980 resultados para Emergency Vehicle Drivers.
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Objective The aim of this study was to gather patients' perceptions regarding their choice between public and private hospital EDs for those who hold private health insurance. The findings of this study will contribute to knowledge regarding patients' decision-making processes and therefore may contribute to the development of evidence based public policies. Methods An in-depth semi-structured guide was used to interview participants at public and private hospital EDs. Questions sought to identify the issues that were considered by the participants to decide to attend that hospital ED, previous ED experience, expectations of ED services and perceived benefits and barriers to accessing services. Interviews were audio recorded, transcribed verbatim and analysed using content and thematic approaches. Results Four core themes emerged: prior good experience with the hospital, perceived quality of care, perceived waiting times and perceived costs that may explain patients' choice. Patients' choice between public and private EDs can be explained by the interaction of these core themes. The principal issues appear to be concern for gap payments at private hospital ED and waiting times at public hospital ED. Conclusions Patients who choose to attend public EDs appear to value financial concern over waiting time; those who choose to attend private EDs appear to value waiting time ahead of financial concerns.
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Objectives: We sought to characterise the demographics, length of admission, final diagnoses, long-term outcome and costs associated with the population who presented to an Australian emergency department (ED) with symptoms of possible acute coronary syndrome (ACS). Design, setting and participants: Prospectively collected data on ED patients presenting with suspected ACS between November 2008 and February 2011 was used, including data on presentation and at 30 days after presentation. Information on patient disposition, length of stay and costs incurred was extracted from hospital administration records. Main outcome measures: Primary outcomes were mean and median cost and length of hospital stay. Secondary outcomes were diagnosis of ACS, other cardiovascular conditions or non-cardiovascular conditions within 30 days of presentation. Results: An ACS was diagnosed in 103 (11.1%) of the 926 patients recruited. 193 patients (20.8%) were diagnosed with other cardiovascular-related conditions and 622 patients (67.2%) had non-cardiac-related chest pain. ACS events occurred in 0 and 11 (1.9%) of the low-risk and intermediate-risk groups, respectively. Ninety-two (28.0%) of the 329 high-risk patients had an ACS event. Patients with a proven ACS, high-grade atrioventricular block, pulmonary embolism and other respiratory conditions had the longest length of stay. The mean cost was highest in the ACS group ($13 509; 95% CI, $11 794–$15 223) followed by other cardiovascular conditions ($7283; 95% CI, $6152–$8415) and non-cardiovascular conditions ($3331; 95% CI, $2976–$3685). Conclusions: Most ED patients with symptoms of possible ACS do not have a cardiac cause for their presentation. The current guideline-based process of assessment is lengthy, costly and consumes significant resources. Investigation of strategies to shorten this process or reduce the need for objective cardiac testing in patients at intermediate risk according to the National Heart Foundation and Cardiac Society of Australia and New Zealand guideline is required.
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- Objective This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). - Methods Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. - Results Chronic disease risks were high (e.g. 97% high waist circumference [≥94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1–4=8,743[SD 2,867] steps/day; weeks 17–20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1–4=38[IQR 21]%; weeks 17–20=58[IQR 18]%). - Conclusions Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. - Implications Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.
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An economic survey of the commercial operators currently active in the Queensland Coral Reef Fin-Fish Fishery has been carried out, as part of a research project aimed at evaluating alternative management options for this fishery. This paper presents the background analysis used as a basis to develop the sampling design for this survey. The background analysis focuses on activity patterns of the fleet based on effort and catch information, as well as patterns of quota ownership. Based on this information, a fishing business profile describing the micro-economic structure of fishing operations is developed. This profile, in conjunction with the qualitative information gained in undertaking the economic surveys, allows preliminary understanding of the key drivers of profitability in the CRFFF, and possible impacts of external factors on fishing operations.
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The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.
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Background There has been considerable publicity regarding population ageing and hospital emergency department (ED) overcrowding. Our study aims to investigate impact of one intervention piloted in Queensland Australia, the Hospital in the Nursing Home (HiNH) program, on reducing ED and hospital attendances from residential aged care facilities (RACFs). Methods A quasi-experimental study was conducted at an intervention hospital undertaking the program and a control hospital with normal practice. Routine Queensland health information system data were extracted for analysis. Results Significant reductions in the number of ED presentations per 1000 RACF beds (rate ratio (95 % CI): 0.78 (0.67–0.92); p = 0.002), number of hospital admissions per 1000 RACF beds (0.62 (0.50–0.76); p < 0.0001), and number of hospital admissions per 100 ED presentations (0.61 (0.43–0.85); p = 0.004) were noticed in the experimental hospital after the intervention; while there were no significant differences between intervention and control hospitals before the intervention. Pre-test and post-test comparison in the intervention hospital also presented significant decreases in ED presentation rate (0.75 (0.65–0.86); p < 0.0001) and hospital admission rate per RACF bed (0.66 (0.54–0.79); p < 0.0001), and a non-significant reduction in hospital admission rate per ED presentation (0.82 (0.61–1.11); p = 0.196). Conclusions Hospital in the Nursing Home program could be effective in reducing ED presentations and hospital admissions from RACF residents. Implementation of the program across a variety of settings is preferred to fully assess the ongoing benefits for patients and any possible cost-savings.
