221 resultados para Emergency medical system


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In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

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- Objective To explore the potential for using a basic text search of routine emergency department data to identify product-related injury in infants and to compare the patterns from routine ED data and specialised injury surveillance data. - Methods Data was sourced from the Emergency Department Information System (EDIS) and the Queensland Injury Surveillance Unit (QISU) for all injured infants between 2009 and 2011. A basic text search was developed to identify the top five infant products in QISU. Sensitivity, specificity, and positive predictive value were calculated and a refined search was used with EDIS. Results were manually reviewed to assess validity. Descriptive analysis was conducted to examine patterns between datasets. - Results The basic text search for all products showed high sensitivity and specificity, and most searches showed high positive predictive value. EDIS patterns were similar to QISU patterns with strikingly similar month-of-age injury peaks, admission proportions and types of injuries. - Conclusions This study demonstrated a capacity to identify a sample of valid cases of product-related injuries for specified products using simple text searching of routine ED data. - Implications As the capacity for large datasets grows and the capability to reliably mine text improves, opportunities for expanded sources of injury surveillance data increase. This will ultimately assist stakeholders such as consumer product safety regulators and child safety advocates to appropriately target prevention initiatives.

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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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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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Within coronial investigations, pathologists are called upon to given evidence as to cause of death. This evidence is given great weight by the coroners; after all, scientific ‘truth’ is widely deemed to be far more reliable than legal ‘opinion’. The purpose of this paper is to examine the ontological and epistemological status of that evidence, from the perspectives of both the pathologists and the coroners. As part of an Australian Research Council Linkage Grant, interviews were conducted with seven pathologists and 10 coroners from within the Queensland coronial system. Contrary to expectations, and the work of philosophers of science, such as Feyerabend (1975), pathologists did not present their findings in terms of unequivocal facts or objective truths relating to causes of death. Rather, their evidence was largely presented as ‘educated opinion’ based upon ‘the weight of evidence’. It was actually the coroners who translated that opinion into ‘medical fact’ within the proceedings of their death investigations, arguably as a consequence of the administrative necessity to reach a clear-cut finding as to cause of death, and on the basis of their own understanding of the ontology of medical knowledge. These findings support Latour’s (2010) claim that law requires a fundamentally different epistemology to science, and that science is not entirely to blame for the extravagant truth-claims made on its behalf

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One could argue that the nature of our housing stock is a key determining factor in the ability of our citizens to manage risk, be resilient to various natural and human events, and to recover from these events. Recent research has been examining current challenges posed by our housing stock and exploring potential solutions from a range of perspectives. The aim of this paper is to discuss key findings from recent built environment research in Australia to initiate cross-sectorial discussion and debate about the implications and opportunities for other sectors such as emergency management and insurance. Three recent building research projects are discussed: - Heat waves The impact of heat waves on houses and occupants, and proposed changes to building regulations, air conditioning standards and building design, to reduce risks associated with heat waves. - Net zero energy homes Exploration of the potential benefits of a strategic optimization of building quality, energy and water efficiency, and household or community level distributed energy and water services for disaster management and recovery. - Building information Mapping of the flow of information about residential buildings, and the potential for national or regional building files (in a similar manner to personal medical records) to assist all parties to make more informed decisions that impact on housing sustainability and community resilience. The paper discusses how sustainability, environmental performance and resilience are inter-related, and can be supported by building files. It concludes with a call for increased cross-sectorial collaboration to explore opportunities for a whole-of-systems approach to our built environment that addresses a range of economic and environmental challenges as well as disaster and emergency management.

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Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

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This study sought to assess the extent to which the entry characteristics of students in a graduate-entry medical programme predict the subsequent development of clinical reasoning ability. Subjects comprised 290 students voluntarily recruited from three successive cohorts of the University of Queensland's MBBS Programme. Clinical reasoning was measured once a year over a period of three years using two methods, a set of 10 Clinical Reasoning Problems (CRPs) and the Diagnostic Thinking Inventory (DTI). Data on gender, age at entry into the programme, nature of primary degree, scores on selection criteria (written examination plus interview) and academic performance in the first two years of the programme were recorded for each student, and their association with clinical reasoning skill analysed using univariate and multivariate analysis. Univariate analysis indicated significant associations between CRP score, gender and primary degree with a significant but small association between DTI and interview score. Stage of progression through the programme was also an important predictor of performance on both indicators. Subsequent multivariate analysis suggested that female gender is a positive predictor of CRP score independently of the nature of a subject's primary degree and stage of progression through the programme, although these latter two variables are interdependent. Positive predictors of clinical reasoning skill are stage of progression through the MBBS programme, female gender and interview score. Although the nature of a student's primary degree is important in the early years of the programme, evidence suggests that by graduation differences between students' clinical reasoning skill due to this factor have been resolved.

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Objective: To evaluate the feasibility, reliability and acceptability of the mini clinical evaluation exercise (mini-CEX) for performance assessment among international medical graduates (IMGs). Design, setting and participants: Observational study of 209 patient encounters involving 28 IMGs and 35 examiners at three metropolitan teaching hospitals in New South Wales, Victoria and Queensland, September-December 2006. Main outcome measures: The reliability of the mini-CEX was estimated using generatisability (G) analysis, and its acceptability was evaluated by a written survey of the examiners and IMGs. Results: The G coefficient for eight encounters was 0.88, suggesting that the reliability of the mini-CEX was 0.90 for 10 encounters. Almost half of the IMGs (7/16) and most examiners (14/18) were satisfied with the mini-CEX as a learning tool. Most of the IMGs and examiners enjoyed the immediate feedback, which is a strong component of the tool. Conclusion: The mini-CEX is a reliable tool for performance assessment of IMGs, and is acceptable to and well received by both learners and supervisors.

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The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.

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This paper describes how a Hospital Social Work Department's Emergency Team has attempted to provide a crisis and out-of-hours service to its Emergency Department. Through a staffing commitment to extensive evening and weekend cover, the Emergency Team's social worker is able to provide an immediate intervention and assessment service to problems. This has resulted in early detection and treatment of the non-medical aspects of a patient's problem and appropriate referral to other agencies for longer-term follow-up.