866 resultados para nutritional management


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The relationship of acetylcholine receptor (AchR) antibodies to disease activity in myasthenia gravis (MG) is controversial. Some authors claim a direct correlation with disease activity and treatment, in particular plasmapheresis therapy, whereas others have commented on the poor overall correlation of antibody levels with clinical state. Antibody levels were examined in a population of MG patients and correlated with disease activity and response to treatment. Antibodies to skeletal muscle AchR were found in most patients with generalised MG (24/25) and in about half of the patients with purely ocular MG (6/10) and in neither of 2 patients with congenital MG. There was scant correlation with disease activity or response to treatment. It is concluded that the assay is more useful for diagnosis than for management of MG.

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This paper aims to contribute to an understanding of what actually takes place during consulting engagements. It draws on data collected from a qualitative case study of eight engagements by a niche consultancy in Australia to describe how consultants actively engage boundary crossing processes to address knowledge boundaries encountered during formal interactions with clients. While consultants actively managed knowledge boundary processes during interactions, by applying techniques such as evoking an ‘ideal state’ for clients, the engagements also yielded many missed opportunities for knowledge transformation.

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Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

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Small and micro-enterprises play a significant part in economic growth and poverty alleviation in developing African countries. There are, however, a range of management issues that arise when looking at the support required for local enterprise development, the role and management style of the local support agency and the role and style of the, usually Western, funding body. This paper explores the management philosophy required to establish and resource micro-enterprise development and compares the local management processes with those expected by a Western funding body.

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Review question/objective What is the effect of using the teach-back method for health education to improve adherence to treatment regimen and self-management in chronic disease? Inclusion criteria Types of participants This review will consider all studies that include adult patients (aged 18 years and over) in any healthcare setting, either as inpatients (eg acute care, medical and surgical wards) or those who attend primary health care, family medical practice, general medical practice, clinics, outpatient departments, rehabilitation or community settings. Participants need to have been diagnosed as having one or more chronic diseases including heart failure, diabetes, cardiovascular disease, cancer, respiratory disease, asthma, chronic obstructive pulmonary disease, chronic kidney disease, arthritis, epilepsy or a mental health condition. Studies that include seriously ill patients, and/or those who have impairments in verbal communication and cognitive function will be excluded. Types of intervention This review will consider studies that investigate the use of the teach-back method alone or in combination with other supporting education, either in routine or research intervention education programs; regardless of how long the programs were and whether or not a follow-up was conducted. The intervention could be delivered by any healthcare professional. The comparator will be any health education for chronic disease that does not include the teach-back method. Types of outcomes Primary outcomes of interest are disease-specific knowledge, adherence, and self-management knowledge, behavior and skills measured using patient report, nursing observation or validated measurement scales. Secondary outcomes include knowledge retention, self-efficacy, hospital readmission, hospitalization, and quality of life, also measured using patient report, nursing observation, hospital records or validated measurement scales.

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In this paper we argue that rationalist ‘predict then act’ approaches to disaster risk management (DRM) policy promote unrealistic public expectations of DRM provisions, the avoidance of decision making by political elites, an over-reliance on technical expertise and engineering solutions to reducing exposure to natural events, and a reactive approach to DRM overall. We propose an alternative incrementalist approach that focuses on managing uncertainties rather than reducing them and building resilience not simply through the reduction of hazard exposure, but also through the ongoing reduction of community vulnerability, the explicit consideration of normative priorities, and more effective community engagement in climate risk debates.

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It is only in recent years that the critical role that spatial data can play in disaster management and strengthening community resilience has been recognised. The recognition of this importance is singularly evident from the fact that in Australia spatial data is considered as soft infrastructure. In the aftermath of every disaster this importance is being increasingly strengthened with state agencies paying greater attention to ensuring the availability of accurate spatial data based on the lessons learnt. For example, the major flooding in Queensland during the summer of 2011 resulted in a comprehensive review of responsibilities and accountability for the provision of spatial information during such natural disasters. A high level commission of enquiry completed a comprehensive investigation of the 2011 Brisbane flood inundation event and made specific recommendations concerning the collection of and accessibility to spatial information for disaster management and for strengthening community resilience during and after a natural disaster. The lessons learnt and processes implemented were subsequently tested by natural disasters during subsequent years. This paper provides an overview of the practical implementation of the recommendations of the commission of enquiry. It focuses particularly on the measures adopted by the state agencies with the primary role for managing spatial data and the evolution of this role in Queensland State, Australia. The paper concludes with a review of the development of the role and the increasing importance of spatial data as an infrastructure for disaster planning and management which promotes the strengthening of community resilience.

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Organisations are constantly seeking cost-effective improvements for their business processes. Business process management (BPM) provides organisations with a range of methods, techniques and tools for analysing, managing, and optimising their business operations. However, BPM initiatives within organisations tend to focus on investigating time and resource utilisation inefficiencies, rather than directly on cost inefficiencies. As a result, high-level cost-based managerial decisions are still being made separately from process related decisions. This position paper describes a research agenda that envisages a holistic approach to managing the cost of business operations in a structured manner, by making an explicit link between cost and processes in all phases of the business process management life cycle. We discuss a number of research challenges that need to be addressed in order to realise such an approach as well as findings from some of the initial research outcomes. It is envisioned that the research outcomes will enable organisations to make operational and strategic decisions with confidence based on accurate and real-time cost information about their operations.

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Background Exploring self management in End Stage Renal Disease is extremely important for patients as they encounter several challenges including ongoing symptoms, complex treatments and restrictions, uncertainty about life and a dependency on technology, all of which impact upon their autonomy particularly after commencement of haemodialysis. Objective To summarise the effects of nursing interventions which effect selfmanagement of haemodialysis for patients with End Stage Renal Disease. Search strategy Search terms were chosen after reviewing text words and MeSH terms in relevant articles and databases. An extensive search of the literature from 1966 to June 2009 was conducted across a range of health databases including Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, CINAHL, PsycINFO and Web of Science. Further studies were identified from reference lists of all retrieved studies. Selection criteria We considered randomised controlled trials that compared interventions to improve self management of haemodialysis in patients with ESRD. In the absence of RCTs, comparative studies without randomisation as well as before and after studies were considered for inclusion. Methodological quality Study reports selected for retrieval were assessed by two independent reviewers for methodological quality prior to inclusion in the review using the standardised critical appraisal instruments for the Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information package (SUMARI). Data collection and analysis Data was extracted using the JBI data extraction tool for evidence of effectiveness independently by pairs of review authors. The evidence was reported in narrative summaries due to heterogeneity of the interventions of the studies. Results and conclusions Five randomised controlled trials were included in the review. Overall, the evidence found that psychosocial and educational interventions influenced self management of haemodialysis in this patient population.

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Current research into project management offices (PMOs) has stressed the PMOs' potential to act as knowledge brokers between projects, and between project and top management. Nonetheless, the literature does not provide sufficient evidence of the brokering role of PMOs. The research reported here aims to examine PMO's functions from a knowledge sharing perspective and explore whether or not these functions reflect the knowledge sharing needs of project managers (PMs). These issues are investigated through a cross-case analysis of seven organisations. The main contribution is insight into how PMs share knowledge and awareness of the need to structure PMOs to align with PMs' nature, needs and expectations in order to improve knowledge sharing in PBOs. Finally, some practical steps for helping PMOs to better adapt their functions to the needs of PMs and their learning and knowledge sharing style are proposed.