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Development of no-tillage (NT) farming has revolutionized agricultural systems by allowing growers to manage greater areas of land with reduced energy, labour and machinery inputs to control erosion, improve soil health and reduce greenhouse gas emission. However, NT farming systems have resulted in a build-up of herbicide-resistant weeds, an increased incidence of soil- and stubble-borne diseases and enrichment of nutrients and carbon near the soil surface. Consequently, there is an increased interest in the use of an occasional tillage (termed strategic tillage, ST) to address such emerging constraints in otherwise-NT farming systems. Decisions around ST uses will depend upon the specific issues present on the individual field or farm, and profitability and effectiveness of available options for management. This paper explores some of the issues with the implementation of ST in NT farming systems. The impact of contrasting soil properties, the timing of the tillage and the prevailing climate exert a strong influence on the success of ST. Decisions around timing of tillage are very complex and depend on the interactions between soil water content and the purpose for which the ST is intended. The soil needs to be at the right water content before executing any tillage, while the objective of the ST will influence the frequency and type of tillage implement used. The use of ST in long-term NT systems will depend on factors associated with system costs and profitability, soil health and environmental impacts. For many farmers maintaining farm profitability is a priority, so economic considerations are likely to be a primary factor dictating adoption. However, impacts on soil health and environment, especially the risk of erosion and the loss of soil carbon, will also influence a grower’s choice to adopt ST, as will the impact on soil moisture reserves in rainfed cropping systems.
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Escalating health care delivery costs and consumer expectations have led to a range of health service and workforce innovations in the provision of high quality cost effective patient care. This research has operationalised a theoretical framework to examine factors that influence sustainability of health service innovations, in particular, emergency nurse practitioner service. The results of this research will inform health service policy and practice for future implementation of innovative workforce models and add to the understanding of factors that influence sustainability.
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Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.
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- Objective To compare health service cost and length of stay between a traditional and an accelerated diagnostic approach to assess acute coronary syndromes (ACS) among patients who presented to the emergency department (ED) of a large tertiary hospital in Australia. - Design, setting and participants This historically controlled study analysed data collected from two independent patient cohorts presenting to the ED with potential ACS. The first cohort of 938 patients was recruited in 2008–2010, and these patients were assessed using the traditional diagnostic approach detailed in the national guideline. The second cohort of 921 patients was recruited in 2011–2013 and was assessed with the accelerated diagnostic approach named the Brisbane protocol. The Brisbane protocol applied early serial troponin testing for patients at 0 and 2 h after presentation to ED, in comparison with 0 and 6 h testing in traditional assessment process. The Brisbane protocol also defined a low-risk group of patients in whom no objective testing was performed. A decision tree model was used to compare the expected cost and length of stay in hospital between two approaches. Probabilistic sensitivity analysis was used to account for model uncertainty. - Results Compared with the traditional diagnostic approach, the Brisbane protocol was associated with reduced expected cost of $1229 (95% CI −$1266 to $5122) and reduced expected length of stay of 26 h (95% CI −14 to 136 h). The Brisbane protocol allowed physicians to discharge a higher proportion of low-risk and intermediate-risk patients from ED within 4 h (72% vs 51%). Results from sensitivity analysis suggested the Brisbane protocol had a high chance of being cost-saving and time-saving. - Conclusions This study provides some evidence of cost savings from a decision to adopt the Brisbane protocol. Benefits would arise for the hospital and for patients and their families.
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This paper presents a Dubins model based strategy to determine the optimal path of a Miniature Air Vehicle (MAV), constrained by a bounded turning rate, that would enable it to fly along a given straight line, starting from an arbitrary initial position and orientation. The method is then extended to meet the same objective in the presence of wind which has a magnitude comparable to the speed of the MAV. We use a modification of the Dubins' path method to obtain the complete optimal solution to this problem in all its generality.
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This paper extends the iterative linear matrix inequality algorithm (ILMI) for systems having non-ideal PI, PD and PID implementations. The new algorithm uses the practical implementation of the feedback blocksto form the equivalent static output feedback plant. The LMI based synthesis techniques are used in the algorithm to design a multi-loop, multi-objective fixed structure control. The benefits of such a control design technique are brought out by applying it to the lateral stabilizing and tracking feedback control problem of a 30cm wingspan micro air vehicle.