746 resultados para Communication in healthcare
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This paper proposes millimeter wave (mmWave) mobile broadband for achieving secure communication in downlink cellular network. Analog beamforming with phase shifters is adopted for the mmWave transmission. The secrecy throughput is analyzed based on two different transmission modes, namely delay-tolerant transmission and delay-limited transmission. The impact of large antenna arrays at the mmWave frequencies on the secrecy throughput is examined. Numerical results corroborate our analysis and show that mmWave systems can enable significant secrecy improvement. Moreover, it is indicated that with large antenna arrays, multi-gigabit per second secure link at the mmWave frequencies can be reached in the delay-tolerant transmission mode and the adverse effect of secrecy outage vanishes in the delay-limited transmission mode.
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In this paper, the impact of hardware impairments on secrecy performance of cognitive MIMO schemes is investigated. In addition, the relay which helps the source forward the source signal to the destination can operate either half-duplex mode or full-duplex mode. For performance evaluation, we give the expressions of average secrecy rate over Rayleigh fading channel. Monte-Carlo simulations are presented to compare and optimize the performance of the proposed schemes.
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Quality Management and Managerialism in Healthcare creates a comprehensive and systematic international survey of various perspectives on healthcare quality management together with some of their most pertinent critiques. Chapter one starts with a general discussion of the factors that drove the introduction of management paradigms into public sector and health management contexts in the mid to late 1980s. Chapter two explores the rise of risk awareness in medicine; which, prior to the 1980s, stood largely in isolation to the implementation of managerial performance targets. Chapter three investigates the widespread adoption of performance management and clinical governance frameworks during the 1980s and 1990s. This is followed by Chapters four and five which examine systems based models of patient safety and the evidence-based medicine movement as exemplars of managerial perspectives on healthcare quality. Chapter six discusses potential future avenues for the development of alternative perspectives on quality of care which emphasise workforce involvement. The book concludes by reviewing the factors which have underpinned the managerialist trajectory of healthcare management over the past decades and explores the potential impact of nascent technologies such as 'connected health' and 'telehealth' on future developments.
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In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multi-antenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the cellular base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, we propose a new power transfer policy, namely, best power beacon (BPB) power transfer. To characterize the power transfer reliability of the proposed policy, we derive new closed-form expressions for the exact power outage probability and the asymptotic power outage probability with large antenna arrays at PBs. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), and 2) nearest receiver selection (NRS). To assess the secrecy performance, we derive new expressions for the secrecy throughput considering the two receiver selection schemes using the BPB power transfer policies. We show that secrecy performance improves with increasing densities of PBs and D2D receivers because of a larger multiuser diversity gain. A pivotal conclusion is reached that BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead.
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Objectives: To determine whether adjusting the denominator of the common hospital antibiotic use measurement unit (defined daily doses/100 bed-days) by including age-adjusted comorbidity score (100 bed-days/age-adjusted comorbidity score) would result in more accurate and meaningful assessment of hospital antibiotic use.
Methods: The association between the monthly sum of age-adjusted comorbidity and monthly antibiotic use was measured using time-series analysis (January 2008 to June 2012). For the purposes of conducting internal benchmarking, two antibiotic usage datasets were constructed, i.e. 2004-07 (first study period) and 2008-11 (second study period). Monthly antibiotic use was normalized per 100 bed-days and per 100 bed-days/age-adjusted comorbidity score.
Results: Results showed that antibiotic use had significant positive relationships with the sum of age-adjusted comorbidity score (P = 0.0004). The results also showed that there was a negative relationship between antibiotic use and (i) alcohol-based hand rub use (P = 0.0370) and (ii) clinical pharmacist activity (P = 0.0031). Normalizing antibiotic use per 100 bed-days contributed to a comparative usage rate of 1.31, i.e. the average antibiotic use during the second period was 31% higher than during the first period. However, normalizing antibiotic use per 100 bed-days per age-adjusted comorbidity score resulted in a comparative usage rate of 0.98, i.e. the average antibiotic use was 2% lower in the second study period. Importantly, the latter comparative usage rate is independent of differences in patient density and case mix characteristics between the two studied populations.
Conclusions: The proposed modified antibiotic measure provides an innovative approach to compare variations in antibiotic prescribing while taking account of patient case mix effects.
