Cost-effectiveness of a central venous catheter care bundle

Background: A bundled approach to central venous catheter care is currently being promoted as an effective way of preventing catheter-related bloodstream infection (CR-BSI). Consumables used in the bundled approach are relatively inexpensive which may lead to the conclusion that the bundle is cost-effective. However, this fails to consider the nontrivial costs of the monitoring and education activities required to implement the bundle, or that alternative strategies are available to prevent CR-BSI. We evaluated the cost-effectiveness of a bundle to prevent CR-BSI in Australian intensive care patients. ---------- Methods and Findings: A Markov decision model was used to evaluate the cost-effectiveness of the bundle relative to remaining with current practice (a non-bundled approach to catheter care and uncoated catheters), or use of antimicrobial catheters. We assumed the bundle reduced relative risk of CR-BSI to 0.34. Given uncertainty about the cost of the bundle, threshold analyses were used to determine the maximum cost at which the bundle remained cost-effective relative to the other approaches to infection control. Sensitivity analyses explored how this threshold alters under different assumptions about the economic value placed on bed-days and health benefits gained by preventing infection. If clinicians are prepared to use antimicrobial catheters, the bundle is cost-effective if national 18-month implementation costs are below $1.1 million. If antimicrobial catheters are not an option the bundle must cost less than $4.3 million. If decision makers are only interested in obtaining cash-savings for the unit, and place no economic value on either the bed-days or the health benefits gained through preventing infection, these cost thresholds are reduced by two-thirds.---------- Conclusions: A catheter care bundle has the potential to be cost-effective in the Australian intensive care setting. Rather than anticipating cash-savings from this intervention, decision makers must be prepared to invest resources in infection control to see efficiency improvements.

Executive coaching : perspectives of effectiveness from executives and coaches

There has been a remarkable expansion in the use of executive coaching as an executive development technique over the past two decades. The widespread popularity of executive coaching has been based largely on anecdotal feedback regarding its effectiveness. The small body of empirical research has been growing but conclusive outcomes are rare. This investigation has focused on the factors of executive coaching that contribute to its effectiveness with the perceptions of both executives and coaches being sought. Six major themes were identified, each comprising a collection of meanings. The findings of this study add value to the field by identifying factors contributing to coaching effectiveness, and providing for the coaching practitioner a basis for enhancing their practice of executive coaching.

Estimation of parameters for macroparasite population evolution using approximate Bayesian computation

We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra-binomial variation in terms of a zero-one immunity variable, which has a short-lived presence in the host.

Effectiveness of nurse-led preoperative assessment services for elective surgery : a systematic review

Background--The admission and assessment of patients for elective procedures is a task faced by all healthcare organisations that provide elective surgical services. Several different strategies have been used to facilitate the management of these tasks. Nurse-led preadmission clinics or services have been implemented in many health services as one of these management strategies; however their effectiveness has not been established. Objectives--The objective of this review was to examine the available research on the effectiveness of nurse-led elective surgery preoperative assessment clinics or services on patient outcomes.--Results--Of the 19 included articles, there were 10 audits of patient and hospital data, 3 surveys or questionnaires, 3 descriptive studies, 1 action research design, 1 prospective observational study and 1 RCT. Five of ten studies reporting data on cancellations rates found that nurse-led preadmission services reduced the number of day-of-surgery cancellations. Non-attendance for surgery was also reduced, with nine studies reporting decreases in the number of patients failing to attend. Eight studies reporting data on patient or parent satisfaction found high levels of satisfaction with nurse-led preadmission services. Three of four studies investigating the effect of the nurse-led preadmission service on patient anxiety found a reduction in reported anxiety levels. Three studies found that preoperative preparation was enhanced by the use of a nurse-led preadmission service.--Conclusions--While all included studies reported evidence of effectiveness for nurse-led preadmission services on a wide range of outcomes for elective surgery patients, the lack of experimental trials means that the level of evidence is low, and further research is needed.--Implications for practice--Nurse-led preadmission services may be an effective strategy for reducing procedural cancellations, failure to attend for procedures, and patient anxiety, however currently the evidence level is low.

Unaided stereo vision based pose estimation

This paper presents the development of a low-cost sensor platform for use in ground-based visual pose estimation and scene mapping tasks. We seek to develop a technical solution using low-cost vision hardware that allows us to accurately estimate robot position for SLAM tasks. We present results from the application of a vision based pose estimation technique to simultaneously determine camera poses and scene structure. The results are generated from a dataset gathered traversing a local road at the St Lucia Campus of the University of Queensland. We show the accuracy of the pose estimation over a 1.6km trajectory in relation to GPS ground truth.

