Funding grant proposals for scientific research : retrospective analysis of scores by members of grant review panel

Objectives: To quantify randomness and cost when choosing health and medical research projects for funding. Design: Analysis of retrospective data from grant review panels. Setting: The National Health & Medical Research Council of Australia. Participants/Data: All panel members’ scores for grant proposals submitted in 2009. Main outcome measure: The proportion of grant proposals that were always, sometimes and never funded after accounting for random variability arising from variation in panel members’ scores; the cost-effectiveness of different size assessment panels. Results: 59% of 620 funded grants were sometimes not funded when random variability was accounted for. Only 9% of grant proposals were always funded, 61% were never funded and 29% were sometimes funded. The extra cost per grant effectively funded from the most effective system was $18,541. Conclusions: Allocating funding for scientific research in health and medicine is costly and somewhat random. There are many useful research questions to be addressed that could improve current processes.

Influence of rainfall and catchment characteristics on urban stormwater quality

This thesis presents the outcomes of a comprehensive research study undertaken to investigate the influence of rainfall and catchment characteristics on urban stormwater quality. The knowledge created is expected to contribute to a greater understanding of urban stormwater quality and thereby enhance the design of stormwater quality treatment systems. The research study was undertaken based on selected urban catchments in Gold Coast, Australia. The research methodology included field investigations, laboratory testing, computer modelling and data analysis. Both univariate and multivariate data analysis techniques were used to investigate the influence of rainfall and catchment characteristics on urban stormwater quality. The rainfall characteristics investigated included average rainfall intensity and rainfall duration whilst catchment characteristics included land use, impervious area percentage, urban form and pervious area location. The catchment scale data for the analysis was obtained from four residential catchments, including rainfall-runoff records, drainage network data, stormwater quality data and land use and land cover data. Pollutants build-up samples were collected from twelve road surfaces in residential, commercial and industrial land use areas. The relationships between rainfall characteristics, catchment characteristics and urban stormwater quality were investigated based on residential catchments and then extended to other land uses. Based on the influence rainfall characteristics exert on urban stormwater quality, rainfall events can be classified into three different types, namely, high average intensity-short duration (Type 1), high average intensity-long duration (Type 2) and low average intensity-long duration (Type 3). This provides an innovative approach to conventional modelling which does not commonly relate stormwater quality to rainfall characteristics. Additionally, it was found that the threshold intensity for pollutant wash-off from urban catchments is much less than for rural catchments. High average intensity-short duration rainfall events are cumulatively responsible for the generation of a major fraction of the annual pollutants load compared to the other rainfall event types. Additionally, rainfall events less than 1 year ARI such as 6- month ARI should be considered for treatment design as they generate a significant fraction of the annual runoff volume and by implication a significant fraction of the pollutants load. This implies that stormwater treatment designs based on larger rainfall events would not be feasible in the context of cost-effectiveness, efficiency in treatment performance and possible savings in land area needed. This also suggests that the simulation of long-term continuous rainfall events for stormwater treatment design may not be needed and that event based simulations would be adequate. The investigations into the relationship between catchment characteristics and urban stormwater quality found that other than conventional catchment characteristics such as land use and impervious area percentage, other catchment characteristics such as urban form and pervious area location also play important roles in influencing urban stormwater quality. These outcomes point to the fact that the conventional modelling approach in the design of stormwater quality treatment systems which is commonly based on land use and impervious area percentage would be inadequate. It was also noted that the small uniformly urbanised areas within a larger mixed catchment produce relatively lower variations in stormwater quality and as expected lower runoff volume with the opposite being the case for large mixed use urbanised catchments. Therefore, a decentralised approach to water quality treatment would be more effective rather than an "end-of-pipe" approach. The investigation of pollutants build-up on different land uses showed that pollutant build-up characteristics vary even within the same land use. Therefore, the conventional approach in stormwater quality modelling, which is based solely on land use, may prove to be inappropriate. Industrial land use has relatively higher variability in maximum pollutant build-up, build-up rate and particle size distribution than the other two land uses. However, commercial and residential land uses had relatively higher variations of nutrients and organic carbon build-up. Additionally, it was found that particle size distribution had a relatively higher variability for all three land uses compared to the other build-up parameters. The high variability in particle size distribution for all land uses illustrate the dissimilarities associated with the fine and coarse particle size fractions even within the same land use and hence the variations in stormwater quality in relation to pollutants adsorbing to different sizes of particles.

