What are the real costs of major trauma?

Background This economic evaluation reports the results of a detailed study of the cost of major trauma treated at Princess Alexandra Hospital (PAH), Australia. Methods A bottom-up approach was used to collect and aggregate the direct and indirect costs generated by a sample of 30 inpatients treated for major trauma at PAH in 2004. Major trauma was defined as an admission for Multiple Significant Trauma with an Injury Severity Score >15. Direct and indirect costs were amalgamated from three sources, (1) PAH inpatient costs, (2) Medicare Australia, and (3) a survey instrument. Inpatient costs included the initial episode of inpatient care including clinical and outpatient services and any subsequent representations for ongoing-related medical treatment. Medicare Australia provided an itemized list of pharmaceutical and ambulatory goods and services. The survey instrument collected out-of-pocket expenses and opportunity cost of employment forgone. Inpatient data obtained from a publically funded trauma registry were used to control for any potential bias in our sample. Costs are reported in Australian dollars for 2004 and 2008. Results The average direct and indirect costs of major trauma incurred up to 1-year postdischarge were estimated to be A$78,577 and A$24,273, respectively. The aggregate costs, for the State of Queensland, were estimated to range from A$86.1 million to $106.4 million in 2004 and from A$135 million to A$166.4 million in 2008. Conclusion These results demonstrate that (1) the costs of major trauma are significantly higher than previously reported estimates and (2) the cost of readmissions increased inpatient costs by 38.1%.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Real-time volume estimation of a dragline payload

This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

Evaluation of financial incentives as a quality improvement strategy in the public hospital context : clinician attitudes, design variables, and economic costs

In 2008, a three-year pilot ‘pay for performance’ (P4P) program, known as ‘Clinical Practice Improvement Payment’ (CPIP) was introduced into Queensland Health (QHealth). QHealth is a large public health sector provider of acute, community, and public health services in Queensland, Australia. The organisation has recently embarked on a significant reform agenda including a review of existing funding arrangements (Duckett et al., 2008). Partly in response to this reform agenda, a casemix funding model has been implemented to reconnect health care funding with outcomes. CPIP was conceptualised as a performance-based scheme that rewarded quality with financial incentives. This is the first time such a scheme has been implemented into the public health sector in Australia with a focus on rewarding quality, and it is unique in that it has a large state-wide focus and includes 15 Districts. CPIP initially targeted five acute and community clinical areas including Mental Health, Discharge Medication, Emergency Department, Chronic Obstructive Pulmonary Disease, and Stroke. The CPIP scheme was designed around key concepts including the identification of clinical indicators that met the set criteria of: high disease burden, a well defined single diagnostic group or intervention, significant variations in clinical outcomes and/or practices, a good evidence, and clinician control and support (Ward, Daniels, Walker & Duckett, 2007). This evaluative research targeted Phase One of implementation of the CPIP scheme from January 2008 to March 2009. A formative evaluation utilising a mixed methodology and complementarity analysis was undertaken. The research involved three research questions and aimed to determine the knowledge, understanding, and attitudes of clinicians; identify improvements to the design, administration, and monitoring of CPIP; and determine the financial and economic costs of the scheme. Three key studies were undertaken to ascertain responses to the key research questions. Firstly, a survey of clinicians was undertaken to examine levels of knowledge and understanding and their attitudes to the scheme. Secondly, the study sought to apply Statistical Process Control (SPC) to the process indicators to assess if this enhanced the scheme and a third study examined a simple economic cost analysis. The CPIP Survey of clinicians elicited 192 clinician respondents. Over 70% of these respondents were supportive of the continuation of the CPIP scheme. This finding was also supported by the results of a quantitative altitude survey that identified positive attitudes in 6 of the 7 domains-including impact, awareness and understanding and clinical relevance, all being scored positive across the combined respondent group. SPC as a trending tool may play an important role in the early identification of indicator weakness for the CPIP scheme. This evaluative research study supports a previously identified need in the literature for a phased introduction of Pay for Performance (P4P) type programs. It further highlights the value of undertaking a formal risk assessment of clinician, management, and systemic levels of literacy and competency with measurement and monitoring of quality prior to a phased implementation. This phasing can then be guided by a P4P Design Variable Matrix which provides a selection of program design options such as indicator target and payment mechanisms. It became evident that a clear process is required to standardise how clinical indicators evolve over time and direct movement towards more rigorous ‘pay for performance’ targets and the development of an optimal funding model. Use of this matrix will enable the scheme to mature and build the literacy and competency of clinicians and the organisation as implementation progresses. Furthermore, the research identified that CPIP created a spotlight on clinical indicators and incentive payments of over five million from a potential ten million was secured across the five clinical areas in the first 15 months of the scheme. This indicates that quality was rewarded in the new QHealth funding model, and despite issues being identified with the payment mechanism, funding was distributed. The economic model used identified a relative low cost of reporting (under $8,000) as opposed to funds secured of over $300,000 for mental health as an example. Movement to a full cost effectiveness study of CPIP is supported. Overall the introduction of the CPIP scheme into QHealth has been a positive and effective strategy for engaging clinicians in quality and has been the catalyst for the identification and monitoring of valuable clinical process indicators. This research has highlighted that clinicians are supportive of the scheme in general; however, there are some significant risks that include the functioning of the CPIP payment mechanism. Given clinician support for the use of a pay–for-performance methodology in QHealth, the CPIP scheme has the potential to be a powerful addition to a multi-faceted suite of quality improvement initiatives within QHealth.

