127 resultados para PERICHROMIC INDICATORS


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Objectives It is widely assumed improving care in residential facilities will improve quality of life (QoL), but little research has explored this relationship. The Clinical Care Indicators (CCI) Tool was developed to fill an existing gap in quality assessment within Australian residential aged care facilities and it was used to explore potential links between clinical outcomes and QoL. Design and Setting Clinical outcome and QoL data were collected within four residential facilities from the same aged care provider. Subjects Subjects were 82 residents of four facilities. Outcome Measures Clinical outcomes were measured using the CCI Tool and QoL data was obtained using the Australian WHOQOL‑100. Results Independent t‑test analyses were calculated to compare individual CCIs with each domain of the WHOQOL‑100, while Pearson’s product moment coefficients (r) were calculated between the total number of problem indicators and QoL scores. Significant results suggested poorer clinical outcomes adversely affected QoL. Social and spiritual QoL were particularly affected by clinical outcomes and poorer status in hydration, falls and depression were most strongly associated with lower QoL scores. Poorer clinical status as a whole was also significantly correlated with poorer QoL. Conclusions Hydration, falls and depression were most often associated with poorer resident QoL and as such appear to be key areas for clinical management in residential aged care. However, poor clinical outcomes overall also adversely affected QoL, which suggests maintaining optimum clinical status through high quality nursing care, would not only be important for resident health but also for enhancing general life quality.

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This article attempts to explore the concept of scientific community at the macro-national level in the context of Iran. Institutionalisation of science and its professional growth has been constrained by several factors. The article first conceptualises the notion of science community as found in the literature in the context of Iran, and attempts to map through some indicators. The main focus, however, lies in mapping some institutional problems through empirical research. This was undertaken in 2002–04 in order to analyse the structure of the scientific community in Iran in the ‘exact sciences’ (mathematics, physics, chemistry, biology and earth sciences). The empirical work was done in two complementary perspectives: through a questionnaire and statistical analysis of it, and through semistructured interviews with the researchers. There are number of problems confronting scientists in Iran. Facilities provided by institutions is one of the major problems of research. Another is the tenuous cooperation among scientists. This is reported by most of the researchers, who deplore the lack of cooperation among their group. Relationships are mostly with the Ph.D. students and only marginally with colleagues. Our research shows that the more brilliant the scientists, the more frustrated they are from scientific institutions in Iran. Medium-range researchers seem to be much happier about the scientific institution to which they belong than the brighter scholars. The scientific institutions in Iran seem to be built for the needs of the former rather than the latter. These institutions seem not to play a positive role in the case of the best scientists. On the whole, many ingredients of the scientific community, at least at its inception, are present among Iranian scientists: the strong desire for scientific achievement in spite of personal, institutional and economic problems.

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Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

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Cohen (1977) reviewed the then current research on occupational safety and stated that both strong company commitment to safety, and communication between all levels of a company are the most influential factors to improving safety. Other relevant factors included careful selection of staff, and early and continuous training throughout the lifetime with the company. These continue to be important factors in OHS today. There has been a continued decrease in the injury rates since Cohen’s review within the Australian construction industry, however, the construction industry has far more injuries and ill-health than the Australian average, with one fatality occurring on average per week in the Australian Construction Industry. The Fatality rate in the building and construction industry remains three times higher than the national average, and 15% of all industry fatalities are in the building and construction industry. In addition the construction industry pays one of the highest workers’ compensation premium rates – in 2001 alone approximately 0.5% ($267 million) of revenue would have to be allocated to the direct cost of 1998/99 compensations (Office of the Federal Safety Commissioner, 2006). Based on these statistics there is a need to measure and improve safety performance within the construction industry.

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The advantages of using a balanced approach to measurement of overall organisational performance are well-known. We examined the effects of a balanced approach in the more specific domain of measuring innovation effectiveness in 144 small to medium sized companies in Australia and Thailand. We found that there were no differences in the metrics used by Australian and Thai companies. In line with our hypotheses, we found that those SMEs that took a balanced approach were more likely to perceive benefits of implemented innovations than those that used only a financial approach to measurement. The perception of benefits then had a subsequent effect on overall attitudes towards innovation. The study shows the importance of measuring both financial and non-financial indicators of innovation effectiveness within SMEs and discusses ways in which these can be conducted with limited resources.