Optimum utilisation of rolling stocks for iron ore mining industries

In this paper, a generic and flexible optimisation methodology is developed to represent, model, solve and analyse the iron ore supply chain system by integrating of iron ore shipment, stockpiles and railing within a whole system. As a result, an integrated train-stockpile-ship timetable is created and optimised for improving efficiency of overall supply chain system. The proposed methodology provides better decision making on how to significantly improve rolling stock utilisation with the best cost-effectiveness ratio. Based on extensive computational experiments and analysis, insightful and quantitative advices are suggested for iron ore mine industry practitioners. The proposed methodology contributes to the sustainability of the environment by reducing pollution due to better utilisation of transportation resources and fuel.

Plastic bending behaviour and section moment capacities of mono-symmetric LiteSteel Beams with web openings

Recently developed cold-formed LiteSteel beam (LSB) sections have found increasing popularity in residential, industrial and commercial buildings due to their light weight and cost-effectiveness. Currently, there is significant interest in the use of LSB sections as flexural members in floor joist systems, although they can be used as flexural and compression members in a range of building systems. The plastic bending behaviour and section moment capacity of LSB sections with web holes can be assumed to differ from those without, but have yet to be investigated. Hence, no appropriate design rules for determining the section moment capacity of LSB sections with web holes are yet available. This paper presents the results of an investigation of the plastic bending behaviour and section moment capacity of LSB sections with circular web holes. LSB sections with varying circular hole diameters and degrees of spacing were considered. The paper also describes the simplified finite element (FE) modelling technique employed in this study, which incorporates all of the significant behavioural effects that influence the plastic bending behaviour and section moment capacity of these sections. The numerical and experimental test results and associated findings are also presented.

Member moment capacities of mono-symmetric LiteSteel beam floor joists with web openings

Recently developed cold-formed LiteSteel beam (LSB) sections have found increasing popularity in residential, industrial and commercial buildings due to their light weight and cost-effectiveness. Another beneficial characteristic is that they allow torsionally rigid rectangular flanges to be combined with economical fabrication processes. Currently, there is significant interest in the use of LSB sections as flexural members in floor joist systems. When used as floor joists, these sections require openings in the web to provide access for inspection and other services. At present, however, there is no design method available that provides accurate predictions of the moment capacities of LSBs with web openings. This paper presents the results of an investigation of the buckling and ultimate strength behaviour of LSB flexural members with web openings. A detailed fine element analysis (FEA)-based parametric study was conducted with the aim of developing appropriate design rules and making recommendations for the safe design of LSB floor joists. The results include the required moment capacity curves for LSB sections with a range of web opening combinations and spans and the development of appropriate design rules for the prediction of the ultimate moment capacities of LSBs with web openings.

Evaluating the economics of the Australian National Hand Hygiene Initiative

The National Hand Hygiene Initiative, implemented in Australia in 2009, is currently being evaluated for effectiveness and cost-effectiveness by a multidisciplinary team of researchers. Data from a wide range of sources are being harvested to address the research questions. The data are observational and appropriate statistical and economic modelling methods are being used. Decision makers will be provided with new knowledge about how hand hygiene interventions should be organised and what investment decisions are justified. This is novel research and the authors are unaware of any other evaluation of hand hygiene improvement initiatives. This paper describes the evaluation currently underway.

Improving trust and securing data accessibility for e-health decision making by using data encryption techniques

In the medical and healthcare arena, patients‟ data is not just their own personal history but also a valuable large dataset for finding solutions for diseases. While electronic medical records are becoming popular and are used in healthcare work places like hospitals, as well as insurance companies, and by major stakeholders such as physicians and their patients, the accessibility of such information should be dealt with in a way that preserves privacy and security. Thus, finding the best way to keep the data secure has become an important issue in the area of database security. Sensitive medical data should be encrypted in databases. There are many encryption/ decryption techniques and algorithms with regard to preserving privacy and security. Currently their performance is an important factor while the medical data is being managed in databases. Another important factor is that the stakeholders should decide more cost-effective ways to reduce the total cost of ownership. As an alternative, DAS (Data as Service) is a popular outsourcing model to satisfy the cost-effectiveness but it takes a consideration that the encryption/ decryption modules needs to be handled by trustworthy stakeholders. This research project is focusing on the query response times in a DAS model (AES-DAS) and analyses the comparison between the outsourcing model and the in-house model which incorporates Microsoft built-in encryption scheme in a SQL Server. This research project includes building a prototype of medical database schemas. There are 2 types of simulations to carry out the project. The first stage includes 6 databases in order to carry out simulations to measure the performance between plain-text, Microsoft built-in encryption and AES-DAS (Data as Service). Particularly, the AES-DAS incorporates implementations of symmetric key encryption such as AES (Advanced Encryption Standard) and a Bucket indexing processor using Bloom filter. The results are categorised such as character type, numeric type, range queries, range queries using Bucket Index and aggregate queries. The second stage takes the scalability test from 5K to 2560K records. The main result of these simulations is that particularly as an outsourcing model, AES-DAS using the Bucket index shows around 3.32 times faster than a normal AES-DAS under the 70 partitions and 10K record-sized databases. Retrieving Numeric typed data takes shorter time than Character typed data in AES-DAS. The aggregation query response time in AES-DAS is not as consistent as that in MS built-in encryption scheme. The scalability test shows that the DBMS reaches in a certain threshold; the query response time becomes rapidly slower. However, there is more to investigate in order to bring about other outcomes and to construct a secured EMR (Electronic Medical Record) more efficiently from these simulations.

