743 resultados para Health and medical initiative updated
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Press Release from the School of Medicine Initiative published January 2005.
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Rates of survival of victims of sudden cardiac arrest (SCA) using cardio pulmonary resuscitation (CPR) have shown little improvement over the past three decades. Since registered nurses (RNs) comprise the largest group of healthcare providers in U.S. hospitals, it is essential that they are competent in performing the four primary measures (compression, ventilation, medication administration, and defibrillation) of CPR in order to improve survival rates of SCA patients. The purpose of this experimental study was to test a color-coded SMOCK system on: 1) time to implement emergency patient care measures 2) technical skills performance 3) number of medical errors, and 4) team performance during simulated CPR exercises. The study sample was 260 RNs (M 40 years, SD=11.6) with work experience as an RN (M 7.25 years, SD=9.42).Nurses were allocated to a control or intervention arm consisting of 20 groups of 5-8 RNs per arm for a total of 130 RNs in each arm. Nurses in each study arm were given clinical scenarios requiring emergency CPR. Nurses in the intervention group wore different color labeled aprons (smocks) indicating their role assignment (medications, ventilation, compression, defibrillation, etc) on the code team during CPR. Findings indicated that the intervention using color-labeled smocks for pre-assigned roles had a significant effect on the time nurses started compressions (t=3.03, p=0.005), ventilations (t=2.86, p=0.004) and defibrillations (t=2.00, p=.05) when compared to the controls using the standard of care. In performing technical skills, nurses in the intervention groups performed compressions and ventilations significantly better than those in the control groups. The control groups made significantly (t=-2.61, p=0.013) more total errors (7.55 SD 1.54) than the intervention group (5.60, SD 1.90). There were no significant differences in team performance measures between the groups. Study findings indicate use of colored labeled smocks during CPR emergencies resulted in: shorter times to start emergency CPR; reduced errors; more technical skills completed successfully; and no differences in team performance.
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Acknowledgements The authors would like to thank, Estelle Payerne (article screening, data extraction and bias assessment); Trish Boyton (article retrieval and screening) and Laura Cawley (search terms and title screening) for their invaluable help in conducting this systematic review. Funding The research was funded by the UK National Institute for Health Research Health Technology Assessment Programme.
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The authors would like to thank the participants of the Aberdeen 1936 Birth Cohort (ABC36). Image acquisition and image analysis for ABC36 were funded by the Alzheimer’s Research Trust (now Alzheimer’s Research UK). A.D.M., C.J.M., S.S., L.J.W., and R.T.S. have received grants from: Chief Scientist Office, Department of Health, Scottish Government; Biotechnology and Biological Sciences Research Council
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The authors would like to thank the participants of the Aberdeen 1936 Birth Cohort (ABC36). Image acquisition and image analysis for ABC36 were funded by the Alzheimer’s Research Trust (now Alzheimer’s Research UK). A.D.M., C.J.M., S.S., L.J.W., and R.T.S. have received grants from: Chief Scientist Office, Department of Health, Scottish Government; Biotechnology and Biological Sciences Research Council
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The recent crisis of the capitalistic economic system has altered the working conditions and occupations in the European Union. The recession situation has accelerated trends and has brought transformations that have been observed before. Changes have not looked the same way in all the countries of the Union. The social occupation norms, labour relations models and the type of global welfare provision can help underline some of these inequalities. Poor working conditions can expose workers to situations of great risk. This is one of the basic assumptions of the theoretical models and analytical studies of the approach to the psychosocial work environment. Changes in working conditions of the population seems to be important to explain in the worst health states. To observe these features in the current period of economic recession it has made a comparative study of trend through the possibilities of the European Working Conditions Survey in the 2005 and 2010 editions. It has also set different multivariate logistic regression models to explore potential partnerships with the worst conditions of employment and work. It seems that the economic crisis has intensified changes in working conditions and highlighted the effects of those conditions on the poor health of the working population. This conclusion can’t be extended for all EU countries; some differences were observed in terms of global welfare models.
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While coaching and customer involvement can enhance the improvement of health and social care, many organizations struggle to develop their improvement capability; it is unclear how best to accomplish this. We examined one attempt at training improvement coaches. The program, set in the Esther Network for integrated care in rural Jonkoping County, Sweden, included eight 1-day sessions spanning 7 months in 2011. A senior citizen joined the faculty in all training sessions. Aiming to discern which elements in the program were essential for assuming the role of improvement coach, we used a case-study design with a qualitative approach. Our focus group interviews included 17 informants: 11 coaches, 3 faculty members, and 3 senior citizens. We performed manifest content analysis of the interview data. Creating will, ideas, execution, and sustainability emerged as crucial elements. These elements were promoted by customer focusembodied by the senior citizen trainershared values and a solution-focused approach, by the supportive coach network and by participants' expanded systems understanding. These elements emerged as more important than specific improvement tools and are worth considering also elsewhere when seeking to develop improvement capability in health and social care organizations.
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Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.