Motorcycle Safety Research Project Interim Report 2 : Review of the Consistent Assessment Process (CAP)

Motorcycle trauma is a serious road safety issue in Queensland and throughout Australia. In 2009, Queensland Transport (later Transport and Main Roads or TMR) appointed CARRS-Q to provide a three-year program of Road Safety Research Services for Motorcycle Rider Safety. Funding for this research originated from the Motor Accident Insurance Commission. This program of research was undertaken to produce knowledge to assist TMR to improve motorcycle safety by further strengthening the licensing and training system to make learner riders safer by developing a pre-learner package (Deliverable 1), and by evaluating the Q-Ride CAP program to ensure that it is maximally effective and contributes to the best possible training for new riders (Deliverable 2), which is the focus of this report. Deliverable 3 of the program identified potential new licensing components that will reduce the incidence of risky riding and improve higher-order cognitive skills in new riders. This report provides a summary of Deliverables 2.1 through to 2.4.

Motorcycle Safety Research Project Interim Summary Report 3 : Training and Licensing Interventions for Risk Taking and Hazard Perception for Motorcyclists

Motorcycle trauma is a serious road safety issue in Queensland and throughout Australia. In 2009, Queensland Transport (later Transport and Main Roads or TMR) appointed CARRS-Q to provide a three-year program of Road Safety Research Services for Motorcycle Rider Safety. Funding for this research originated from the Motor Accident Insurance Commission. This program of research was undertaken to produce knowledge to assist TMR to improve motorcycle safety by further strengthening the licensing and training system to make learner riders safer by developing a pre-learner package (Deliverable 1), and by evaluating the QRide CAP program to ensure that it is maximally effective and contributes to the best possible training for new riders (Deliverable 2). The focus of this report is Deliverable 3 of the overall program of research. It identifies potential new licensing components that will reduce the incidence of risky riding and improve higher-order cognitive skills in new riders.

Using the Donabedian framework to examine the quality and safety of nursing service innovation

Aims and objectives To evaluate the safety and quality of nurse practitioner service using the audit framework of Structure,Process and Outcome. Background Health service and workforce reform are on the agenda of governments and other service providers seeking to contain healthcare costs whilst providing safe and effective health care to communities. The nurse practitioner service is one health workforce innovation that has been adopted globally to improve timely access to clinical care, but there is scant literature reporting evaluation of the quality of this service innovation. Design. A mixed-methods design within the Donabedian evaluation framework was used. Methods The Donabedian framework was used to evaluate the Structure, Process and Outcome of nurse practitioner service. A range of data collection approaches was used, including stakeholder survey (n=36), in-depth interviews (11 patients and 13 nurse practitioners) and health records data on service processes. Results The study identified that adequate and detailed preparation of Structure and Process is essential for the successful implementation of a service innovation. The multidisciplinary team was accepting of the addition of nurse practitioner service, and nurse practitioner clinical care was shown to be effective, satisfactory and safe from the perspective of the clinician stakeholders and patients. Conclusions This study demonstrated that the Donabedian framework of Structure, Process and Outcome evaluation is a valuable and validated approach to examine the safety and quality of a service innovation. Furthermore, in this study, specific Structure elements were shown to influence the quality of service processes further validating the framework and the interdependence of the Structure, Process and Outcome components. Relevance to clinical practice Understanding the structure and process requirements for establishing nursing service innovation lays the foundation for safe, effective and patient-centred clinical care.

A comparison of safety climate and safety outcomes between construction and resource functions in a large case study organisation

The research described in this paper forms part of an in-depth investigation of safety culture in one of Australia’s largest construction companies. The research builds on a previous qualitative study with organisational safety leaders and further investigates how safety culture is perceived and experienced by organisational members, as well as how this relates to their safety behaviour and related outcomes at work. Participants were 2273 employees of the case study organisation, with 689 from the Construction function and 1584 from the Resources function. The results of several analyses revealed some interesting organisational variance on key measures. Specifically, the Construction function scored significantly higher on all key measures: safety climate, safety motivation, safety compliance, and safety participation. The results are discussed in terms of relevance in an applied research context.