Simple rules to contain an invasive species with a complex life cycle and high dispersal capacity

Designing practical rules for controlling invasive species is a challenging task for managers, particularly when species are long-lived, have complex life cycles and high dispersal capacities. Previous findings derived from plant matrix population analyses suggest that effective control of long-lived invaders may be achieved by focusing on killing adult plants. However, the cost-effectiveness of managing different life stages has not been evaluated. We illustrate the benefits of integrating matrix population models with decision theory to undertake this evaluation, using empirical data from the largest infestation of mesquite (Leguminosae: Prosopis spp) within Australia. We include in our model the mesquite life cycle, different dispersal rates and control actions that target individuals at different life stages with varying costs, depending on the intensity of control effort. We then use stochastic dynamic programming to derive cost-effective control strategies that minimize the cost of controlling the core infestation locally below a density threshold and the future cost of control arising from infestation of adjacent areas via seed dispersal. Through sensitivity analysis, we show that four robust management rules guide the allocation of resources between mesquite life stages for this infestation: (i) When there is no seed dispersal, no action is required until density of adults exceeds the control threshold and then only control of adults is needed; (ii) when there is seed dispersal, control strategy is dependent on knowledge of the density of adults and large juveniles (LJ) and broad categories of dispersal rates only; (iii) if density of adults is higher than density of LJ, controlling adults is most cost-effective; (iv) alternatively, if density of LJ is equal or higher than density of adults, management efforts should be spread between adults, large and to a lesser extent small juveniles, but never saplings. Synthesis and applications.In this study, we show that simple rules can be found for managing invasive plants with complex life cycles and high dispersal rates when population models are combined with decision theory. In the case of our mesquite population, focussing effort on controlling adults is not always the most cost-effective way to meet our management objective.

Outcomes following operative and non-operative management of humeral midshaft fractures: a prospective, observational cohort study of 47 patients

Background Although the non-operative management of closed humeral midshaft fractures has been advocated for years, the increasing popularity of operative intervention has left the optimal treatment choice unclear. Objective To compare the outcomes of operative and non-operative treatment of traumatic closed humeral midshaft fractures in adult patients. Methods A multicentre prospective comparative cohort study across 20 centres was conducted. Patients with AO type 12 A2, A3 and B2 fractures were treated with a functional brace or a retrograde-inserted unreamed humeral nail. Follow-up measurements were taken at 6, 12 and 52 weeks after the injury. The primary outcome was fracture healing after 1 year. Secondary outcomes included sub-items of the Constant score, general patient satisfaction, complications and cost-effectiveness parameters. Functions of the uninjured extremity were used as reference parameters. Intention-to-treat analysis was applied with the use of t-tests, Fisher’s exact tests, Mann–Whitney U-tests and adjusted analysis of variance (ANOVA). Results Forty-seven patients were included. The patient sample consisted of 23 women and 24 men, with a mean age of 52.7 years (range 17–86 years). Of the 47 cases, 14 were treated non-operatively and 33 operatively. The follow-up rate at 1 year was 81%. After 1 year, 11 fractures (100%) healed in the non-operative group and at least 24 fractures (≥89%) healed in the operative group [1 non-union patient (4%) and no data for 2 patients (7%)]. There were no significant differences in pain, range of motion (ROM) of the shoulder and elbow, and return to work after 6 weeks, 12 weeks and 1 year. Although operatively treated patients showed significantly greater shoulder abduction strength (p = 0.036), elbow flexion strength (p = 0.021), functional hand positioning (p = 0.008) and return to recreational activities (p = 0.043) after 6 weeks, no statistically significant differences existed in any outcome measure at the 1-year follow-up. Conclusions Our findings indicate that the non-operative management of humeral midshaft fractures can be expected to have similar functional outcomes and patient satisfaction at 1 year, despite an early benefit to operative treatment. If no radiological evidence of fracture healing exists in non-operatively treated patients during early follow-up, a switch to surgical treatment results in good functional outcomes and patient satisfaction. Keywords: Humeral shaft fracture, Non-operative treatment, Functional brace, Operative treatment, Unreamed humeral nail (UHN), Prospective, Cohort study

