836 resultados para Effectiveness in real-life practice
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Mode of access: Internet.
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Adapted from the play "Les filles de marbre" by Th. Barrière and L. Thiboust.--BMC.
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Includes references to boxing in chapters VII, XVII, XXV and interspersed throughout the rest.
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"Perceptions of Organizational Effectiveness over Organizational Life Cycles" written by Kim S. Cameron and David S. Whetten, posits a theory regarding organizational effectiveness criteria change as firms develop along the life cycle continuum. Induced from observations obtained from a simulation game, the Cameron and Whetten theory is applied in this article to two real organizations, Wendy's and McDonald's, with the intention of demonstrating that this theory is applicable in "real life" situations.
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Data access and analyses were funded by Boehringer Ingelheim, who played no role in the conduct or reporting of the study.
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Objective: Existing evidence suggests that family interventions can be effective in reducing relapse rates in schizophrenia and related conditions. Despite this, such interventions are not routinely delivered in Australian mental health services. The objective of the current study is to investigate the incremental cost-effectiveness ratios (ICERs) of introducing three types of family interventions, namely: behavioural family management (BFM); behavioural intervention for families (BIF); and multiple family groups (MFG) into current mental health services in Australia. Method: The ICER of each of the family interventions is assessed from a health sector perspective, including the government, persons with schizophrenia and their families/carers using a standardized methodology. A two-stage approach is taken to the assessment of benefit. The first stage involves a quantitative analysis based on disability-adjusted life years (DALYs) averted. The second stage involves application of 'second filter' criteria (including equity, strength of evidence, feasibility and acceptability to stakeholders) to results. The robustness of results is tested using multivariate probabilistic sensitivity analysis. Results: The most cost-effective intervention, in order of magnitude, is BIF (A$8000 per DALY averted), followed by MFG (A$21 000 per DALY averted) and lastly BFM (A$28 000 per DALY averted). The inclusion of time costs makes BFM more cost-effective than MFG. Variation of discount rate has no effect on conclusions. Conclusions: All three interventions are considered 'value-for-money' within an Australian context. This conclusion needs to be tempered against the methodological challenge of converting clinical outcomes into a generic economic outcome measure (DALY). Issues surrounding the feasibility of routinely implementing such interventions need to be addressed.
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Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.
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Measuring impact is the third in a series of publications commissioned by the Health Development Agency from the mid-life programme of work, which seeks to improve the health and wellbeing of people in the mid-life age group and reduce inequalities. The publications Making the case (HDA, 2003) and Taking action (HDA, 2004), and now Measuring impact, aim to support practitioners and policy makers at a local level in implementing and using the evidence of what works to develop mainstream practice and influence policy formulation in this population group.
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The rate of overweight and obese children and adolescents is rapidly increasing in developed countries. Although a decrease in sport practice may be one of the several factors implicated, data on recent trends are scarce. This article presents the trends in sport practice among Swiss adolescents between 1993 and 2002, comparing data from two surveys.
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Winter weather in Iowa is often unpredictable and can have an adverse impact on traffic flow. The Iowa Department of Transportation (Iowa DOT) attempts to lessen the impact of winter weather events on traffic speeds with various proactive maintenance operations. In order to assess the performance of these maintenance operations, it would be beneficial to develop a model for expected speed reduction based on weather variables and normal maintenance schedules. Such a model would allow the Iowa DOT to identify situations in which speed reductions were much greater than or less than would be expected for a given set of storm conditions, and make modifications to improve efficiency and effectiveness. The objective of this work was to predict speed changes relative to baseline speed under normal conditions, based on nominal maintenance schedules and winter weather covariates (snow type, temperature, and wind speed), as measured by roadside weather stations. This allows for an assessment of the impact of winter weather covariates on traffic speed changes, and estimation of the effect of regular maintenance passes. The researchers chose events from Adair County, Iowa and fit a linear model incorporating the covariates mentioned previously. A Bayesian analysis was conducted to estimate the values of the parameters of this model. Specifically, the analysis produces a distribution for the parameter value that represents the impact of maintenance on traffic speeds. The effect of maintenance is not a constant, but rather a value that the researchers have some uncertainty about and this distribution represents what they know about the effects of maintenance. Similarly, examinations of the distributions for the effects of winter weather covariates are possible. Plots of observed and expected traffic speed changes allow a visual assessment of the model fit. Future work involves expanding this model to incorporate many events at multiple locations. This would allow for assessment of the impact of winter weather maintenance across various situations, and eventually identify locations and times in which maintenance could be improved.
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With six targeted agents approved (sorafenib, sunitinib, temsirolimus, bevacizumab [+interferon], everolimus and pazopanib), many patients with metastatic renal cell carcinoma (mRCC) will receive multiple therapies. However, the optimum sequencing approach has not been defined. A group of European experts reviewed available data and shared their clinical experience to compile an expert agreement on the sequential use of targeted agents in mRCC. To date, there are few prospective studies of sequential therapy. The mammalian target of rapamycin (mTOR) inhibitor everolimus was approved for use in patients who failed treatment with inhibitors of vascular endothelial growth factor (VEGF) and VEGF receptors (VEGFR) based on the results from a Phase III placebo-controlled study; however, until then, the only licensed agents across the spectrum of mRCC were VEGF(R) inhibitors (sorafenib, sunitinib and bevacizumab + interferon), and as such, a large body of evidence has accumulated regarding their use in sequence. Data show that sequential use of VEGF(R) inhibitors may be an effective treatment strategy to achieve prolonged clinical benefit. The optimal place of each targeted agent in the treatment sequence is still unclear, and data from large prospective studies are needed. The Phase III AXIS study of second-line sorafenib vs. axitinib (including post-VEGF(R) inhibitors) has completed, but the data are not yet published; other ongoing studies include the Phase III SWITCH study of sorafenib-sunitinib vs. sunitinib-sorafenib (NCT00732914); the Phase III 404 study of temsirolimus vs. sorafenib post-sunitinib (NCT00474786) and the Phase II RECORD 3 study of sunitinib-everolimus vs. everolimus-sunitinib (NCT00903175). Until additional data are available, consideration of patient response and tolerability to treatment may facilitate current decision-making regarding when to switch and which treatment to switch to in real-life clinical practice.