Sustainable Road Management in Texas : network-level flexible pavement structural condition analysis using data mining techniques

The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.

The emerging role of private health care provision in China : a critical analysis of the current health system

China continues to face great challenges in meeting the health needs of its large population. The challenges are not just lack of resources, but also how to use existing resources more efficiently, more effectively, and more equitably. Now a major unaddressed challenge facing China is how to reform an inefficient, poorly organized health care delivery system. The objective of this study is to analyze the role of private health care provision in China and discuss the implications of increasing private-sector development for improving health system performance. This study is based on an extensive literature review, the purpose of which was to identify, summarize, and evaluate ideas and information on private health care provision in China. In addition, the study uses secondary data analysis and the results of previous study by the authors to highlight the current situation of private health care provision in one province of China. This study found that government-owned hospitals form the backbone of the health care system and also account for most health care service provision. However, even though the public health care system is constantly trying to adapt to population needs and improve its performance, there are many problems in the system, such as limited access, low efficiency, poor quality, cost inflation, and low patient satisfaction. Currently, private hospitals are relatively rare, and private health care as an important component of the health care system in China has received little policy attention. It is argued that policymakers in China should recognize the role of private health care provision for health system performance, and then define and achieve an appropriate role for private health care provision in helping to respond to the many challenges facing the health system in present-day China.

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.

An analysis of construction productivity in Malaysia

The construction industry is an industry of major strategic importance. Its level of productivity has a significant effect on national economic growth. Productivity indicators are examined. The indicators consist of labour productivity, capital productivity, labour competitiveness, capital intensity and added value content of data, which are obtained from the published census/biannual surveys of the construction industry between the years 1999 and 2011 from the Department of Statistics of Malaysia. The results indicated that there is an improvement in the labour productivity, but the value-added content is declining. The civil engineering and special trades subsectors are more productive than the residential and non-residential subsectors in terms of labour productivity because machine-for-labour substitution is a more important process in those subsectors. The capital-intensive characteristics of civil engineering and special trade works enable these subsectors to achieve higher added value per labour cost but not the capital productivity. The added value per labour cost is lower in larger organizations despite higher capital productivity. However, the capital intensity is lower and unit labour cost is higher in the larger organizations.

Utility of corneal confocal microscopy for assessing mild diabetic neuropathy: baseline findings of the LANDMark study

Background:  For those in the field of managing diabetic complications, the accurate diagnosis and monitoring of diabetic peripheral neuropathy (DPN) continues to be a challenge. Assessment of sub-basal corneal nerve morphology has recently shown promise as a novel ophthalmic marker for the detection of DPN. Methods:  Two hundred and thirty-one individuals with diabetes with predominantly mild or no neuropathy and 61 controls underwent evaluation of diabetic neuropathy symptom score, neuropathy disability score, testing with 10 g monofilament, quantitative sensory testing (warm, cold, vibration detection) and nerve conduction studies. Corneal nerve fibre length, branch density and tortuosity were measured using corneal confocal microscopy. Differences in corneal nerve morphology between individuals with and without DPN and controls were investigated using analysis of variance and correlations were determined between corneal morphology and established tests of, and risk factors for, DPN. Results:  Corneal nerve fibre length was significantly reduced in diabetic individuals with mild DPN compared with both controls (p < 0.001) and diabetic individuals without DPN (p = 0.012). Corneal nerve branch density was significantly reduced in individuals with mild DPN compared with controls (p = 0.032). Corneal nerve fibre tortuosity did not show significant differences. Corneal nerve fibre length and corneal nerve branch density showed modest correlations to most measures of neuropathy, with the strongest correlations to nerve conduction study parameters (r = 0.15 to 0.25). Corneal nerve fibre tortuosity showed only a weak correlation to the vibration detection threshold. Corneal nerve fibre length was inversely correlated to glycated haemoglobin (r = -0.24) and duration of diabetes (r = -0.20). Conclusion:  Assessment of corneal nerve morphology is a non-invasive, rapid test capable of showing differences between individuals with and without DPN. Corneal nerve fibre length shows the strongest associations with other diagnostic tests of neuropathy and with established risk factors for neuropathy.

