73 research outputs found

    Development of a novel benchmark method to identify and characterize best practices in home care across six European countries: design, baseline, and rationale of the IBenC project.

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    To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBACKGROUND: Europe's ageing society leads to an increased demand for long-term care, thereby putting a strain on the sustainability of health care systems. The 'Identifying best practices for care-dependent elderly by Benchmarking Costs and outcomes of Community Care' (IBenC) project aims to develop a new benchmark methodology based on quality of care and cost of care utilization to identify best practices in home care. The study's baseline data, methodology, and rationale are reported. METHODS: Home care organizations in Belgium, Finland, Germany, Iceland, Italy, and the Netherlands, home care clients of 65 years and over receiving home care, and professionals working in these organizations were included. Client data were collected according to a prospective longitudinal design with the interRAI Home Care instrument. Assessments were performed at baseline, after six and 12 months by trained (research) nurses. Characteristics of home care organizations and professionals were collected cross-sectionally with online surveys. RESULTS: Thirty-eight home care organizations, 2884 home care clients, and 1067 professionals were enrolled. Home care clients were mainly female (66.9%), on average 82.9 years (± 7.3). Extensive support in activities of daily living was needed for 41.6% of the sample, and 17.6% suffered cognitive decline. Care professionals were mainly female (93.4%), and over 45 years (52.8%). Considerable country differences were found. CONCLUSION: A unique, international, comprehensive database is established, containing in-depth information on home care organizations, their clients and staff members. The variety of data enables the development of a novel cost-quality benchmark method, based on interRAI-HC data. This benchmark can be used to explore relevant links between organizational efficiency and organizational and staff characteristics.7th Framework Programme of the European Commissio

    Is organizational justice climate at the workplace associated with individual-level quality of care and organizational affective commitment?:A multi-level, cross-sectional study on dentistry in Sweden

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    Purpose The aim of this study is to investigate whether organizational justice climate at the workplace level is associated with individual staff members’ perceptions of carequality and affective commitment to the workplace.Methods The study adopts a cross-sectional multi-level design. Data were collected using an electronic survey and a response rate of 75% was obtained. Organizational justice climate and affective commitment to the workplace were measured by items from Copenhagen Psychosocial Questionnaire and quality of care by three self-developed items. Non-managerial staff working at dental clinics with at least five respondents (n = 900 from 68 units) was included in analyses. A set of Level-2 random intercept models were built to predict individual-level organizational affective commitment and perceived quality of care from unit-level organizational justice climate, controlling for potential confoundingby group size, gender, age, and occupation.Results The results of the empty model showed substantial between-unit variation for both affective commitment (ICC-1 = 0.17) and quality of care (ICC-1 = 0.12). The overall results showed that the shared perception of organizational justice climate at the clinical unit level was significantly associated with perceived quality of care and affective commitment to the organization (p < 0.001).Conclusions Organizational justice climate at work unit level explained all variation in affective commitment among dental clinics and was associated with both the individualstaff members’ affective commitment and perceived quality of care. These findings suggest a potential for that addressing organizational justice climate may be a way to promote quality of care and enhancing affective commitment. However, longitudinal studies are needed to support causality in the examined relationships. Intervention research is also recommended to probe the effectiveness of actions increasingunit-level organizational justice climate and test their impact on quality of care and affective commitment

    Statistical discrimination of steroid profiles in doping control with support vector machines.

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    Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport
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