Vision only pose estimation and scene reconstruction on airborne platforms

We aim to demonstrate unaided visual 3D pose estimation and map reconstruction using both monocular and stereo vision techniques. To date, our work has focused on collecting data from Unmanned Aerial Vehicles, which generates a number of significant issues specific to the application. Such issues include scene reconstruction degeneracy from planar data, poor structure initialisation for monocular schemes and difficult 3D reconstruction due to high feature covariance. Most modern Visual Odometry (VO) and related SLAM systems make use of a number of sensors to inform pose and map generation, including laser range-finders, radar, inertial units and vision [1]. By fusing sensor inputs, the advantages and deficiencies of each sensor type can be handled in an efficient manner. However, many of these sensors are costly and each adds to the complexity of such robotic systems. With continual advances in the abilities, small size, passivity and low cost of visual sensors along with the dense, information rich data that they provide our research focuses on the use of unaided vision to generate pose estimates and maps from robotic platforms. We propose that highly accurate (�5cm) dense 3D reconstructions of large scale environments can be obtained in addition to the localisation of the platform described in other work [2]. Using images taken from cameras, our algorithm simultaneously generates an initial visual odometry estimate and scene reconstruction from visible features, then passes this estimate to a bundle-adjustment routine to optimise the solution. From this optimised scene structure and the original images, we aim to create a detailed, textured reconstruction of the scene. By applying such techniques to a unique airborne scenario, we hope to expose new robotic applications of SLAM techniques. The ability to obtain highly accurate 3D measurements of an environment at a low cost is critical in a number of agricultural and urban monitoring situations. We focus on cameras as such sensors are small, cheap and light-weight and can therefore be deployed in smaller aerial vehicles. This, coupled with the ability of small aerial vehicles to fly near to the ground in a controlled fashion, will assist in increasing the effective resolution of the reconstructed maps.

Effectiveness of constructability concept in the provision of infrastructure assets

The concept of constructability is to use construction knowledge and experience during all phases of a project, particularly in the earliest phases of planning and design. It facilitates project objectives before delivery stage, and decreases unnecessary costs during construction phase. Despite the extensive use, constructability concept fails to address many issues related to Operation and Maintenance (O&M) of construction projects. Extending constructability concept, to include the O&M issues, could lead to the projects that are not fitted for construction purposes only, but also fitted for use. This study reviews the literature of constructability implementation, its benefits and shortcomings during the infrastructure life cycle, as well as the delivery success factors of infrastructure projects. This contributes to the propose need of a model to improve the effectiveness and efficiency of infrastructure project by extending the concept of constructability to include O&M. Development of such a model can facilitate post-occupancy stakeholders’ participation in a constructability program. It will help infrastructure owners eliminate project reworks, and improve O&M effectiveness and efficiency.

A test of podcasting effectiveness for lecture revision

It is important to understand how student performance when higher education is delivered by via new technology. Podcasting is a relatively recent new technology gaining widespread use across the world. We present the results of a quasi-experimental research project that finds when podcasts are used as a revision tool, student performance in Accounting improves. We highlight that aligning podcast use with pedagological design is important and discuss constraints on and barriers to the use of podcasting in higher education.

Modal parameter estimation in the presence of non-linearities

This paper investigates the use of time-frequency techniques to assist in the estimation of power system modes which are resolvable by a Digital Fourier Transform (DFT). The limitations of linear estimation techniques in the presence of large disturbances which excite system non-linearities, particularly the swing equation non-linearity are shown. Where a nonlinearity manifests itself as time varying modal frequencies the Wigner-Ville Distribution (WVD) is used to describe the variation in modal frequencies and construct a window over which standard linear estimation techniques can be used. The error obtained even in the presence of multiple resolvable modes is better than 2%.

Fixed-wing attitude estimation using temporal tracking of the horizon and optical flow

In this paper, a method has been developed for estimating pitch angle, roll angle and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front-end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an Extended Kalman Filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42◦ and 0.71◦ respectively when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79◦ and 1.75◦ respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front-end is also demonstrated.