A framework for cost-aware process management : generation of accurate and timely management accounting cost reports

Organisations are constantly seeking efficiency improvements for their business processes in terms of time and cost. Management accounting enables reporting of detailed cost of operations for decision making purpose, although significant effort is required to gather accurate operational data. Business process management is concerned with systematically documenting, managing, automating, and optimising processes. Process mining gives valuable insight into processes through analysis of events recorded by an IT system in the form of an event log with the focus on efficient utilisation of time and resources, although its primary focus is not on cost implications. In this paper, we propose a framework to support management accounting decisions on cost control by automatically incorporating cost data with historical data from event logs for monitoring, predicting and reporting process-related costs. We also illustrate how accurate, relevant and timely management accounting style cost reports can be produced on demand by extending open-source process mining framework ProM.

Earned value management insights using inferential statistics

Purpose – The purpose of this paper is to summarise a successfully defended doctoral thesis. The main purpose of this paper is to provide a summary of the scope, and main issues raised in the thesis so that readers undertaking studies in the same or connected areas may be aware of current contributions to the topic. The secondary aims are to frame the completed thesis in the context of doctoral-level research in project management as well as offer ideas for further investigation which would serve to extend scientific knowledge on the topic. Design/methodology/approach – Research reported in this paper is based on a quantitative study using inferential statistics aimed at better understanding the actual and potential usage of earned value management (EVM) as applied to external projects under contract. Theories uncovered during the literature review were hypothesized and tested using experiential data collected from 145 EVM practitioners with direct experience on one or more external projects under contract that applied the methodology. Findings – The results of this research suggest that EVM is an effective project management methodology. The principles of EVM were shown to be significant positive predictors of project success on contracted efforts and to be a relatively greater positive predictor of project success when using fixed-price versus cost-plus (CP) type contracts. Moreover, EVM's work-breakdown structure (WBS) utility was shown to positively contribute to the formation of project contracts. The contribution was not significantly different between fixed-price and CP contracted projects, with exceptions in the areas of schedule planning and payment planning. EVM's “S” curve benefited the administration of project contracts. The contribution of the S-curve was not significantly different between fixed-price and CP contracted projects. Furthermore, EVM metrics were shown to also be important contributors to the administration of project contracts. The relative contribution of EVM metrics to projects under fixed-price versus CP contracts was not significantly different, with one exception in the area of evaluating and processing payment requests. Practical implications – These results have important implications for project practitioners, EVM advocates, as well as corporate and governmental policy makers. EVM should be considered for all projects – not only for its positive contribution to project contract development and administration, for its contribution to project success as well, regardless of contract type. Contract type should not be the sole determining factor in the decision whether or not to use EVM. More particularly, the more fixed the contracted project cost, the more the principles of EVM explain the success of the project. The use of EVM mechanics should also be used in all projects regardless of contract type. Payment planning using a WBS should be emphasized in fixed-price contracts using EVM in order to help mitigate performance risk. Schedule planning using a WBS should be emphasized in CP contracts using EVM in order to help mitigate financial risk. Similarly, EVM metrics should be emphasized in fixed-price contracts in evaluating and processing payment requests. Originality/value – This paper provides a summary of cutting-edge research work and a link to the published thesis that researchers can use to help them understand how the research methodology was applied as well as how it can be extended.