Narrative therapy for adults with major depressive disorder: Improved symptom and interpersonal outcomes

Abstract This study investigated depressive symptom and interpersonal relatedness outcomes from eight sessions of manualized narrative therapy for 47 adults with major depressive disorder. Post-therapy, depressive symptom improvement (d=1.36) and proportions of clients achieving reliable improvement (74%), movement to the functional population (61%), and clinically significant improvement (53%) were comparable to benchmark research outcomes. Post-therapy interpersonal relatedness improvement (d=.62) was less substantial than for symptoms. Three-month follow-up found maintenance of symptom, but not interpersonal gains. Benchmarking and clinical significance analyses mitigated repeated measure design limitations, providing empirical evidence to support narrative therapy for adults with major depressive disorder. RÉSUMÉ Cette étude a investigué les symptômes dépressifs et les relations interpersonnels d'une thérapie narrative en huit séances chez 47 adultes souffrant d'un trouble dépressif majeur. Après la thérapie, l'amélioration des symptômes dépressifs (d=1.36) et la proportion de clients atteignant un changement significatif (74%), le mouvement vers la population fonctionnelle (61%), enfin l'amélioration clinique significative (53%) étaient comparables aux performances des études de résultats. L'amélioration des relations interpersonnelles (d=0.62) était inférieure à l'amélioration symptomatique. Le suivi à trois mois montrait un maintien des gains symptomatiques mais pas pour les relations interpersonnelles. L’évaluation des performances et les analyses de significativité clinique modèrent les limitations du plan de recherche à mesures répétées et apportent une preuve empirique qui étaie l'efficacité des thérapies narratives pour des adultes avec un trouble dépressif majeur. Este estudo investigou sintomas depressivos e resultados interpessoais relacionados em oito sessões de terapia narrativa manualizada para 47 adultos com perturbação depressiva major. No pós terapia, melhoria de sintomas depressivos (d=1,36) e proporção de clientes que alcançam melhoria válida (74%), movimento para a população funcional (61%) e melhoria clinicamente significativa (53%) foram comparáveis com os resultados da investigação reportados. As melhorias pós terapia nos resultados interpessoais relacionados (d=.62) foi menos substancial do que para os sintomas. Aos três meses de seguimento houve a manutenção dos sintomas mas não dos ganhos interpessoais. As análises de benchemarking e de melhoria clinicamente significativas atenuam as limitações de um design de medidas repetidas, fornecendo evidência empírica para a terapia narrativa para adultos com perturbação depressiva major. Questo lavoro ha valutato i sintomi depressivi e gli outcome nella capacità di relazionarsi a livello interpersonale in 8 sedute di psicoterapia narrativa manualizzata in un gruppo di 47 adulti con depressione maggiore. I risultati ottenuti relativamente a: post terapy, miglioramento dei sintomi depressivi (d_1.36), proporzione di pazienti che hanno raggiunto un miglioramento affidabile e consistente (74%), movimento verso il funzionamento atteso nella popolazione (61%) e miglioramento clinicamente significativo (53%) sono paragonabili ai valori di riferimento della ricerca sull'outcome. I miglioramento della capacità di relazionarsi valutata alla fine del trattamento (d_.62) si è rivelata meno sostanziale rispetto ai sintomi. Un follow-up dopo 3 mesi ha dimostrato che il miglioramento sintomatologico è stato mantenuto, ma non quello degli obiettivi interpersonali. Valori di riferimento e analisi della significatività clinica hanno fatto fronte ai limiti del disegno a misure ripetute, offrendo prove empiriche sulla rilevanza della terapia narrativa in pazienti adulti con depressione maggiore

Living well with diabetes: a randomized controlled trial of a telephone-delivered intervention for maintenance of weight loss, physical activity and glycaemic control in adults with type 2 diabetes

Background By 2025, it is estimated that approximately 1.8 million Australian adults (approximately 8.4% of the adult population) will have diabetes, with the majority having type 2 diabetes. Weight management via improved physical activity and diet is the cornerstone of type 2 diabetes management. However, the majority of weight loss trials in diabetes have evaluated short-term, intensive clinic-based interventions that, while producing short-term outcomes, have failed to address issues of maintenance and broad population reach. Telephone-delivered interventions have the potential to address these gaps. Methods/Design Using a two-arm randomised controlled design, this study will evaluate an 18-month, telephone-delivered, behavioural weight loss intervention focussing on physical activity, diet and behavioural therapy, versus usual care, with follow-up at 24 months. Three-hundred adult participants, aged 20-75 years, with type 2 diabetes, will be recruited from 10 general practices via electronic medical records search. The Social-Cognitive Theory driven intervention involves a six-month intensive phase (4 weekly calls and 11 fortnightly calls) and a 12-month maintenance phase (one call per month). Primary outcomes, assessed at 6, 18 and 24 months, are: weight loss, physical activity, and glycaemic control (HbA1c), with weight loss and physical activity also measured at 12 months. Incremental cost-effectiveness will also be examined. Study recruitment began in February 2009, with final data collection expected by February 2013. Discussion This is the first study to evaluate the telephone as the primary method of delivering a behavioural weight loss intervention in type 2 diabetes. The evaluation of maintenance outcomes (6 months following the end of intervention), the use of accelerometers to objectively measure physical activity, and the inclusion of a cost-effectiveness analysis will advance the science of broad reach approaches to weight control and health behaviour change, and will build the evidence base needed to advocate for the translation of this work into population health practice.

