714 resultados para health failure

em Queensland University of Technology - ePrints Archive


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Objective For more than ten years the public health and health promotion workforce in the Australian state of Queensland grew dramatically. This growth was most pronounced in the disciplines of Health Promotion and in Public Health Nutrition, both regionally and corporately. In 2012 political change led to an abrupt dismantling of its public and preventive health services across the state. Individual responsibility was declared. Method This presentation provides a qualitative narrative description of past achievements and activities, the current situation and provides a perspective towards the future. Findings Government reports over several years described the growing burden of chronic disease arising from conditions such as obesity, physical inactivity, and poor nutrition in Queensland. By 2008, obesity had overtaken smoking as the single greatest risk factor to the health of Queenslanders. In 2010, the Chief Health Officer called for an increased focus on prevention to address the continuing need for more beds in hospitals. However, with political change in 2012 resulted in the dismantling and dismissal of preventive health services across the state. The following year, despite outcry, sexual health services were also axed. At present, outbreaks of vaccine preventable diseases such as measles are occurring. The epidemics of chronic disease, obesity and physical inactivity continue to grow. Conclusion The evolution of public health is not necessarily progressive, but cyclic. Challenges include political change, health practice and the interplay of health policy. A lack of an embedded emphasis on systematic review translation is one potential contributor. Perhaps the warning of Lang & Rayner should be heeded: “public health proponents have allowed themselves to be corralled into the narrow language of individualism and choice”.

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This paper proposes a new prognosis model based on the technique for health state estimation of machines for accurate assessment of the remnant life. For the evaluation of health stages of machines, the Support Vector Machine (SVM) classifier was employed to obtain the probability of each health state. Two case studies involving bearing failures were used to validate the proposed model. Simulated bearing failure data and experimental data from an accelerated bearing test rig were used to train and test the model. The result obtained is very encouraging and shows that the proposed prognostic model produces promising results and has the potential to be used as an estimation tool for machine remnant life prediction.

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Public health decision making is critically dependant on accurate, timely and reliable information. There is a widespread belief that most of the national and sub-national health information systems fail in providing much needed information support for evidence based health planning and interventions. This situation is more acute in developing nations where resources are either stagnant or decreasing, coupled with the situations of demographic transition and double burden of diseases. Literature abounds with publications, which provide information on misguided health interventions in developing nations, leading to failure and waste of resources. Health information system failure is widely blamed for this situation. Nevertheless, there is a dearth of comprehensive evaluations of existing national or sub-national health information systems, especially in the region of South-East Asia. This study makes an attempt to bridge this knowledge gap by evaluating a regional health information system in Sri Lanka. It explores the strengths and weaknesses of the current health information system and related causative factors in a decentralised health system and then proposes strategic recommendations for reform measures. A mix methodological and phased approach was adopted to reach the objectives. An initial self administered questionnaire survey was conducted among health managers to study their perceptions in relation to the regional health information system and its management support. The survey findings were used to establish the presence of health information system failure in the region and also as a precursor to the more in-depth case study which was followed. The sources of data for the case study were literature review, document analysis and key stake holder interviews. Health information system resources, health indicators, data sources, data management, data quality, and information dissemination were the six major components investigated. The study findings reveal that accurate, timely and reliable health information is unavailable and therefore evidence based health planning is lacking in the studied health region. Strengths and weaknesses of the current health information system were identified and strategic recommendations were formulated accordingly. It is anticipated that this research will make a significant and multi-fold contribution for health information management in developing countries. First, it will attempt to bridge an existing knowledge gap by presenting the findings of a comprehensive case study to reveal the strengths and weaknesses of a decentralised health information system in a developing country. Second, it will enrich the literature by providing an assessment tool and a research method for the evaluation of regional health information systems. Third, it will make a rewarding practical contribution by presenting valuable guidelines for improving health information systems in regional Sri Lanka.