The utility of serum CA-125 in predicting extra-uterine disease in apparent early stage endometrial cancer

Objectives: To evaluate the clinical value of pre-operative serum CA125 in predicting the presence of extra-uterine disease in patients with apparent early stage endometrial cancer. Methods: Between October 6, 2005 and June 17, 2010, 760 patients were enrolled in an international, multicentre, prospective randomized trial (LACE) comparing laparotomy with laparoscopy in the management of endometrial cancer apparently confined to the uterus. This study is based on data from 657 patients with endometrial adenocarcinoma who had a pre-operative serum CA125 value, and was undertaken to correlate pre-operative serum CA125 with final stage. Results: Using a pre-operative CA-125 cutpoint of 30U/ml was associated with the smallest misclassification error (14.5%) using a multiple cross-validation method. Median pre-operative serum CA-125 was 14U/ml, and using a cutpoint of 30U/ml, 14.9% of patients had elevated CA-125 levels. Of 98 patients with elevated CA-125 level, 36 (36.7%) had evidence of extra-uterine disease. Of the 116 patients (17.7%) with evidence of extra-uterine disease, 31.0% had elevated CA-125 level. In univariate and multivariate logistic regression analysis, only pre-operative CA-125 level was found to be associated with extra-uterine spread of disease. Utilising a cutpoint of 30U/ml achieved a sensitivity, specificity, positive predictive value and negative predictive value of 31.0%, 88.5%, 36.7% and 85.7% respectively. Overall, 326/657 (49.6%) of patients had full surgical staging involving lymph node dissection. When analysis was limited to patients that had undergone full surgical staging, the outcomes remained essentially unchanged. Conclusions: Elevated CA-125 above 30U/ml in patients with apparent early stage disease is associated with a sensitivity of 31.0% and specificity of 88.5% in detecting extra-uterine disease. Pre-operative identification of this risk factor may assist to triage patients to tertiary centres and comprehensive surgical staging.

Why do policy decision-makers opt for command and control environmental regulation? An economic analysis with special reference to Sri Lanka

This chapter examines why policy decision-makers opt for command and control environmental regulation despite the availability of a plethora of market-based instruments which are more efficient and cost-effective. Interestingly, Sri Lanka has adopted a wholly command and control system, during both the pre and post liberalisation economic policies. This chapter first examines the merits and demerits of command and control and market-based approaches and then looks at Sri Lanka’s extensive environmental regulatory framework. The chapter then examines the likely reasons as to why the country has gone down the path of inflexible regulatory measures and has become entrenched in them. The various hypotheses are discussed and empirical evidence is provided. The chapter also discusses the consequences of an environmentally slack economy and policy implications stemming from adopting a wholly regulatory approach. The chapter concludes with a discussion of the main results.

Determinants of health costs due to farmers’ exposure to pesticides: an empirical analysis

Pesticide spraying by farmers has an adverse impact on their health. However, in studies to date examining farmers’ exposure to pesticides, the costs of ill health and their determinants have been based on information provided by farmers themselves. Some doubt has therefore been cast on the reliability of these estimates. In this study, we address this by conducting surveys among two groups of farmers who use pesticides on a regular basis. The first group is made up of farmers who perceive that their ill health is due to exposure to pesticides and have obtained at least some form of treatment (described in this article as the ‘general farmer group’). The second group is composed of farmers whose ill health has been diagnosed by doctors and who have been treated in hospital for exposure to pesticides (described here as the ‘hospitalised farmer group’). Cost comparisons are made between the two groups of farmers. Regression analysis of the determinants of health costs show that the most important determinants of medical costs for both samples are the defensive expenditure, the quantity of pesticides used per acre per month, frequency of pesticide use and number of pesticides used per hour per day. The results have important policy implications.

