333 resultados para e-health systems


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This study examines the impact of utilising a Decision Support System (DSS) in a practical health planning study. Specifically, it presents a real-world case of a community-based initiative aiming to improve overall public health outcomes. Previous studies have emphasised that because of a lack of effective information, systems and an absence of frameworks for making informed decisions in health planning, it has become imperative to develop innovative approaches and methods in health planning practice. Online Geographical Information Systems (GIS) has been suggested as one of the innovative methods that will inform decision-makers and improve the overall health planning process. However, a number of gaps in knowledge have been identified within health planning practice: lack of methods to develop these tools in a collaborative manner; lack of capacity to use the GIS application among health decision-makers perspectives, and lack of understanding about the potential impact of such systems on users. This study addresses the abovementioned gaps and introduces an online GIS-based Health Decision Support System (HDSS), which has been developed to improve collaborative health planning in the Logan-Beaudesert region of Queensland, Australia. The study demonstrates a participatory and iterative approach undertaken to design and develop the HDSS. It then explores the perceived user satisfaction and impact of the tool on a selected group of health decision makers. Finally, it illustrates how decision-making processes have changed since its implementation. The overall findings suggest that the online GIS-based HDSS is an effective tool, which has the potential to play an important role in the future in terms of improving local community health planning practice. However, the findings also indicate that decision-making processes are not merely informed by using the HDSS tool. Instead, they seem to enhance the overall sense of collaboration in health planning practice. Thus, to support the Healthy Cities approach, communities will need to encourage decision-making based on the use of evidence, participation and consensus, which subsequently transfers into informed actions.

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The modern structural diagnosis process is rely on vibration characteristics to assess safer serviceability level of the structure. This paper examines the potential of change in flexibility method to use in damage detection process and two main practical constraints associated with it. The first constraint addressed in this paper is reduction in number of data acquisition points due to limited number of sensors. Results conclude that accuracy of the change in flexibility method is influenced by the number of data acquisition points/sensor locations in real structures. Secondly, the effect of higher modes on damage detection process has been studied. This addresses the difficulty of extracting higher order modal data with available sensors. Four damage indices have been presented to identify their potential of damage detection with respect to different locations and severity of damage. A simply supported beam with two degrees of freedom at each node is considered only for a single damage cases throughout the paper.

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The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

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This research examined the implementation of clinical information system technology in a large Saudi Arabian health care organisation. The research was underpinned by symbolic interactionism and grounded theory methods informed data collection and analysis. Observations, a review of policy documents and 38 interviews with registered nurses produced in-depth data. Analysis generated three abstracted concepts that explained how imported technology increased practice and health care complexity rather than enhance quality patient care. The core category, Disseminating Change, also depicted a hierarchical and patriarchal culture that shaped the implementation process at the levels of government, organisation and the individual.

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This workshop aims at discussing alternative approaches to resolving the problem of health information fragmentation, partially resulting from difficulties of health complex systems to semantically interact at the information level. In principle, we challenge the current paradigm of keeping medical records where they were created and discuss an alternative approach in which an individual's health data can be maintained by new entities whose sole responsibility is the sustainability of individual-centric health records. In particular, we will discuss the unique characteristics of the European health information landscape. This workshop is also a business meeting of the IMIA Working Group on Health Record Banking.

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Abstract Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.

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Troubled dynamics between residents of an Aboriginal town in Queensland and the local health system were established during colonisation and consolidated during those periods of Australian history where the policies of 'protection' (segregation), integration and then assimilation held sway. The status of Aboriginal health is, in part, related to interactions between the residents' current and historical experiences of the health and criminal justice systems as together these agencies used medical and moral policing to legitimate dispossession, marginalisation, institutionalisation and control of the residents. The punitive regulations and ethnocentric strategies used by these institutions are within the living memory of many of the residents or in the published accounts of preceding generations. This paper explores current residents' memories and experiences.

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As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

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Many factors have the potential to influence human health. These factors need to be monitored to maintain health. As is the case with human health, construction projects have a number of critical factors that can facilitate a broad evaluation of project health. In order to use these factors as an indication of health, they need to be assessed. This assessment can help to achieve desired outcomes for the project. This paper discusses the approach of assessing Critical Success Factors (CSFs) using Key Performance Indicators (KPIs) to ascertain the immediate health of a construction project. This approach is applicable to all phases of construction projects and many construction procurement methods. KPIs have been benchmarked on the basis of industry standards and historical data. The robustness of the KPIs to assess the immediate health of a project has been validated using Australian and international case studies.

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In many cases, construction projects do not achieve the objectives that the project participants set for them. If participants could better understand how their project is performing overall, at various stages of its delivery, then the opportunities to achieve project success would almost certainly be greater. This paper documents a method of assessing the status of a project, at a point in its design or construction phase, or after completion. The status is assessed in terms of up to seven (7) key success factors. Any evidence of less than adequate performance in these performance areas is scrutinised to seek out the root causes of why this situation is happening. Using these identified root causes of under performance, general suggestions can then be made as to how to return the project to good health. A software package that assists in assessing the status of the project has been developed. The package is currently being calibrated before commercial release.

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Maintaining the health of a construction project can help to achieve the desired outcomes of the project. An analogy is drawn to the medical process of a human health check where it is possible to broadly diagnose health in terms of a number of key areas such as blood pressure or cholesterol level. Similarly it appears possible to diagnose the current health of a construction project in terms of a number of Critical Success Factors (CSFs) and key performance indicators (KPIs). The medical analogy continues into the detailed investigation phase where a number of contributing factors are evaluated to identify possible causes of ill health and through the identification of potential remedies to return the project to the desired level of health. This paper presents the development of a model that diagnoses the immediate health of a construction project, investigates the factors which appear to be causing the ill health and proposes a remedy to return the project to good health. The proposed model uses the well-established continuous improvement management model (Deming, 1986) to adapt the process of human physical health checking to construction project health.