902 resultados para Modelling Health Benefit


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Objective: Although several studies have demonstrated a relationship between staff engagement and health and wellbeing, none has analysed the association with presenteeism in the National Health Service (NHS) context. Our aim is to determine whether there is a relationship between presenteeism and staff engagement. Methods: A hierarchical logistic multilevel modelling of cross-sectional data from the NHS staff survey (2009) was conducted. We controlled for a range of demographic and socioeconomic background variables, including ethnic group, gender, age and occupational group. The sample was 156,951 respondents across all 390 English NHS trusts, each providing a random sample of employees. Engagement was measured using three facets: motivation, advocacy and involvement, which were also used in a composite score. Results: Therewas a low-to-moderate negative correlation between presenteeismand staff engagement: odds ratio 0.42 (95% confidence interval [CI] 0.42-0.43) for overall staff engagement and 0.53 (95% CI 0.52-0.54) for staff advocacy of the trust; 0.53 (95% CI 0.52-0.54) for motivation and 0.50 (95% CI 0.49-0.51) for involvement. Conclusions: Putting pressure on health-care staff to come to work when unwell is associated with poorer staff engagement with their jobs. © The Royal Society of Medicine Press Ltd 2011.

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Prior research has found entrepreneurs to experience significantly higher job control and job demands compared with employees. This suggests that entrepreneurs have so-called active jobs and thus may benefit from positive health consequences. The present research compared entrepreneurs' health with employees' health in a national representative sample with regard to the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) diagnoses of somatic diseases, the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) diagnoses of mental disorders, blood pressure, well-being (life-satisfaction) as well as behavioural health indicators (sick days, physician visits). Entrepreneurs showed significantly lower overall somatic and mental morbidity, lower blood pressure, lower prevalence rates of hypertension, and somatoform disorders, as well as higher well-being and more favourable behavioural health indicators. The results are discussed with regard to the active job hypothesis and recommendations for future research are provided.

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One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

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Multiscale systems that are characterized by a great range of spatial–temporal scales arise widely in many scientific domains. These range from the study of protein conformational dynamics to multiphase processes in, for example, granular media or haemodynamics, and from nuclear reactor physics to astrophysics. Despite the diversity in subject areas and terminology, there are many common challenges in multiscale modelling, including validation and design of tools for programming and executing multiscale simulations. This Theme Issue seeks to establish common frameworks for theoretical modelling, computing and validation, and to help practical applications to benefit from the modelling results. This Theme Issue has been inspired by discussions held during two recent workshops in 2013: ‘Multiscale modelling and simulation’ at the Lorentz Center, Leiden (http://www.lorentzcenter.nl/lc/web/2013/569/info.php3?wsid=569&venue=Snellius), and ‘Multiscale systems: linking quantum chemistry, molecular dynamics and microfluidic hydrodynamics’ at the Royal Society Kavli Centre. The objective of both meetings was to identify common approaches for dealing with multiscale problems across different applications in fluid and soft matter systems. This was achieved by bringing together experts from several diverse communities.

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Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages.

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Purpose. The Internet has provided an unprecedented opportunity for psychotropic medication consumers, a traditionally silenced group in clinical trial research, to have voice by contributing to the construction of drug knowledge in an immediate, direct manner. Currently, there are no systematic appraisals of the potential of online consumer drug reviews to contribute to drug knowledge. The purpose of this research was to explore the content of drug information on various websites representing themselves as consumer- and expert-constructed, and as a practical consideration, to examine how each source may help and hinder treatment decision-making.^ Methodology. A mixed-methods research strategy utilizing a grounded theory approach was used to analyze drug information on 5 exemplar websites (3 consumer- and 2 expertconstructed) for 2 popularly prescribed psychotropic drugs (escitalopram and quetiapine). A stratified simple random sample was used to select 1,080 consumer reviews from the websites (N=7,114) through February 2009. Text was coded using QDA Miner 3.2 software by Provalis Research. A combination of frequency tables, descriptive excerpts from text, and chi-square tests for association were used throughout analyses.^ Findings. The most frequently mentioned effects by consumers taking either drug were related to psychological/behavioral symptoms and sleep. Consumers reported many of the same effects as found on expert health sites, but provided more descriptive language and situational examples. Expert labels of less serious on certain effects were not congruent with the sometimes tremendous burden described by consumers. Consumers mentioned more than double the themes mentioned in expert text, and demonstrated a diversity and range of discourses around those themes.^ Conclusions. Drug effects from each source were complete relative to the information provided in the other, but each also offered distinct advantages. Expert health sites provided concise summaries of medications’ effects, while consumer reviews had the added advantage of concrete descriptions and greater context. In short, consumer reviews better prepared potential consumers for what it’s like to take psychotropic drugs. Both sources of information benefit clinicians and consumers in making informed treatment-related decisions. Social work practitioners are encouraged to thoughtfully utilize online consumer drug reviews as a legitimate additional source for assisting clients in learning about treatment options.^