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Purpose: Heart failure (HF) is the leading cause of hospitalization and significant burden to the health care system in Australia. To reduce hospitalizations, multidisciplinary approaches and enhance self-management programs have been strongly advocated for HF patients globally. HF patients who can effectively manage their symptoms and adhere to complex medicine regimes will experience fewer hospitalizations. Research indicates that information technologies (IT) have a significant role in providing support to promote patients' self-management skills. The iPad utilizes user-friendly interfaces and to date an application for HF patient education has not been developed. This project aimed to develop the HF iPad teaching application in the way that would be engaging, interactive and simple to follow and usable for patients' carers and health care workers within both the hospital and community setting. Methods: The design for the development and evaluation of the application consisted of two action research cycles. Each cycle included 3 phases of testing and feedback from three groups comprising IT team, HF experts and patients. All patient education materials of the application were derived from national and international evidence based practice guidelines and patient self-care recommendations. Results: The iPad application has animated anatomy and physiology that simply and clearly teaches the concepts of the normal heart and the heart in failure. Patient Avatars throughout the application can be changed to reflect the sex and culture of the patient. There is voice-over presenting a script developed by the heart failure expert panel. Additional engagement processes included points of interaction throughout the application with touch screen responses and the ability of the patient to enter their weight and this data is secured and transferred to the clinic nurse and/or research data set. The application has been used independently, for instance, at home or using headphones in a clinic waiting room or most commonly to aid a nurse-led HF consultation. Conclusion: This project utilized iPad as an educational tool to standardize HF education from nurses who are not always heart failure specialists. Furthermore, study is currently ongoing to evaluate of the effectiveness of this tool on patient outcomes and to develop several specifically designed cultural adaptations [Hispanic (USA), Aboriginal (Australia), and Maori (New Zealand)].

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Aims This paper is a report on the effectiveness of a self-management programme based on the self-efficacy construct, in older people with heart failure. Background Heart failure is a major health problem worldwide, with high mortality and morbidity, making it a leading cause of hospitalization. Heart failure is associated with a complex set of symptoms that arise from problems in fluid and sodium retention. Hence, managing salt and fluid intake is important and can be enhanced by improving patients' self-efficacy in changing their behaviour. Design Randomized controlled trial. Methods Heart failure patients attending cardiac clinics in northern Taiwan from October 2006–May 2007 were randomly assigned to two groups: control (n = 46) and intervention (n = 47). The intervention group received a 12-week self-management programme that emphasized self-monitoring of salt/fluid intake and heart failure-related symptoms. Data were collected at baseline as well as 4 and 12 weeks later. Data analysis to test the hypotheses used repeated-measures anova models. Results Participants who received the intervention programme had significantly better self-efficacy for salt and fluid control, self-management behaviour and their heart failure-related symptoms were significantly lower than participants in the control group. However, the two groups did not differ significantly in health service use. Conclusion The self-management programme improved self-efficacy for salt and fluid control, self-management behaviours, and decreased heart failure-related symptoms in older Taiwanese outpatients with heart failure. Nursing interventions to improve health-related outcomes for patients with heart failure should emphasize self-efficacy in the self-management of their disease.

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Introduction: Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (Nmm−1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived froma single 2D radiographic image. Methods: 18 excised human femora had previously been quantitative computed tomography scanned, from which 2D BMD-equivalent radiographic images were derived, and mechanically tested to failure in a stance-loading configuration. A 3D proximal femur shape was generated from each 2D radiographic image and used to construct 3D-FEA models. Results: The coefficient of determination (R2%) to predict failure load was 54.5% for BMD and 80.4% for 3D-FEXI. Conclusions: This ex vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD. This approach may be readily extended to routine clinical BMD images derived by dual energy X-ray absorptiometry. Crown Copyright © 2009 Published by Elsevier Ltd on behalf of IPEM. All rights reserved