Executive coaching : perspectives of effectiveness from executives and coaches

Over the past two decades there has been a remarkable expansion in the use of executive coaching as an executive development technique. The increasing prominence of executive coaching has been attributed to the emergence of new organisational cultures and the subtler competencies needed by executives in these faster moving organisations. The widespread popularity of executive coaching has been based largely on anecdotal feedback regarding its effectiveness. The small body of empirical research has been growing but conclusive outcomes are rare. The prominent question for those with the business imperative to implement executive coaching has been what are the ingredients of the process that engender an effective outcome? This investigation has focused on the factors of executive coaching that contribute to effectiveness. A qualitative methodology facilitated an in-depth study of the experiences of the participants of executive coaching with the perceptions of both executives and coaches being sought. Semi-structured interviews and a focus group provided rich, thick descriptions and together with a process of inductive analysis produced findings that confidently identify the key factors that contribute to coaching effectiveness. Six major themes were identified, each comprising a collection of meanings. These themes have been labelled Executive Engagement, Preliminary Assessment and Feedback, Coaching Process, Coach.s Contribution, Trusting Relationship and Support from the Organisation. One theme, Coaching Process, comprises three significant sub-themes, namely, Encouragement and Emotional Support, Challenge and Reflection and Enhancing Executive Performance. The findings of this study add value to the field by identifying factors contributing to coaching effectiveness, and providing for the coaching practitioner a basis for enhancing their practice of executive coaching to better meet the needs of executives and their organisations.

The effectiveness of a short-term group music therapy intervention for parents who have a child with a disability

Background The relationship between positive parent-child interactions and optimal child development is well established. Families with a child with a disability may face additional challenges to establishing positive parent-child relationships. There are limited studies addressing the effectiveness of interventions which seek to address these issues with parents and young children with a disability. In particular, prior studies of music therapy with this group have been limited by small sample sizes and the use of measures of limited reliability and validity. Objective This study investigates the effectiveness of a short-term group music therapy intervention for parents who have a child with a disability and explores the factors associated with higher outcomes for participating families. Methods The participants were 201 mother-child dyads, where the child had a disability. Pre and post intervention parental questionnaires and clinician observation measures were taken on a range of parental wellbeing, parenting behaviours and child developmental factors. Descriptive data, t-tests for repeated measures and a predictive model tested via logistic regression are presented. Results Significant improvements pre to post were found for parent mental health, child communication and social skills, parenting sensitivity, parental engagement with child and acceptance of child, child responsiveness to parent, and child interest and participation in program activities. There was also evidence that parents were very satisfied with the program and that it brought social benefits to families. Reliable change on six or more indicators of parent or child functioning was predicted by attendance and parent education. Conclusions This study provides positive evidence for the effectiveness of group music therapy in promoting improved parental mental health, positive parenting and key child developmental areas. Whilst several limitations are discussed, the study does address some of the gaps in the music therapy evidence base in this area.

Automatic in-bucket volume estimation for dragline operations

This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.

Range sensor pose estimation

This paper presents a method of recovering the 6 DoF pose (Cartesian position and angular rotation) of a range sensor mounted on a mobile platform. The method utilises point targets in a local scene and optimises over the error between their absolute position and their apparent position as observed by the range sensor. The analysis includes an investigation into the sensitivity and robustness of the method. Practical results were collected using a SICK LRS2100 mounted on a P&H electric mining shovel and present the errors in scan data relative to an independent 3D scan of the scene. A comparison to directly measuring the sensor pose is presented and shows the significant accuracy improvements in scene reconstruction using this pose estimation method.

Computed success rates of various carrier phase integer estimation solutions and their comparison with statistical success rates

The success rate of carrier phase ambiguity resolution (AR) is the probability that the ambiguities are successfully fixed to their correct integer values. In existing works, an exact success rate formula for integer bootstrapping estimator has been used as a sharp lower bound for the integer least squares (ILS) success rate. Rigorous computation of success rate for the more general ILS solutions has been considered difficult, because of complexity of the ILS ambiguity pull-in region and computational load of the integration of the multivariate probability density function. Contributions of this work are twofold. First, the pull-in region mathematically expressed as the vertices of a polyhedron is represented by a multi-dimensional grid, at which the cumulative probability can be integrated with the multivariate normal cumulative density function (mvncdf) available in Matlab. The bivariate case is studied where the pull-region is usually defined as a hexagon and the probability is easily obtained using mvncdf at all the grid points within the convex polygon. Second, the paper compares the computed integer rounding and integer bootstrapping success rates, lower and upper bounds of the ILS success rates to the actual ILS AR success rates obtained from a 24 h GPS data set for a 21 km baseline. The results demonstrate that the upper bound probability of the ILS AR probability given in the existing literatures agrees with the actual ILS success rate well, although the success rate computed with integer bootstrapping method is a quite sharp approximation to the actual ILS success rate. The results also show that variations or uncertainty of the unit–weight variance estimates from epoch to epoch will affect the computed success rates from different methods significantly, thus deserving more attentions in order to obtain useful success probability predictions.