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The United States Census Bureau (2006) reported that in 2005 more than 46 million Americans lacked health insurance, and that by 2019 national spending for health care would exceed $4.5 trillion (Centers for Medicare & Medicaid Services, 2010). Because those numbers are expected to increase, health tourists are seeking better opportunities for low-cost, high-quality treatment in other countries, plus the added benefit of experiencing foreign cultures. Health tourism is a rapidly growing market in both advanced and developing countries. The purpose of this study was to develop an applicable model of health tourism, the Jeju-Style Health Tourism Model, for Jeju Special Self-Governing Province, in the Republic of Korea (South Korea) and to provide other cities and countries with its implications. This study employed a focus group, indepth interviews, and content analysis to discover important factors in developing the model. The results suggested that four major sources must be executed together to maximize the benefits of health tourism development. On a foundation of natural resources, knowledge-based resources were most important (54.5%), followed by artificial resources (25.7%), and expenses-based resources (19.8%).

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Background There is substantial evidence from high income countries that neighbourhoods have an influence on health independent of individual characteristics. However, neighbourhood characteristics are rarely taken into account in the analysis of urban health studies from developing countries. Informal urban neighbourhoods are home to about half of the population in Aleppo, the second largest city in Syria (population>2.5 million). This study aimed to examine the influence of neighbourhood socioeconomic status (SES) and formality status on self-rated health (SRH) of adult men and women residing in formal and informal urban neighbourhoods in Aleppo. Methods The study used data from 2038 survey respondents to the Aleppo Household Survey, 2004 (age 18–65 years, 54.8% women, response rate 86%). Respondents were nested in 45 neighbourhoods. Five individual-level SES measures, namely education, employment, car ownership, item ownership and household density, were aggregated to the level of neighbourhood. Multilevel regression models were used to investigate associations. Results We did not find evidence of important SRH variation between neighbourhoods. Neighbourhood average of household item ownership was associated with a greater likelihood of reporting excellent SRH in women; odds ratio (OR) for an increase of one item on average was 2.3 (95% CI 1.3-4.4 (versus poor SRH)) and 1.7 (95% CI 1.1-2.5 (versus normal SRH)), adjusted for individual characteristics and neighbourhood formality. After controlling for individual and neighbourhood SES measures, women living in informal neighbourhoods were less likely to report poor SRH than women living in formal neighbourhoods (OR= 0.4; 95% CI (0.2- 0.8) (versus poor SRH) and OR=0.5; 95%; CI (0.3-0.9) (versus normal SRH). Conclusions Findings support evidence from high income countries that certain characteristic of neighbourhoods affect men and women in different ways. Further research from similar urban settings in developing countries is needed to understand the mechanisms by which informal neighbourhoods influence women’s health.

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Women are a high-risk population for cardiovascular diseases (CVD); however relationships between CVD and subpopulations of mothers are sparse. A secondary data analysis of the 2006 Health Survey of Adults and Children in Bermuda was conducted to compare the prevalence of CVD risk factors in single (n=77) and partnered (n=241) mothers. A higher percentage of single mothers were Black (p25 kg/m2 (p=0.01) and reported high blood pressure (p=0.004) and high cholesterol (0.017). Single mothers were nearly three times (OR=2.66) more likely to experience high blood pressure and two times (OR= 2.22) more likely to have high cholesterol. Single mothers may benefit from nutrition education programs related to lowering CVD risk.

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Funding sources: The study was funded by a research grant from the Chief Scientist’s Office of the Scottish Government Health and Social Care Directorates (CZH/4/971). The funder played no role in study design, data collection, data analysis, manuscript preparation and/or publication decisions. The views expressed herein are those of the authors and do not necessarily reflect those of the funder.

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Acknowledgements and funding We would like to thank the GPs who took part in this study. We would also like to thank Marie Pitkethly and Gail Morrison for their help and support in recruiting GPs to the study. WIME was funded by the Chief Scientist Office, grant number CZH/4/610. The Health Services Research Unit, University of Aberdeen, is core funded by the Chief Scientist Office of the Scottish Government Health Directorates.