a cross-discipline and collaborative approach to reveal psychological mechanisms driving environmentally friendly behaviour. This objective is further divided into three broad aims, the first of which is to take a cross-discipline and collaborative approach to research. The second aim is to explore and identify the salient beliefs which most strongly predict environmentally friendly behaviour. The third aim is to build an augmented model to explain environmentally friendly behaviour. The thesis builds on the understanding that an interdisciplinary collaborative approach will facilitate the rapid transfer of knowledge to inform behaviour change interventions. Methods. The application of this approach involved two surveys which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in collaboration with an expert panel comprising academics, industry professionals and government representatives, a self-administered, Theory of Planned Behaviour (TPB) based, mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay Region (Queensland, Australia). This survey explored specific beliefs including attitudes, norms, perceived control, intention and behaviour, as well as environmental altruism and green identity, in relation to walking for transport and switching off lights when not in use. Following analysis of the mail survey data and based on feedback from participants and key stakeholders, an internet survey was employed (N=451) to explore two additional behaviours, switching off appliances at the wall when not in use, and shopping with reusable bags. This work is presented as a series of interrelated publications which address each of the research aims. Presentation of Findings. Chapter five of this thesis consists of a published paper which addresses the first aim of the research and outlines the collaborative and multidisciplinary approach employed in the mail survey. The paper argued that forging alliances with those who are in a position to immediately utilise the findings of research has the potential to improve the quality and timely communication of research. Illustrating this timely communication, Chapter six comprises a report presented to Moreton Bay Regional Council (MBRC). This report addresses aim's one and two. The report contains a summary of participation in a range of environmentally friendly behaviours and identifies the beliefs which most strongly predicted walking for transport and switching off lights (from the mail survey). These salient beliefs were then recommended as targets for interventions and included: participants believing that they might save money; that their neighbours also switch off lights; that it would be inconvenient to walk for transport and that their closest friend also walks for transport. Chapter seven also addresses the second aim and presents a published conference paper in which the salient beliefs predicting the four specified behaviours (from both surveys) are identified and potential applications for intervention are discussed. Again, a range of TPB based beliefs, including descriptive normative beliefs, were predictive of environmentally friendly behaviour. This paper was also provided to MBRC, along with recommendations for applying the findings. For example, as descriptive normative beliefs were consistently correlated with environmentally friendly behaviour, local councils could engage in marketing and interventions (workshops, letter box drops, internet promotions) which encourage parents and friends to model, rather than simply encourage, environmentally friendly behaviour. The final two papers, presented in Chapters eight and nine, addresses the third aim of the project. These papers each present two behaviours together to inform a TPB based theoretical model with which to predict environmentally friendly behaviour. A generalised model is presented, which is found to predict the four specific behaviours under investigation. The role of demographics was explored across each of the behaviour specific models. It was found that some behaviour's differ by age, gender, income or education. In particular, adjusted models predicted more of the variance in walking for transport amongst younger participants and females. Adjusted models predicted more variance in switching off lights amongst those with a bachelor degree or higher and predicted more variance in switching off appliances amongst those on a higher income. Adjusted models predicted more variance in shopping with reusable bags for males, people 40 years or older, those on a higher income and those with a bachelor degree or higher. However, model structure and general predictability was relatively consistent overall. The models provide a general theoretical framework from which to better understand the motives and predictors of environmentally friendly behaviour. Conclusion. This research has provided an example of the benefits of a collaborative interdisciplinary approach. It has identified a number of salient beliefs which can be targeted for social marketing campaigns and educational initiatives; and these findings, along with recommendations, have been passed on to a local council to be used as part of their ongoing community engagement programs. Finally, the research has informed a practical model, as well as behaviour specific models, for predicting sustainable living behaviours. Such models can highlight important core constructs from which targeted interventions can be designed. Therefore, this research represents an important step in undertaking collaborative approaches to improving population health through human-environment interactions.
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Introduction. The purpose of this chapter is to address the question raised in the chapter title. Specifically, how can models of motor control help us understand low back pain (LBP)? There are several classes of models that have been used in the past for studying spinal loading, stability, and risk of injury (see Reeves and Cholewicki (2003) for a review of past modeling approaches), but for the purpose of this chapter we will focus primarily on models used to assess motor control and its effect on spine behavior. This chapter consists of 4 sections. The first section discusses why a shift in modeling approaches is needed to study motor control issues. We will argue that the current approach for studying the spine system is limited and not well-suited for assessing motor control issues related to spine function and dysfunction. The second section will explore how models can be used to gain insight into how the central nervous system (CNS) controls the spine. This segues segue nicely into the next section that will address how models of motor control can be used in the diagnosis and treatment of LBP. Finally, the last section will deal with the issue of model verification and validity. This issue is important since modelling accuracy is critical for obtaining useful insight into the behavior of the system being studied. This chapter is not intended to be a critical review of the literature, but instead intended to capture some of the discussion raised during the 2009 Spinal Control Symposium, with some elaboration on certain issues. Readers interested in more details are referred to the cited publications.