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There is a growing body of literature within social and cultural geography that explores notions of place, space, culture, race and identity. The more recent works suggest that places are experienced and understood in multiple ways and are embedded within an array of politics. Memmott and Long, who have undertaken place-based research with Australian Indigenous people, present the theoretical position that ‘place is made and takes on meaning through an interaction process involving mutual accommodation between people and the environment’. They outline that places and their cultural meanings are generated through one or a combination of three types of people–environment interactions. These include: a place that is created by altering the physical characteristics of a piece of environment and which might encompass a feature or features which are natural or made; a place that is created totally through behaviour that is carried out within a specific area, therefore that specific behaviour becomes connected to that specific place; and a place created by people moving or being moved from one environment to another and establishing a new place where boundaries are created and activities carried out. All these ideas of places are challenged and confirmed by what Indigenous women have said about their particular use of, and relationship with, space within several health services in Rockhampton, Central Queensland. As my title suggests, Indigenous women do not see themselves as ‘neutral’ or ‘non-racialised’ citizens who enter and ‘use’ a supposedly neutral health service. Instead, Aboriginal women demonstrate they are active recognisers of places that would identify them within the particular health place. That is, they as Aboriginal women didn’t just ‘make’ place, the places and spaces ‘make’ them. The health services were identified as sites within which spatial relations could begin to grow with recognition of themselves as Aboriginal women in place, or instead create a sense of marginality in the failure of the spaces to identify them. The women’s voices within this paper are drawn from interviews undertaken with twenty Aboriginal women in Rockhampton, Central Queensland, Australia, who participated in a research project exploring ‘how the relationship between health services and Aboriginal women can be more empowering from the viewpoints of Aboriginal women’. The assumption underpinning this study was that empowering and re-empowering practices for Aboriginal women can lead to improved health outcomes. Throughout the interviews women shared some of their lived realities including some of their thoughts on identity, the body, employment in the health sector, service delivery and their notions of health service spaces and places. Their thoughts on health service spaces and places provide an understanding of the lived reality for Aboriginal women and are explored and incorporated within this paper.

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Bone mineral density (BMD) is currently the preferred surrogate for bone strength in clinical practice. Finite element analysis (FEA) is a computer simulation technique that can predict the deformation of a structure when a load is applied, providing a measure of stiffness (N mm− 1). Finite element analysis of X-ray images (3D-FEXI) is a FEA technique whose analysis is derived from a single 2D radiographic image. This ex-vivo study demonstrates that 3D-FEXI derived from a conventional 2D radiographic image has the potential to significantly increase the accuracy of failure load assessment of the proximal femur compared with that currently achieved with BMD.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

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Bridges are an important part of society's infrastructure and reliable methods are necessary to monitor them and ensure their safety and efficiency. Bridges deteriorate with age and early detection of damage helps in prolonging the lives and prevent catastrophic failures. Most bridges still in used today were built decades ago and are now subjected to changes in load patterns, which can cause localized distress and if not corrected can result in bridge failure. In the past, monitoring of structures was usually done by means of visual inspection and tapping of the structures using a small hammer. Recent advancements of sensors and information technologies have resulted in new ways of monitoring the performance of structures. This paper briefly describes the current technologies used in bridge structures condition monitoring with its prime focus in the application of acoustic emission (AE) technology in the monitoring of bridge structures and its challenges.

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Management of acute heart failure is an important consideration in critical care. Mechanical support of the failing heart is crucial for improving health outcomes. The most common Australasian application of intraaortic balloon counterpulsation (IABP) is in the setting of cardiogenic shock. High end users of IABP (>37/annum) demonstrate significantly lower mortality for cardiogenic shock managed with IABP (p <0.001) in contrast to hospitals which employ limited IABP (<4/annum). This underscores the importance of proficiency in managing patient receiving IABP support. Nurses play a crucial role in carding for patients with acute heart failure. This paper summarises care considerations for management of the IABP.

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Costly hospital readmissions among chronic heart failure (CHF) patients are expected to increase dramatically with the ageing population. This study investigated the prognostic ability of depression, anger and anxiety, prospectively, and after adjusting for illness severity, on the number of readmissions to hospital and the total length of stay over one year. Participants comprised 175 inpatients with CHF. Depression, anger, anxiety, and illness severity were measured at baseline. One year later, the number of readmissions and length of stay for each patient were obtained from medical records. Depression and anger play a detrimental role in the health profile of CHF patients.