Soil carbon sequestration rates and associated economic costs for farming systems of south-eastern Australia

Soil organic carbon (C) sequestration rates based on the Intergovernmental Panel for Climate Change (IPCC) methodology were combined with local economic data to simulate the economic potential for C sequestration in response to conservation tillage in the six agro-ecological zones within the Southern Region of the Australian grains industry. The net C sequestration rate over 20 years for the Southern Region (which includes discounting for associated greenhouse gases) is estimated to be 3.6 or 6.3 Mg C/ha after converting to either minimum or no-tillage practices, respectively, with no-till practices estimated to return 75% more carbon on average than minimum tillage. The highest net gains in C per ha are realised when converting from conventional to no-tillage practices in the high-activity clay soils of the High Rainfall and Wimmera agro-ecological zones. On the basis of total area available for change, the Slopes agro-ecological zone offers the highest net returns, potentially sequestering an additional 7.1 Mt C under no-tillage scenario over 20 years. The economic analysis was summarised as C supply curves for each of the 6 zones expressing the total additional C accumulated over 20 years for a price per t C sequestered ranging from zero to AU$200. For a price of $50/Mg C, a total of 427 000 Mg C would be sequestered over 20 years across the Southern Region, <5% of the simulated C sequestration potential of 9.1 Mt for the region. The Wimmera and Mid-North offer the largest gains in C under minimum tillage over 20 years of all zones for all C prices. For the no-tillage scenario, for a price of $50/Mg C, 1.74 Mt C would be sequestered over 20 years across the Southern Region, <10% of the simulated C sequestration potential of 18.6 Mt for the region over 20 years. The Slopes agro-ecological zone offers the best return in C over 20 years under no-tillage for all C prices. The Mallee offers the least return for both minimum and no-tillage scenarios. At a price of $200/Mg C, the transition from conventional tillage to minimum or no-tillage practices will only realise 19% and 33%, respectively, of the total biogeochemical sequestration potential of crop and pasture systems of the Southern Region over a 20-year period.

Peer state assessment of TxDOT maintenance program and practices : workshop and road rally findings

In an effort to evaluate and improve their practices to ensure the future excellence of the Texas highway system, the Texas Department of Transportation (TxDOT) sought a forum in which experts from other state departments of transportation could share their expertise. Thus, the Peer State Review of TxDOT Maintenance Practices project was organized and conducted for TxDOT by the Center for Transportation Research (CTR) at The University of Texas at Austin. The goal of the project was to conduct a workshop at CTR and in the Austin District that would educate the visiting peers on TxDOT’s maintenance practices and invite their feedback. CTR and TxDOT arranged the participation of the following directors of maintenance: Steve Takigawa, CA; Roy Rissky, KS; Eric Pitts, GA; Jim Carney, MO; Jennifer Brandenburg, NC; and David Bierschbach, WA. One of the means used to capture the peer reviewers’ opinions was a carefully designed booklet of 15 questions. The peers provided TxDOT with written responses to these questions, and the oral comments made during the workshop were also captured. This information was then compiled and summarized in the following report. An examination of the peers’ comments suggests that TxDOT should use a more holistic, statewide approach to funding and planning rather than funding and planning for each district separately. Additionally, the peers stressed the importance of allocating funds based on the actual conditions of the roadways instead of on inventory. The visiting directors of maintenance also recommended continuing and proliferating programs that enhance communication, such as peer review workshops.

Teaching tribology and maintenance-related subjects : a hands-on focus

In this paper different aspects of teaching tribology and maintenance-related subjects with a hands-on focus at Queensland University of Technology (QUT) are presented and discussed. As part of the study, a combination of data from core units, such as engineering design units, and elective units, was used, in addition to laboratory experiments, real-life projects, interactive software packages and industry visits. The mechanical engineering curriculum structure used at QUT, consisting of the main specialization (first major) and the second specialization (second major), is also discussed with specific emphasis on the teaching of tribology and maintenance-related subjects. To evaluate students' satisfaction with the novel teaching approaches used, tailored questionnaires were used as well as QUT's online learning experience survey (LEX). Statistical results of these sureveys are presented and discussed. In summary, these showed that students overwhelmingly support the hands-on and practical focus in teaching tribology and maintenance-related subjects and that the teaching approaches used shorten the learning curve and make students better prepared for integration in the workplace.