An analysis of the corporate governance practices of smaller listed Australian companies

We examine the corporate governance environment of smaller listed Australian firms to investigate the factors that determine how firms respond to recommendations contained in corporate governance codes. We group corporate governance recommendations into three distinct categories and argue that differences in adoption costs between categories, together with firm specific factors, determine a firm’s decision to conform with the recommendation or to explain the reasons for non-conformance. Analysis of the conformance by smaller firms with governance recommendations highlights substantial differences in adoption rates between categories of recommendations. Our results also reveal that the cost of adopting specific recommendations, together with profitability, external audit quality, and ownership dispersion, jointly explain a firm’s decision to ‘comply or explain’. This study provides insights for policy makers and regulators regarding the appropriateness of corporate governance recommendations for smaller firms

A cost-outcome description of the septic work-up for bacterial infection in neonates in a tertiary care hospital

Analysis of the septic work-up of 194 neonates at Women's College Hospital, Toronto, showed that the only antepartum condition predicting neonatal sepsis was the mother being on antibiotics. The only postnatal condition predicting sepsis was a maternal postpartum white blood cell count over 11,000. The average cost for tests for a septic work-up in these 194 mother-neonate pairs was $71.48 (Canadian dollars), and the average cost of tests to find a septic case was $1,066.77.

Circulating tumour cells, their role in metastasis and their clinical utility in lung cancer

Circulating tumour cells (CTCs) have attracted much recent interest in cancer research as a potential biomarker and as a means of studying the process of metastasis. It has long been understood that metastasis is a hallmark of malignancy, and conceptual theories on the basis of metastasis from the nineteenth century foretold the existence of a tumour "seed" which is capable of establishing discrete tumours in the "soil" of distant organs. This prescient "seed and soil" hypothesis accurately predicted the existence of CTCs; microscopic tumour fragments in the blood, at least some of which are capable of forming metastases. However, it is only in recent years that reliable, reproducible methods of CTC detection and analysis have been developed. To date, the majority of studies have employed the CellSearch™ system (Veridex LLC), which is an immunomagnetic purification method. Other promising techniques include microfluidic filters, isolation of tumour cells by size using microporous polycarbonate filters and flow cytometry-based approaches. While many challenges still exist, the detection of CTCs in blood is becoming increasingly feasible, giving rise to some tantalizing questions about the use of CTCs as a potential biomarker. CTC enumeration has been used to guide prognosis in patients with metastatic disease, and to act as a surrogate marker for disease response during therapy. Other possible uses for CTC detection include prognostication in early stage patients, identifying patients requiring adjuvant therapy, or in surveillance, for the detection of relapsing disease. Another exciting possible use for CTC detection assays is the molecular and genetic characterization of CTCs to act as a "liquid biopsy" representative of the primary tumour. Indeed it has already been demonstrated that it is possible to detect HER2, KRAS and EGFR mutation status in breast, colon and lung cancer CTCs respectively. In the course of this review, we shall discuss the biology of CTCs and their role in metastagenesis, the most commonly used techniques for their detection and the evidence to date of their clinical utility, with particular reference to lung cancer.

Extending the explanatory utility of the EPPM beyond fear-based persuasion

In the 20 years since its inception, the EPPM has attracted much empirical support. Currently, and unsurprisingly given that is a model of fear-based persuasion, the EPPM’s explanatory utility has been based only upon fear-based messages. However, an argument is put forth herein, which draws upon existing evidence, that the EPPM may be an efficacious framework for explaining the persuasive process and outcomes of emotion-based messages more broadly when such messages are addressing serious health topics. For the current study, four different types of emotional appeals were purposefully devised and included a fear, an annoyance/agitation, a pride, and a humour-based message. All messages addressed the serious health issue of road safety, and in particular the risky behaviour of speeding. Participants (N = 551) were exposed to only one of the four messages and subsequently provided responses within a survey. A series of 2 (threat: low, high) x 2 (efficacy: low, high) analysis of variance was conducted for each of the appeals based on the EPPM’s message outcomes of acceptance and rejection. Support was found for the EPPM with a number of main effects of threat and efficacy emerging, reflecting that, irrespective of emotional appeal type, high levels of threat and efficacy enhanced message outcomes via maximising acceptance and minimising rejection. Theoretically, the findings provide support for the explanatory utility of the EPPM for emotion-based health messages more broadly. In an applied sense, the findings highlight the value of adopting the EPPM as a framework when devising and evaluating emotion-based health messages for serious health topics.