Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

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.

Is the iPhone a useful clinical tool to monitor spinal deformity patients?

The progression of spinal deformity is traditionally monitored on hard copy radiographs using the Cobb method with a protractor and pencil. The rotation of the spine and ribcage (rib hump) in scoliosis is measured with a hand-held inclinometer/Scoliometer. The iPhone and other smart phones, can accurately sense inclination, and can therefore be used to measure Cobb angles and rib hump angulation. The purpose of this study was to quantify the performance of the iPhone compared to the standard protractor (Cobb angles) and the Scoliometer (rib hump).

A survey to evaluate the implementation of a national clinical assessment form

Purpose: The Australian Universities Radiation Therapy Student Clinical Assessment Form (AURTSCAF) was designed to assess the clinical skills of radiation therapy (RT) students from the six universities that offer entry level RT programs. Given the AURTSCAF has now been in use for over two years, the Radiation Therapy Program Coordinators (RTPC) group initiated a post implementation evaluation survey. This formed the final phase of the AURTSCAF project and was funded by the Radiation Oncology Division of the Department of Health and Ageing. Methods: A cross-sectional designed survey using purposive sampling was distributed via email to all RT clinical sites. The survey asked questions about the requirements of a pass grade for students at different stages of their program, and the addition of a new category of assessment related to fitness to practise. Response types included both forced choice closed ended responses and open ended responses. There was also a section for open comments about the AURTSCAF. Results: There were 100 responses (55%) from clinicians who had utilised the assessment form over the previous 12 month period. Responses highlighted several positives with regard to the utility and implementation of the form. Comments regarding areas for improvement with the standardisation of the grading of students and consensus for the addition of a new domain in fitness for practise have informed the recommended changes proposed for 2012. Conclusion: This evaluation has provided a representative sample of the views of clinicians involved in assessing students on clinical placement. Recommendations include the addition of the sixth domain of assessment: Fitness for practise, the addition of descriptors and prompts for this domain in the user guide, the addition of a consensus statement about the use of the rating scale and dissemination of the proposed changes nationally.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Evaluation of coronary angiographic projections to balance the clinical yield with the radiation risk

Objective: Radiation safety principles dictate that imaging procedures should minimise the radiation risks involved, without compromising diagnostic performance. This study aims to define a core set of views that maximises clinical information yield for minimum radiation risk. Angiographers would supplement these views as clinically indicated. Methods: An algorithm was developed to combine published data detailing the quality of information derived for the major coronary artery segments through the use of a common set of views in angiography with data relating to the dose–area product and scatter radiation associated with these views. Results: The optimum view set for the left coronary system comprised four views: left anterior oblique (LAO) with cranial (Cr) tilt, shallow right anterior oblique (AP-RAO) with caudal (Ca) tilt, RAO with Ca tilt and AP-RAO with Cr tilt. For the right coronary system three views were identified: LAO with Cr tilt, RAO and AP-RAO with Cr tilt. An alternative left coronary view set including a left lateral achieved minimally superior efficiency (,5%), but with an ,8% higher radiation dose to the patient and 40% higher cardiologist dose. Conclusion: This algorithm identifies a core set of angiographic views that optimises the information yield and minimises radiation risk. This basic data set would be supplemented by additional clinically determined views selected by the angiographer for each case. The decision to use additional views for diagnostic angiography and interventions would be assisted by referencing a table of relative radiation doses for the views being considered.

