The internet of services and USDL

A prominent research focus, especially in the context of EU public funding, has been the systematic use of the Internet for new ways of value creation in the services sector. This idea of service networks in the Internet, frequently dubbed the Internet of Services or Web service ecosystems, wants to make services tradable in digital media. In order to enable communication and trade between providers and consumers of services, the Internet of Services requires a standard that creates a "commercial envelope" around a service. This is where the Unified Service Description Language (USDL) comes into play as a normative and balanced unification of service information. The unified description established by USDL is machine-processable, considers technical and business aspects of a service as well as functional and non-functional attributes.

Stakeholders' perceptions of data utility in the context of ERP outcomes

A substantial body of literature exists identifying factors contributing to under-performing Enterprise Resource Planning systems (ERPs), including poor communication, lack of executive support and user dissatisfaction (Calisir et al., 2009). Of particular interest is Momoh et al.’s (2010) recent review identifying poor data quality (DQ) as one of nine critical factors associated with ERP failure. DQ is central to ERP operating processes, ERP facilitated decision-making and inter-organizational cooperation (Batini et al., 2009). Crucial in ERP contexts is that the integrated, automated, process driven nature of ERP data flows can amplify DQ issues, compounding minor errors as they flow through the system (Haug et al., 2009; Xu et al., 2002). However, the growing appreciation of the importance of DQ in determining ERP success lacks research addressing the relationship between stakeholders’ requirements and perceptions of ERP DQ, perceived data utility and the impact of users’ treatment of data on ERP outcomes.

Quality and readability of information materials for people with brain tumours and their families

Written information is commonly used to inform patients about their disease and treatment, but must be evidence-based and understandable to be useful. This study assessed the quality of the content and the readability of information brochures for people affected by brain tumours. We randomly selected 18 publicly available brochures. Brochures were assessed by criteria to assess the quality of content using the DISCERN instrument. Readability was tested using three commonly used formulas, which yield the reading grade level required to comprehend the brochure (sixth grade level recommended). The mean overall DISCERN score was 3.17 out of a maximum of 5 (moderate quality); only one achieved a rating greater than 4 (high quality). Only one brochure met the sixth grade readability criteria. Although brochures may have accurate content, few satisfied all of the recommended criteria to evaluate their content. Existing brochures need to be critically reviewed and simplified, consumer-focused brochures produced.

The Industry Commission inquiry into charitable organisations : the draft report implications for the future of community services

In December 1993, the Commonwealth Assistant Treasurer., Mr George Gear announced an Inquiry into Charitable Organisations in Australia. The inquiry would be undertaken by the Industry Commission, the structure charged by the Commonwealth to oversight its micro-economic reform agenda. The inquiry had been on the Industry Commission's forward workplan since 1992. In July 1993 a draft terms of reference was prepared for comment by the State Premiers...

Nonprofit organisations face a restructuring state : the case of local social services in the Hunter region of New South Wales

This paper is concerned with certain of the characteristics of local social services, and their role in a restructuring Australian welfare state. I am particularly concerned with the distinctive gender characteristics of these organisations, because in comparison with most other organisations they have a feminised quality. This partly mirrors women's traditional role of undertaking the major part of the caring labour of society. However, simultaneously work in these organisation deviates from more traditional patterns where employed women occupy subordinate positions. In many community organisations, women occupy leadership roles. The analysis here is concerned with the apparently paradoxical nature of these organisations in their capacity to entrench traditional gender roles and to challenge these by allowing women to fill management positions. It is also concerned to examine whether changes that have been occurring in the community services sector over the last two decades are likely to enhance women's general position in the society, or diminish the power exercised by women. The paper draws in a preliminary way on a study of local services in the Hunter Region of NSW undertaken in the latter half of 1992. These preliminary findings are set against the broader picture of developments in the contemporary welfare state.

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.

Can you describe him for me? A technique for semantic person search in video

From a law enforcement standpoint, the ability to search for a person matching a semantic description (i.e. 1.8m tall, red shirt, jeans) is highly desirable. While a significant research effort has focused on person re-detection (the task of identifying a previously observed individual in surveillance video), these techniques require descriptors to be built from existing image or video observations. As such, person re-detection techniques are not suited to situations where footage of the person of interest is not readily available, such as a witness reporting a recent crime. In this paper, we present a novel framework that is able to search for a person based on a semantic description. The proposed approach uses size and colour cues, and does not require a person detection routine to locate people in the scene, improving utility in crowded conditions. The proposed approach is demonstrated with a new database that will be made available to the research community, and we show that the proposed technique is able to correctly localise a person in a video based on a simple semantic description.

Pandemic (H1N1) Influenza 2009 and Australian emergency departments : implications for policy, practice and pandemic preparedness

Objective: To describe the reported impact of Pandemic (H1N1) 2009 on EDs, so as to inform future pandemic policy, planning and response management. Methods: This study comprised an issue and theme analysis of publicly accessible literature, data from jurisdictional health departments, and data obtained from two electronic surveys of ED directors and ED staff. The issues identified formed the basis of policy analysis and evaluation. Results: Pandemic (H1N1) 2009 had a significant impact on EDs with presentation for patients with ‘influenza-like illness’ up to three times that of the same time in previous years. Staff reported a range of issues, including poor awareness of pandemic plans, patient and family aggression, chaotic information flow to themselves and the public, heightened stress related to increased workloads and lower levels of staffing due to illness, family care duties and redeployment of staff to flu clinics. Staff identified considerable discomfort associated with prolonged times wearing personal protective equipment. Staff believed that the care of non-flu patients was compromised during the pandemic as a result of overwork, distraction from core business and the difficulties associated with accommodating infectious patients in an environment that was not conducive. Conclusions: This paper describes the breadth of the impact of pandemics on ED operations. It identifies a need to address a range of industrial, management and procedural issues. In particular, there is a need for a single authoritative source of information, the re-engineering of EDs to accommodate infectious patients and organizational changes to enable rapid deployment of alternative sources of care.

Disaster triage : evidence, consistency and standard practice

Triage has military origins, with the initial purpose being to direct care to those most likely to be able to return to the battlefield. Conversely, modern disaster triage attempts to ensure both the prioritisation of care for those who need it most and a fair distribution of resources, so that health responders are able to ‘do the most for the most’...

Prevalence of breast cancer treatment sequelae over 6 years of follow-up

Background: There is a need to better describe and understand the prevalence of breast cancer treatment-related adverse effects amenable to physical therapy and rehabilitative exercise. Prior studies have been limited to single issues and lacked long term follow-up. The Pulling Through Study provides data on prevalence of adverse effects in breast cancer survivors followed over six years. Methods: A population-based sample of Australian women (n=287) diagnosed with invasive, unilateral breast cancer was followed for a median of 6.6 years and prospectively assessed for treatment-related complications at 6, 12, 18 months, and 6 years post-diagnosis. Assessments included post-surgical complications, skin or tissue reaction to radiation therapy, upper-body symptoms, lymphedema, 10% weight gain, fatigue, and upper-quadrant function. The proportion of women with positive indication for each complication and one or more complication was estimated using all available data at each time point. Women were only considered to have a specific complication if they reported the highest two levels of the Likert scale for self-reported issues. Results: At six years post-diagnosis over 60% of women experienced one or more side effects amenable to rehabilitative intervention. The proportion of women experiencing 3 or more side effects decreased throughout follow-up, while the proportion experiencing no side effects remained stable around 40% from 12 months to six years. Weight gain was the only complication to increase in prevalence over time. Conclusion: These data support the development of a multi-disciplinary prospective surveillance approach for the purposes of managing and treating adverse effects in breast cancer survivors.