Development and feasibility of a smartphone, ECG and GPS based system for remotely monitoring exercise in cardiac rehabilitation

Background Despite its efficacy and cost-effectiveness, exercise-based cardiac rehabilitation is undertaken by less than one-third of clinically eligible cardiac patients in every country for which data is available. Reasons for non-participation include the unavailability of hospital-based rehabilitation programs, or excessive travel time and distance. For this reason, there have been calls for the development of more flexible alternatives. Methodology and Principal Findings We developed a system to enable walking-based cardiac rehabilitation in which the patient's single-lead ECG, heart rate, GPS-based speed and location are transmitted by a programmed smartphone to a secure server for real-time monitoring by a qualified exercise scientist. The feasibility of this approach was evaluated in 134 remotely-monitored exercise assessment and exercise sessions in cardiac patients unable to undertake hospital-based rehabilitation. Completion rates, rates of technical problems, detection of ECG changes, pre- and post-intervention six minute walk test (6 MWT), cardiac depression and Quality of Life (QOL) were key measures. The system was rated as easy and quick to use. It allowed participants to complete six weeks of exercise-based rehabilitation near their homes, worksites, or when travelling. The majority of sessions were completed without any technical problems, although periodic signal loss in areas of poor coverage was an occasional limitation. Several exercise and post-exercise ECG changes were detected. Participants showed improvements comparable to those reported for hospital-based programs, walking significantly further on the post-intervention 6 MWT, 637 m (95% CI: 565–726), than on the pre-test, 524 m (95% CI: 420–655), and reporting significantly reduced levels of cardiac depression and significantly improved physical health-related QOL. Conclusions and Significance The system provided a feasible and very flexible alternative form of supervised cardiac rehabilitation for those unable to access hospital-based programs, with the potential to address a well-recognised deficiency in health care provision in many countries. Future research should assess its longer-term efficacy, cost-effectiveness and safety in larger samples representing the spectrum of cardiac morbidity and severity.

A randomised controlled trial to prevent hospital readmissions and loss of functional ability in high risk older adults: a study protocol

Background Older people have higher rates of hospital admission than the general population and higher rates of readmission due to complications and falls. During hospitalisation, older people experience significant functional decline which impairs their future independence and quality of life. Acute hospital services comprise the largest section of health expenditure in Australia and prevention or delay of disease is known to produce more effective use of services. Current models of discharge planning and follow-up care, however, do not address the need to prevent deconditioning or functional decline. This paper describes the protocol of a randomised controlled trial which aims to evaluate innovative transitional care strategies to reduce unplanned readmissions and improve functional status, independence, and psycho-social well-being of community-based older people at risk of readmission. Methods/Design The study is a randomised controlled trial. Within 72 hours of hospital admission, a sample of older adults fitting the inclusion/exclusion criteria (aged 65 years and over, admitted with a medical diagnosis, able to walk independently for 3 meters, and at least one risk factor for readmission) are randomised into one of four groups: 1) the usual care control group, 2) the exercise and in-home/telephone follow-up intervention group, 3) the exercise only intervention group, or 4) the in-home/telephone follow-up only intervention group. The usual care control group receive usual discharge planning provided by the health service. In addition to usual care, the exercise and in-home/telephone follow-up intervention group receive an intervention consisting of a tailored exercise program, in-home visit and 24 week telephone follow-up by a gerontic nurse. The exercise only and in-home/telephone follow-up only intervention groups, in addition to usual care receive only the exercise or gerontic nurse components of the intervention respectively. Data collection is undertaken at baseline within 72 hours of hospital admission, 4 weeks following hospital discharge, 12 weeks following hospital discharge, and 24 weeks following hospital discharge. Outcome assessors are blinded to group allocation. Primary outcomes are emergency hospital readmissions and health service use, functional status, psychosocial well-being and cost effectiveness. Discussion The acute hospital sector comprises the largest component of health care system expenditure in developed countries, and older adults are the most frequent consumers. There are few trials to demonstrate effective models of transitional care to prevent emergency readmissions, loss of functional ability and independence in this population following an acute hospital admission. This study aims to address that gap and provide information for future health service planning which meets client needs and lowers the use of acute care services.