Benefit cost analysis applied to behavioral and engineering safety countermeasures in San Francisco, California

The state of the practice in safety has advanced rapidly in recent years with the emergence of new tools and processes for improving selection of the most cost-effective safety countermeasures. However, many challenges prevent fair and objective comparisons of countermeasures applied across safety disciplines (e.g. engineering, emergency services, and behavioral measures). These countermeasures operate at different spatial scales, are funded often by different financial sources and agencies, and have associated costs and benefits that are difficult to estimate. This research proposes a methodology by which both behavioral and engineering safety investments are considered and compared in a specific local context. The methodology involves a multi-stage process that enables the analyst to select countermeasures that yield high benefits to costs, are targeted for a particular project, and that may involve costs and benefits that accrue over varying spatial and temporal scales. The methodology is illustrated using a case study from the Geary Boulevard Corridor in San Francisco, California. The case study illustrates that: 1) The methodology enables the identification and assessment of a wide range of safety investment types at the project level; 2) The nature of crash histories lend themselves to the selection of both behavioral and engineering investments, requiring cooperation across agencies; and 3) The results of the cost-benefit analysis are highly sensitive to cost and benefit assumptions, and thus listing and justification of all assumptions is required. It is recommended that a sensitivity analyses be conducted when there is large uncertainty surrounding cost and benefit assumptions.

Why we need a population-based approach to clinical indicators for cancer: a case study using microscopic confirmation of lung cancer in Queensland

An important function of clinical cancer registries is to provide feedback to clinicians on various performance measures. To date, most clinical cancer registries in Australia are located in tertiary academic hospitals, where adherence to guidelines is probably already high. Microscopic confirmation is an important process measure for lung cancer care. We found that the proportion of patients with lung cancer without microscopic confirmation was much higher in regional public hospitals (27.1%) than in tertiary hospitals (7.5%), and this disparity remained after adjusting for age, sex and comorbidities. The percentage was also higher in the private than in the public sector. This case study shows that we need a population-based approach to measuring clinical indicators that includes regional public hospitals as a matter of priority and should ideally include the private sector.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Remove, rehabilitate, return? The use and effectiveness of behaviour schools in New South Wales, Australia

Research indicates that enrolments in separate special educational settings for students with disruptive behaviour have increased in a number of educational jurisdictions internationally. Recent analysis of school enrolment data has identified a similar increase in the New South Wales (NSW) government school sector; however, questions have been raised as to their use and effectiveness. To situate the NSW experiment with behaviour schools in a broader context, the paper begins with a review of the international research literature. This is followed by a discussion of the NSW experience with the aim of identifying parallels and gaps in the research. The paper concludes by outlining important questions and directions for research to better understand and improve the educational experiences and outcomes of disruptive disaffected students in Australia’s largest school system.

Towards a structured understanding of caregivers’ safety behaviour in the domestic and driveway setting

Slow speed run-overs represent a major cause of injury and death among Australian children, with higher rates of incidents being reported in Queensland than in the remaining Australian states. Yet, little attention has been given to how caregivers develop their safety behaviour in and around the driveway setting. To address this gap, the current study aimed to develop a conceptual model of driveway child safety behaviours among caregivers of children aged five years or younger. Semi-structured interviews were conducted with 26 caregivers (25 females/1 male, mean age, 33.24 year) from rural and metropolitan Queensland. To enable a comparison and validation of findings from the driveway, the study analysed both driveway and domestic safety behaviours. Domestic safety behaviours were categorised and validated against driveway safety behaviours, uncovering a process of risk appraisal and safety behaviour that was applicable in both settings (the Safety System Model). However, noteworthy differences between the domestic and driveway setting were uncovered. Unlike in the domestic setting, driveway risks were perceived as shifting according the presence of moving vehicles, which resulted in inconsistent safety behaviours. While the findings require further validation, they have implications for the design and implementation of driveway run-over interventions.

A safe system-based approach to selection of clear zones, safety barriers and other roadside treatments

On average, 560 fatal run-off-road crashes occur annually in Australia and 135 in New Zealand. In addition, there are more than 14,000 run-off-road crashes causing injuries each year across both countries. In rural areas, run-off-road casualty crashes constitute 50-60% of all casualty crashes. Their severity is particularly high with more than half of those involved sustaining fatal or serious injuries. This paper reviews the existing approach to roadside hazard risk assessment, selection of clear zones and hazard treatments. It proposes a modified approach to roadside safety evaluation and management. It is a methodology based on statistical modelling of run-off-road casualty crashes, and application of locally developed crash modification factors and severity indices. Clear zones, safety barriers and other roadside design/treatment options are evaluated with a view to minimise fatal and serious injuries – the key Safe System objective. The paper concludes with a practical demonstration of the proposed approach. The paper is based on findings from a four-year Austroads research project into improving roadside safety in the Safe System context.