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Establishing a nationwide Electronic Health Record system has become a primary objective for many countries around the world, including Australia, in order to improve the quality of healthcare while at the same time decreasing its cost. Doing so will require federating the large number of patient data repositories currently in use throughout the country. However, implementation of EHR systems is being hindered by several obstacles, among them concerns about data privacy and trustworthiness. Current IT solutions fail to satisfy patients’ privacy desires and do not provide a trustworthiness measure for medical data. This thesis starts with the observation that existing EHR system proposals suer from six serious shortcomings that aect patients’ privacy and safety, and medical practitioners’ trust in EHR data: accuracy and privacy concerns over linking patients’ existing medical records; the inability of patients to have control over who accesses their private data; the inability to protect against inferences about patients’ sensitive data; the lack of a mechanism for evaluating the trustworthiness of medical data; and the failure of current healthcare workflow processes to capture and enforce patient’s privacy desires. Following an action research method, this thesis addresses the above shortcomings by firstly proposing an architecture for linking electronic medical records in an accurate and private way where patients are given control over what information can be revealed about them. This is accomplished by extending the structure and protocols introduced in federated identity management to link a patient’s EHR to his existing medical records by using pseudonym identifiers. Secondly, a privacy-aware access control model is developed to satisfy patients’ privacy requirements. The model is developed by integrating three standard access control models in a way that gives patients access control over their private data and ensures that legitimate uses of EHRs are not hindered. Thirdly, a probabilistic approach for detecting and restricting inference channels resulting from publicly-available medical data is developed to guard against indirect accesses to a patient’s private data. This approach is based upon a Bayesian network and the causal probabilistic relations that exist between medical data fields. The resulting definitions and algorithms show how an inference channel can be detected and restricted to satisfy patients’ expressed privacy goals. Fourthly, a medical data trustworthiness assessment model is developed to evaluate the quality of medical data by assessing the trustworthiness of its sources (e.g. a healthcare provider or medical practitioner). In this model, Beta and Dirichlet reputation systems are used to collect reputation scores about medical data sources and these are used to compute the trustworthiness of medical data via subjective logic. Finally, an extension is made to healthcare workflow management processes to capture and enforce patients’ privacy policies. This is accomplished by developing a conceptual model that introduces new workflow notions to make the workflow management system aware of a patient’s privacy requirements. These extensions are then implemented in the YAWL workflow management system.

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The high levels of end-stage renal disease among Indigenous Australians, particularly in remote areas of the country, are a serious public health concern. The magnitude of the problem is reflected in figures from the Australian and New Zealand Transplant and Dialysis Registry that show that Indigenous Australians experience end-stage renal disease at a rate almost 9–10 times higher than other non-Indigenous Australians. A majority of Indigenous Australians have to relocate to receive appropriate renal dialysis treatment. In some Australian states, renal treatment is based on self-care dialysis which allows those Indigenous Australians to be treated back in their community. Evidence clearly shows that reuniting renal patients with community and family improves overall health and well-being for those Indigenous Australians. With the appropriate resources, training, and support, self-care management of renal dialysis treatment is an effective way for Indigenous people with end-stage renal failure to be treated at home. In this context, the study was used to gain insight and further understanding of the impact that end-stage renal disease and renal dialysis treatment has had on the lives of Indigenous community members. The study findings are from 14 individually interviewed people from South East Queensland. Data from the interviews were analysed using a combination of thematic and content analysis. The study methodology was based on qualitative data principles where the Indigenous community members were able to share their experiences and journeys living with end-stage renal disease. Many of the experiences and understanding closely relate to the renal disease pattern and the treatment with other outside influences, such as social, cultural, and environmental influences, all having an equal impact. Each community member’s experience with end-stage renal disease is unique; some manage with family and medical support, while others try to manage independently. From the study, community members who managed their renal dialysis treatment independently were much more aware of their renal health status. The study provides recommendations towards a model of care to improve the health and well-being is based on self-care and self-determination principles.