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In recent years, practitioners and researchers alike have turned their attention to knowledge management (KM) in order to increase organisational performance (OP). As a result, many different approaches and strategies have been investigated and suggested for how knowledge should be managed to make organisations more effective and efficient. However, most research has been undertaken in the for-profit sector, with only a few studies focusing on the benefits nonprofit organisations might gain by managing knowledge. This study broadly investigates the impact of knowledge management on the organisational performance of nonprofit organisations. Organisational performance can be evaluated through either financial or non-financial measurements. In order to evaluate knowledge management and organisational performance, non-financial measurements are argued to be more suitable given that knowledge is an intangible asset which often cannot be expressed through financial indicators. Non-financial measurement concepts of performance such as the balanced scorecard or the concept of Intellectual Capital (IC) are well accepted and used within the for-profit and nonprofit sectors to evaluate organisational performance. This study utilised the concept of IC as the method to evaluate KM and OP in the context of nonprofit organisations due to the close link between KM and IC: Indeed, KM is concerned with managing the KM processes of creating, storing, sharing and applying knowledge and the organisational KM infrastructure such as organisational culture or organisational structure to support these processes. On the other hand, IC measures the knowledge stocks in different ontological levels: at the individual level (human capital), at the group level (relational capital) and at the organisational level (structural capital). In other words, IC measures the value of the knowledge which has been managed through KM. As KM encompasses the different KM processes and the KM infrastructure facilitating these processes, previous research has investigated the relationship between KM infrastructure and KM processes. Organisational culture, organisational structure and the level of IT support have been identified as the main factors of the KM infrastructure influencing the KM processes of creating, storing, sharing and applying knowledge. Other research has focused on the link between KM and OP or organisational effectiveness. Based on existing literature, a theoretical model was developed to enable the investigation of the relation between KM (encompassing KM infrastructure and KM processes) and IC. The model assumes an association between KM infrastructure and KM processes, as well as an association between KM processes and the various levels of IC (human capital, structural capital and relational capital). As a result, five research questions (RQ) with respect to the various factors of the KM infrastructure as well as with respect to the relationship between KM infrastructure and IC were raised and included into the research model: RQ 1 Do nonprofit organisations which have a Hierarchy culture have a stronger IT support than nonprofit organisations which have an Adhocracy culture? RQ 2 Do nonprofit organisations which have a centralised organisational structure have a stronger IT support than nonprofit organisations which have decentralised organisational structure? RQ 3 Do nonprofit organisations which have a stronger IT support have a higher value of Human Capital than nonprofit organisations which have a less strong IT support? RQ 4 Do nonprofit organisations which have a stronger IT support have a higher value of Structural Capital than nonprofit organisations which have a less strong IT support? RQ 5 Do nonprofit organisations which have a stronger IT support have a higher value of Relational Capital than nonprofit organisations which have a less strong IT support? In order to investigate the research questions, measurements for IC were developed which were linked to the main KM processes. The final KM/IC model contained four items for evaluating human capital, five items for evaluating structural capital and four items for evaluating relational capital. The research questions were investigated through empirical research using a case study approach with the focus on two nonprofit organisations providing trade promotions services through local offices worldwide. Data for the investigation of the assumptions were collected via qualitative as well as quantitative research methods. The qualitative study included interviews with representatives of the two participating organisations as well as in-depth document research. The purpose of the qualitative study was to investigate the factors of the KM infrastructure (organisational culture, organisational structure, IT support) of the organisations and how these factors were related to each other. On the other hand, the quantitative study was carried out through an online-survey amongst staff of the various local offices. The purpose of the quantitative study was to investigate which impact the level of IT support, as the main instrument of the KM infrastructure, had on IC. Overall several key themes were found as a result of the study: • Knowledge Management and Intellectual Capital were complementary with each other, which should be expressed through measurements of IC based on KM processes. • The various factors of the KM infrastructure (organisational culture, organisational structure and level of IT support) are interdependent. • IT was a primary instrument through which the different KM processes (creating, storing, sharing and applying knowledge) were performed. • A high level of IT support was evident when participants reported higher level of IC (human capital, structural capital and relational capital). The study supported previous research in the field of KM and replicated the findings from other case studies in this area. The study also contributed to theory by placing the KM research within the nonprofit context and analysing the linkage between KM and IC. From the managerial perspective, the findings gave clear indications that would allow interested parties, such as nonprofit managers or consultants to understand more about the implications of KM on OP and to use this knowledge for implementing efficient and effective KM strategies within their organisations.