Proteomics science & society : the role of knowledge translation in moving towards clinical applications

Background: Outside the mass-spectrometer, proteomics research does not take place in a vacuum. It is affected by policies on funding and research infrastructure. Proteomics research both impacts and is impacted by potential clinical applications. It provides new techniques & clinically relevant findings, but the possibilities for such innovations (and thus the perception of the potential for the field by funders) are also impacted by regulatory practices and the readiness of the health sector to incorporate proteomics-related tools & findings. Key to this process is how knowledge is translated. Methods: We present preliminary results from a multi-year social science project, funded by the Canadian Institutes of Health Research, on the processes and motivations for knowledge translation in the health sciences. The proteomics case within this wider study uses qualitative methods to examine the interplay between proteomics science and regulatory and policy makers regarding clinical applications of proteomics. Results: Adopting an interactive format to encourage conference attendees’ feedback, our poster focuses on deficits in effective knowledge translation strategies from the laboratory to policy, clinical, & regulatory arenas. An analysis of the interviews conducted to date suggests five significant choke points: the changing priorities of funding agencies; the complexity of proteomics research; the organisation of proteomics research; the relationship of proteomics to genomics and other omics sciences; and conflict over the appropriate role of standardisation. Conclusion: We suggest that engagement with aspects of knowledge translation, such as those mentioned above, is crucially important for the eventual clinical application ofproteomics science on any meaningful scale.

Perceptions of clinical safety climate of the multicultural nursing workforce in Saudi Arabia : a cross-sectional survey

Purpose The purpose of this study is to explore the safety climate perceptions of the multicultural nursing workforce, and to investigate the influence of diversity of the multicultural nursing workforce on clinical safety in a large tertiary hospital in Saudi Arabia. Background Working in a multicultural environment is challenging. Each culture has its own unique characteristics and dimensions that shape the language, lifestyle, beliefs, values, customs, traditions, and patterns of behaviour, which expatriate nurses must come to terms with. However, cultural diversity in the health care environment can potentially affect the quality of care and patient safety. Method A mixed-method case study (survey, interview and document analysis) was employed. A primary study phase entailed the administration of the Safety Climate Survey (SCS). A population sampling strategy was used and 319 nurses participated, yielding a 76.8% response rate. Descriptive and inferential statistics (Kruskal–Wallis test) were used to analyse survey data. Results The data revealed the nurses’ perceptions of the clinical safety climate in this multicultural environment was unsafe, with a mean score of 3.9 out of 5. No significant difference was found between the age groups, years of nursing experience and their perceptions of the safety climate in this context. A significant difference was observed between the national background categories of nurses and perceptions of safety climate. Conclusion Cultural diversity within the nursing workforce could have a significant influence on perceptions of clinical safety. These findings have the potential to inform policy and practice related to cultural diversity in Saudi Arabia.

Lateral movements in composite high-rise buildings under seismic action

Daring human nature has already led to the construction of high-rise buildings in naturally challenging geological regions and in worse environments of the world. However; literature review divulges that there is a lag in research of certain generic principles and rules for the prediction of lateral movement in multistorey construction. The present competitive trend orders the best possible used of available construction material and resources. Hence; the mixed used of reinforced concrete with structural steel is gaining prevalence day by day. This paper investigates the effects of Seismic load on composite multistorey building provided with core wall and trusses through FEM modelling. The results showed that increased rigidity corresponds to lower period of vibration and hence higher seismic forces. Since Seismic action is a function of mass and response acceleration, therefore; mass increment generate higher earthquake load and thus cause higher impact base shear and overturning movement. Whereas; wind force depends on building exposed, larger the plan dimension greater is the wind impact. Nonetheless; outriggers trusses noticeably contribute, in improving the serviceability of structure subjected to wind and earthquake forces.

'It ain't over till it's over' : Yogi Berra bias on prediction markets

The recent expansion of prediction markets provides a great opportunity to test the market efficiency hypothesis and the calibration of trader judgements. Using a large database of observed prices, this article studies the calibration of prediction markets prices on sporting events using both nonparametric and parametric methods. While only minor bias can be observed during most of the lifetime of the contracts, the calibration of prices deteriorates very significantly in the last moments of the contracts’ lives. Traders tend to overestimate the probability of the losing team to reverse the situation in the last minutes of the game.