A randomised, feasibility trial of a tele-health intervention for Acute Coronary Syndrome patients with depression ('MoodCare')

Background Coronary heart disease (CHD) and depression are leading causes of disease burden globally and the two often co-exist. Depression is common after Myocardial Infarction (MI) and it has been estimated that 15-35% of patients experience depressive symptoms. Co-morbid depression can impair health related quality of life (HRQOL), decrease medication adherence and appropriate utilisation of health services, lead to increased morbidity and suicide risk, and is associated with poorer CHD risk factor profiles and reduced survival. We aim to determine the feasibility of conducting a randomised, multi-centre trial designed to compare a tele-health program (MoodCare) for depression and CHD secondary prevention, with Usual Care (UC). Methods Over 1600 patients admitted after index admission for Acute Coronary Syndrome (ACS) are being screened for depression at six metropolitan hospitals in the Australian states of Victoria and Queensland. Consenting participants are then contacted at two weeks post-discharge for baseline assessment. One hundred eligible participants are to be randomised to an intervention or a usual medical care control group (50 per group). The intervention consists of up to 10 × 30-40 minute structured telephone sessions, delivered by registered psychologists, commencing within two weeks of baseline screening. The intervention focuses on depression management, lifestyle factors (physical activity, healthy eating, smoking cessation, alcohol intake), medication adherence and managing co-morbidities. Data collection occurs at baseline (Time 1), 6 months (post-intervention) (Time 2), 12 months (Time 3) and 24 months follow-up for longer term effects (Time 4). We are comparing depression (Cardiac Depression Scale [CDS]) and HRQOL (Short Form-12 [SF-12]) scores between treatment and UC groups, assessing the feasibility of the program through patient acceptability and exploring long term maintenance effects. A cost-effectiveness analysis of the costs and outcomes for patients in the intervention and control groups is being conducted from the perspective of health care costs to the government. Discussion This manuscript presents the protocol for a randomised, multi-centre trial to evaluate the feasibility of a tele-based depression management and CHD secondary prevention program for ACS patients. The results of this trial will provide valuable new information about potential psychological and wellbeing benefits, cost-effectiveness and acceptability of an innovative tele-based depression management and secondary prevention program for CHD patients experiencing depression.

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

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

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 evolving perspective on physical activity counselling by medical professionals

Background Physical inactivity is a modifiable risk factor for many chronic conditions and a leading cause of premature mortality. An increasing proportion of adults worldwide are not engaging in a level of physical activity sufficient to prevent or alleviate these adverse effects. Medical professionals have been identified as potentially powerful sources of influence for those who do not meet minimum physical activity guidelines. Health professionals are respected and expected sources of advice and they reach a large and relevant proportion of the population. Despite this potential, health professionals are not routinely practicing physical activity promotion. Discussion Medical professionals experience several known barriers to physical activity promotion including lack of time and lack of perceived efficacy in changing physical activity behaviour in patients. Furthermore, evidence for effective physical activity promotion by medical professionals is inconclusive. To address these problems, new approaches to physical activity promotion are being proposed. These include collaborating with community based physical activity behaviour change interventions, preparing patients for effective brief counselling during a consultation with the medical professional, and use of interactive behaviour change technology. Summary It is important that we recognise the latent risk of physical inactivity among patients presenting in clinical settings. Preparation for improving patient physical activity behaviours should commence before the consultation and may include physical activity screening. Medical professionals should also identify suitable community interventions to which they can refer physically inactive patients. Outsourcing the majority of a comprehensive physical activity intervention to community based interventions will reduce the required clinical consultation time for addressing the issue with each patient. Priorities for future research include investigating ways to promote successful referrals and subsequent engagement in comprehensive community support programs to increase physical activity levels of inactive patients. Additionally, future clinical trials of physical activity interventions should be evaluated in the context of a broader framework of outcomes to inform a systematic consideration of broad strengths and weaknesses regarding not only efficacy but cost-effectiveness and likelihood of successful translation of interventions to clinical contexts.