Managing the health effects of temperature in response to climate change : challenges ahead

BACKGROUND: Although many studies have shown that high temperatures are associated with an increased risk of mortality and morbidity, there has been little research on managing the process of planned adaptation to alleviate the health effects of heat events and climate change. In particular, economic evaluation of public health adaptation strategies has been largely absent from both the scientific literature and public policy discussion. OBJECTIVES: his paper aims to discuss how public health organizations should implement adaptation strategies, and how to improve the evidence base for policies to protect health from heat events and climate change. DISCUSSION: Public health adaptation strategies to cope with heat events and climate change fall into two categories: reducing the heat exposure and managing the health risks. Strategies require a range of actions, including timely public health and medical advice, improvements to housing and urban planning, early warning systems, and the assurance that health care and social systems are ready to act. Some of these actions are costly, and the implementation should be based on the cost-effectiveness analysis given scarce financial resources. Therefore, research is required not only on the temperature-related health costs, but also on the costs and benefits of adaptation options. The scientific community must ensure that the health co-benefits of climate change policies are recognized, understood and quantified. CONCLUSIONS: The integration of climate change adaptation into current public health practice is needed to ensure they increase future resilience. The economic evaluation of temperature-related health costs and public health adaptation strategies are particularly important for policy decisions.

Effect of depithing on the safety and environmental aspects of bagasse stockpiling

Large scale sugarcane bagasse storage in uncovered stockpiles has the potential to result in adverse impacts on the environment and surrounding communities through hazards associated with nuisance dust, groundwater seepage, spontaneous combustion and generation of contaminated leachates. Managing these hazards will assist in improved health and safety outcomes for factory staff and reduced potential environmental impacts on surrounding communities. Removal of the smaller fibres (pith) from bagasse prior to stockpiling reduced the dust number of bagasse by 50% and modelling suggests peak ground level PM10 dust emissions would reduce by 70%. Depithed bagasse has much lower water holding capacity (~43%) than whole bagasse. This experimental and modelling study investigated the physical properties of depithed and whole bagasse. Dust dispersion modelling was undertaken to determine the likely effects associated with storage of whole and depithed sugarcane bagasse.

Team communications in surgery - creating a culture of safety

As a key department within a healthcare organisation, the operating room is a hazardous environment, where the consequences of errors are high, despite the relatively low rates of occurrence. Team performance in surgery is increasingly being considered crucial for a culture of safety. The aim of this study was to describe team communication and the ways it fostered or threatened safety culture in surgery. Ethnography was used, and involved a 6-month fieldwork period of observation and 19 interviews with 24 informants from nursing, anaesthesia and surgery. Data were collected during 2009 in the operating rooms of a tertiary care facility in Queensland, Australia. Through analysis of the textual data, three themes that exemplified teamwork culture in surgery were generated: ‘‘building shared understandings through open communication’’; ‘‘managing contextual stressors in a hierarchical environment’’ and ‘‘intermittent membership influences team performance’’. In creating a safety culture in a healthcare organisation, a team’s optimal performance relies on the open discussion of teamwork and team expectation, and significantly depends on how the organisational culture promotes such discussions.

The effectiveness of the best interests duty : enhancing consumer protection?

This article considers the uncertainty surrounding the scope of the best interests duty which forms part of the Government’s Future of Financial Advice (FOFA) reforms. It is likely to be many years before the courts can interpret and clarify the content of the duty. Under the new regime, the provision of personal financial advice will be made more difficult, complex and costly and these costs will be passed on to consumers. The article also considers whether there will still be scope for delivering standardized, non-tailored advice in the light of the best interests duty. In the pas standardized advice has allowed large amounts of low-level, generic advice to be delivered very efficiently. In order to avoid breaching the best interests duty standardized advice should only be used rarely, and only after a careful assessment has been made to ensure that a standardized approach is appropriate.

Analyzing the effectiveness of graph metrics for anomaly detection in online social networks

Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.