National Institute for Clinical Studies Report for Phase 1, Evidence Uptake Network : Best Practice Community Care for Clients with Chronic Venous Leg Ulcers

Chronic leg ulcers cause significant pain, cost, decreased quality of life and morbidity for a considerable segment of the older population (Graham et al., 2003a). At any given time the prevalence of patients with open leg ulcers receiving treatment is between 0.11% - 0.18% (Briggs & Closs 2003). Chronic leg ulcers occur in approximately 1 - 2% of the over 60 population in the US, UK, Europe and Australia (Baker & Stacey 1994; Johnson 1995; Lees & Lambert 1992; Margolis et al. 2002). Considerable research has been undertaken to determine the best treatment practices that will aid in the management and the healing of these ulcers, and practical and effective strategies and techniques for healing venous leg ulcers have been trialled to demonstrate their beneficial effects (Nelson et al. 2004; Cullum et al. 2001)...

Investigation of decision making issues in the use of current clinical information systems

Clinical information systems have become important tools in contemporary clinical patient care. However, there is a question of whether the current clinical information systems are able to effectively support clinicians in decision making processes. We conducted a survey to identify some of the decision making issues related to the use of existing clinical information systems. The survey was conducted among the end users of the cardiac surgery unit, quality and safety unit, intensive care unit and clinical costing unit at The Prince Charles Hospital (TPCH). Based on the survey results and reviewed literature, it was identified that support from the current information systems for decision-making is limited. Also, survey results showed that the majority of respondents considered lack in data integration to be one of the major issues followed by other issues such as limited access to various databases, lack of time and lack in efficient reporting and analysis tools. Furthermore, respondents pointed out that data quality is an issue and the three major data quality issues being faced are lack of data completeness, lack in consistency and lack in data accuracy. Conclusion: Current clinical information systems support for the decision-making processes in Cardiac Surgery in this institution is limited and this could be addressed by integrating isolated clinical information systems.

Australian Diabetes Foot Network : management of diabetes-related foot ulceration — a clinical update

Summary Appropriate assessment and management of diabetes-related foot ulcers (DRFUs) is essential to reduce amputation risk. Management requires debridement, wound dressing, pressure off-loading, good glycaemic control and potentially antibiotic therapy and vascular intervention. As a minimum, all DRFUs should be managed by a doctor and a podiatrist and/or wound care nurse. Health professionals unable to provide appropriate care for people with DRFUs should promptly refer individuals to professionals with the requisite knowledge and skills. Indicators for immediate referral to an emergency department or multidisciplinary foot care team (MFCT) include gangrene, limb-threatening ischaemia, deep ulcers (bone, joint or tendon in the wound base), ascending cellulitis, systemic symptoms of infection and abscesses. Referral to an MFCT should occur if there is lack of wound progress after 4 weeks of appropriate treatment.

Standardising practices improves clinical diabetic foot management: the Queensland Diabetic Foot Innovation Project, 2006-09

Objective. The aim of this paper is to report the clinical practice changes resulting from strategies to standardise diabetic foot clinical management in three diverse ambulatory service sites in Queensland, Australia. Methods. Multifaceted strategies were implemented in 2008, including: multidisciplinary teams, clinical pathways, clinical training, clinical indicators, and telehealth support. Prior to the intervention, none of the aforementioned strategies were used, except one site had a basic multidisciplinary team. A retrospective audit of consecutive patient records from July 2006 to June 2007 determined baseline clinical activity (n = 101).Aclinical pathway teleform was implemented as a clinical activity analyser in 2008 (n = 327) and followed up in 2009 (n = 406). Pre- and post-implementation data were analysed using Chi-square tests with a significance level set at P < 0.05. Results. There was an improvement in surveillance of the high risk population of 34% in 2008 and 19% in 2009, and treating according to risk of 15% in 2009 (P < 0.05). The documentation of all best-practice clinical activities performed improved 13–66% (P < 0.03). Conclusion. These findings support the use of multifaceted strategies to standardise practice and improve diabetic foot complications management in diverse ambulatory services.