Tailoring Consumer Resources to Enhance Self-Care in Chronic Heart Failure

Background Chronic heart failure (CHF) is associated with high hospitalisation and mortality rates and debilitating symptoms. In an effort to reduce hospitalisations and improve symptoms individuals must be supported in managing their condition. Patients who can effectively self-manage their symptoms through lifestyle modification and adherence to complex medication regimens will experience less hospitalisations and other adverse events. Aim The purpose of this paper is to explain how providing evidence-based information, using patient education resources, can support self-care. Discussion Self-care relates to the activities that individuals engage in relation to health seeking behaviours. Supporting self-care practices through tailored and relevant information can provide patients with resources and advice on strategies to manage their condition. Evidence-based approaches to improve adherence to self-care practices in patients with heart failure are not often reported. Low health literacy can result in poor understanding of the information about CHF and is related to adverse health outcomes. Also a lack of knowledge can lead to non-adherence with self-care practices such as following fluid restriction, low sodium diet and daily weighing routines. However these issues need to be addressed to improve self-management skills. Outcome Recently the Heart Foundation CHF consumer resource was updated based on evidence-based national clinical guidelines. The aim of this resource is to help consumers improve understanding of the disease, reduce uncertainty and anxiety about what to do when symptoms appear, encourage discussions with local doctors, and build confidence in self-care management. Conclusion Evidence-based CHF patient education resources promote self-care practices and early detection of symptom change that may reduce hospitalisations and improve the quality of life for people with CHF.

Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

Access and Quality of Heart Failure Management Programs in Australia

Background/aim In response to the high burden of disease associated with chronic heart failure (CHF), in particular the high rates of hospital admissions, dedicated CHF management programs (CHF-MP) have been developed. Over the past five years there has been a rapid growth of CHF-MPs in Australia. Given the apparent mismatch between the demand for, and availability of CHF-MPs, this paper has been designed to discuss the accessibility to and quality of current CHF-MPs in Australia. Methods The data presented in this report has been combined from the research of the co-authors, in particular a review of the inequities in access to chronic heart failure which utilised geographical information systems (GIS) and the survey of heterogeneity in quality and service provision in Australian. Results Of the 62 CHF-MPs surveyed in this study 93% (58) centres had been located areas that are rated as Highly Accessible. This result indicated that most of the CHF-MPs have been located in capital cities or large regional cities. Six percent (4 CHF-MPs) had been located in Accessible areas which were country towns or cities. No CHF-MPs had been established outside of cities to service the estimated 72,000 individuals with CHF living in rural and remote areas. 16% of programs recruited NYHA Class I patients and of these 20% lacked confirmation (echocardiogram) of their diagnosis. Conclusion Overall, these data highlight the urgent need to provide equitable access to CHF-MP's. When establishing CHF-MPs consideration of current evidence based models to ensure quality in practice.

Exploration and optimization of user experience in viewing videos on a mobile phone

Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user’s viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user’s acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanying the quantitative method (acceptance assessment), we used a qualitative interview method to obtain a deeper understanding of a user’s assessment criteria and to support the quantitative results from a user’s perspective. Based on the results from data analysis, we advocate two user-driven strategies to adaptively provide an acceptable quality and to predict a good user experience, respectively. There are two main contributions from this paper. Firstly, the field user study allows a consideration of more influencing factors into the research on user experience of mobile video. And these influences are further demonstrated by user’s opinions. Secondly, the proposed strategies — user-driven acceptance threshold adaptation and user experience prediction — will be valuable in mobile video delivery for optimizing user experience.

Semantic modeling method for configurable enterprise information systems

Business practices vary from one company to another and business practices often need to be changed due to changes of business environments. To satisfy different business practices, enterprise systems need to be customized. To keep up with ongoing business practice changes, enterprise systems need to be adapted. Because of rigidity and complexity, the customization and adaption of enterprise systems often takes excessive time with potential failures and budget shortfall. Moreover, enterprise systems often drag business behind because they cannot be rapidly adapted to support business practice changes. Extensive literature has addressed this issue by identifying success or failure factors, implementation approaches, and project management strategies. Those efforts were aimed at learning lessons from post implementation experiences to help future projects. This research looks into this issue from a different angle. It attempts to address this issue by delivering a systematic method for developing flexible enterprise systems which can be easily tailored for different business practices or rapidly adapted when business practices change. First, this research examines the role of system models in the context of enterprise system development; and the relationship of system models with software programs in the contexts of computer aided software engineering (CASE), model driven architecture (MDA) and workflow management system (WfMS). Then, by applying the analogical reasoning method, this research initiates a concept of model driven enterprise systems. The novelty of model driven enterprise systems is that it extracts system models from software programs and makes system models able to stay independent of software programs. In the paradigm of model driven enterprise systems, system models act as instructors to guide and control the behavior of software programs. Software programs function by interpreting instructions in system models. This mechanism exposes the opportunity to tailor such a system by changing system models. To make this true, system models should be represented in a language which can be easily understood by human beings and can also be effectively interpreted by computers. In this research, various semantic representations are investigated to support model driven enterprise systems. The significance of this research is 1) the transplantation of the successful structure for flexibility in modern machines and WfMS to enterprise systems; and 2) the advancement of MDA by extending the role of system models from guiding system development to controlling system behaviors. This research contributes to the area relevant to enterprise systems from three perspectives: 1) a new paradigm of enterprise systems, in which enterprise systems consist of two essential elements: system models and software programs. These two elements are loosely coupled and can exist independently; 2) semantic representations, which can effectively represent business entities, entity relationships, business logic and information processing logic in a semantic manner. Semantic representations are the key enabling techniques of model driven enterprise systems; and 3) a brand new role of system models; traditionally the role of system models is to guide developers to write system source code. This research promotes the role of system models to control the behaviors of enterprise.