Secure D2D Communication in Large-Scale Cognitive Cellular Networks: A Wireless Power Transfer Model
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In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multiantenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the primary base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power transfer model, three wireless power transfer (WPT) policies are proposed: 1) co-operative power beacons (CPB) power transfer, 2) best power beacon (BPB) power transfer, and 3) nearest power beacon (NPB) power transfer. To characterize the power transfer reliability of the proposed three policies, we derive new expressions for the exact power outage probability. Moreover, the analysis of the power outage probability is extended to the case when PBs are equipped with large antenna arrays. In the information signal model, we present a new comparative framework with two receiver selection schemes: 1) best receiver selection (BRS), where the receiver with the strongest channel is selected; and 2) nearest receiver selection (NRS), where the nearest receiver is selected. To assess the secrecy performance, we derive new analytical expressions for the secrecy outage probability and the secrecy throughput considering the two receiver selection schemes using the proposed WPT policies. We presented Monte carlo simulation results to corroborate our analysis and show: 1) secrecy performance improves with increasing densities of PBs and D2D receivers due to larger multiuser diversity gain; 2) CPB achieves better secrecy performance than BPB and NPB but consumes more power; and 3) BRS achieves better secrecy performance than NRS but demands more instantaneous feedback and overhead. A pivotal conclusion- is reached that with increasing number of antennas at PBs, NPB offers a comparable secrecy performance to that of BPB but with a lower complexity.
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The Mozambique tilapia (Oreochromis mossambicus) is a maternal mouthbrooding cichlid from the southern Africa. The olfactory sensitivity of the species to 20 amino acids was assessed using the electro-olfactogram (EOG). We estimated whether the olfactory potency of the polar fraction of male urine can be explained by the presence of identified amino acids. In addition, filtrate and amino acid mixture of the urine of Nile tilapia were used to estimate their olfactory potency for O.mossambicus. Finally, concentrations of the main amino acids were measured in the urine of males of different social status and the correlations between amino acid concentration and hierarchical status were explored. L-cysteine, L-glutamine and L-threonine were the most potent stimuli at M while L-proline and L-aspartate were the least potent. Four groups of amino acids were identified according to their thresholds of detection and three groups – according to the similarity of their ɣ-factors. The estimated threshold of detection for O.mossambicus mixture was higher than that for the filtrate. On the contrary, the threshold of detection for the mixture of Nile tilapia was lower than that for the filtrate The concentration of L-arginine in the urine was positively correlated with fish dominance index. Both L-arginine and L-glutamic acid concentrations had much greater variability in dominant males (DI˃0.5) than in subordinate males (DI˂0.5). The urinary concentrations of L-phenylalanine had similar variability in dominant and subordinate groups. The Mozambique tilapia has olfactory sensitivity to all twenty amino acids tested. The fish showed more acute sensitivity to conspecific urine filtrate than to the heterospecific. Olfactory potency of O.mossambicus filtrate can be largely but not fully explained by the presence of L-arginine, L-glutamic acid and L-phenylalanine. Larginine and L-glutamic acid may indicate the dominance status of the fish and, possibly, individual identity.
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Volunteer administrators from 105 hospitals in five states in the northeast and southern United States provided open-ended survey responses about what they perceived to be the most pressing challenges and opportunities facing healthcare volunteer management. Taken together, these 105 hospitals used a total of 39,008 volunteers and 5.3 million volunteer hours during a 12-month period between 2010 and 2011. A qualitative content analysis of administrator responses suggests that primary challenges include volunteer recruitment and retention, administrative issues, and operational difficulties brought about by the current economic crisis. Key opportunities include more explicitly linking the volunteer function to hospital outcomes and community impact, expanding volunteer recruitment pools and roles and jobs, and developing organizational support for volunteers and making the volunteer management function more efficient and effective.
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Thesis (Master's)--University of Washington, 2016-03
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Thesis (Ph.D.)--University of Washington, 2016-03
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Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.
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This paper intends to show the Portuguese municipalities’ commitment, since the first decade of this century, in cultural facilities of municipal management and how it provided 12 of the 18 district capitals of mainland Portugal with cultural equipment, but after all we want to know if this effort resulted in a regular, diverse, and innovative schedule. Investing in urban regeneration, local governments have tried to convert cities’ demographic changes (strengthening of the most educated and professionally qualified groups) in effective cultural demands that consolidate the three axes of development competitiveness-innovation-creativity. What the empirical study to the programming and communication proposals of those equipment shows is that it is not enough to provide cities with facilities; to escape to a utilitarian conception of culture, there is a whole work to be done so that such equipment be experienced and felt as new public sphere. Equipment in which proposals go through a fluid bind, constructed through space and discourse with local community, devoted a diversified and innovative bet full filling development axis. This paper presents in a systematic way what contributes to this binding on the analyzed equipment.