7,746 research outputs found
Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology.
No full textContains fulltext :
97171.pdf (Author’s version postprint ) (Open Access)BACKGROUND: Current human resources planning models in nursing are unreliable and ineffective as they consider volumes, but ignore effects on quality in patient care. The project RN4CAST aims innovative forecasting methods by addressing not only volumes, but quality of nursing staff as well as quality of patient care. METHODS/DESIGN: A multi-country, multilevel cross-sectional design is used to obtain important unmeasured factors in forecasting models including how features of hospital work environments impact on nurse recruitment, retention and patient outcomes. In each of the 12 participating European countries, at least 30 general acute hospitals were sampled. Data are gathered via four data sources (nurse, patient and organizational surveys and via routinely collected hospital discharge data). All staff nurses of a random selection of medical and surgical units (at least 2 per hospital) were surveyed. The nurse survey has the purpose to measure the experiences of nurses on their job (e.g. job satisfaction, burnout) as well as to allow the creation of aggregated hospital level measures of staffing and working conditions. The patient survey is organized in a sub-sample of countries and hospitals using a one-day census approach to measure the patient experiences with medical and nursing care. In addition to conducting a patient survey, hospital discharge abstract datasets will be used to calculate additional patient outcomes like in-hospital mortality and failure-to-rescue. Via the organizational survey, information about the organizational profile (e.g. bed size, types of technology available, teaching status) is collected to control the analyses for institutional differences.This information will be linked via common identifiers and the relationships between different aspects of the nursing work environment and patient and nurse outcomes will be studied by using multilevel regression type analyses. These results will be used to simulate the impact of changing different aspects of the nursing work environment on quality of care and satisfaction of the nursing workforce. DISCUSSION: RN4CAST is one of the largest nurse workforce studies ever conducted in Europe, will add to accuracy of forecasting models and generate new approaches to more effective management of nursing resources in Europe
Report of the Irish RN4CAST Study 2009-2011: A nursing workforce under strain
No full textForeword:
The RN4CAST consortium research study, funded by the European Commission, has provided a unique opportunity to gain insight into both organisational and nurse staffing issues across the acute hospital sector in Ireland. As part of the RN4CAST (Ireland) study, for the first time, both hospitals and medical and surgical units within thirty out of a possible thirty-one acute hospitals (with over one hundred beds) have been surveyed. Data were collected in 2009-2010.
The work of the international consortium also enables comparisons of Irish findings with key findings internationally. For example it has proved possible to compare such issues as patient – to - nurse ratios and patient - to health care-staff ratios across the 12 partner countries of the consortium. This is also the case, for example, for nurse burnout levels, job satisfaction and nurse perceptions of safety and quality of care.
RN4CAST (Ireland) provides a portrayal of the Irish acute hospital sector as operating in a context of dynamic challenge and change from both internal and external drivers. There is considerable evidence of significant strain on the nursing staff working in the sector. Nursing staff indicate concern regarding aspects of the quality and safety of patient care and the availability of sufficient staff and resources to do their job properly.
We are of the view that unless these and a number of other issues raised in this report are managed effectively, there will be detrimental impacts on patient care, patient safety and retention and recruitment of high quality nursing staff for our health service
Report of the Irish RN4CAST Studey 2009-2011: a nursing workforce under strain.
No full textForeword: The RN4CAST consortium research study, funded by the European Commission, has provided a unique opportunity to gain insight into both organisational and nurse staffing issues across the acute hospital sector in Ireland. As part of the RN4CAST (Ireland) study, for the first time, both hospitals and medical and surgical units within thirty out of a possible thirty-one acute hospitals (with over one hundred beds) have been surveyed. Data were collected in 2009-2010. The work of the international consortium also enables comparisons of Irish findings with key findings internationally. For example it has proved possible to compare such issues as patient – to - nurse ratios and patient - to health care-staff ratios across the 12 partner countries of the consortium. This is also the case, for example, for nurse burnout levels, job satisfaction and nurse perceptions of safety and quality of care. RN4CAST (Ireland) provides a portrayal of the Irish acute hospital sector as operating in a context of dynamic challenge and change from both internal and external drivers. There is considerable evidence of significant strain on the nursing staff working in the sector. Nursing staff indicate concern regarding aspects of the quality and safety of patient care and the availability of sufficient staff and resources to do their job properly. We are of the view that unless these and a number of other issues raised in this report are managed effectively, there will be detrimental impacts on patient care, patient safety and retention and recruitment of high quality nursing staff for our health service
Structural characteristics of hospitals and nurse-reported care quality, work environment, burnout and leaving intentions
No full textAim To investigate whether hospital characteristics not readily susceptible to change (i.e. hospital size, university status, and geographic location) are associated with specific self-reported nurse outcomes. Background Research often focuses on factors within hospitals (e.g. work environment), which are susceptible to change, rather than on structural factors in their own right. However, numerous assumptions exist about the role of structural factors that may lead to a sense of pessimism and undermine efforts at constructive change. Method Data was derived from survey questions on assessments of work environment and satisfaction, intention to leave, quality of care and burnout (measured by the Maslach Burnout Inventory), from a population-based sample of 11 000 registered nurses in Sweden. Mixed model regressions were used for analysis. Result Registered nurses in small hospitals were slightly more likely to rank their working environment and quality of nursing care better than others. For example 23% of staff in small hospitals were very satisfied with the work environment compared with 20% in medium-sized hospitals and 21% in large hospitals. Registered nurses in urban areas, who intended to leave their job, were more likely to seek work in another hospital (38% vs. 32%). Conclusion While some structural factors were related to nurse-reported outcomes in this large sample, the associations were small or of questionable importance. Implications for nursing management The influence of structural factors such as hospital size on nurse-reported outcomes is small and unlikely to negate efforts to improve work environment
Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
No full textBackground: Current human resources planning models in nursing are unreliable and ineffective asthey consider volumes, but ignore effects on quality in patient care. The project RN4CAST aims innovative forecasting methods by addressing not only volumes, but quality of nursing staff as well as quality of patient care.Methods/Design: A multi-country, multilevel cross sectional design is used to obtain important unmeasured factors in forecasting models including how features of hospital work environments impact on nurse recruitment, retention and patient outcomes. In each of the 12 participating European countries, at least 30 general acute hospitals were sampled. Data are gathered via four data sources (nurse, patient and organizational surveys and via routinely collected hospital discharge data). All staff nurses of a random selection of medical and surgical units (at least 2 per hospital) were surveyed. The nurse survey has the purpose to measure the experiences of nurses on their job (e.g. job satisfaction, burnout) as well as to allow the creation of aggregated hospital level measures of staffing and working conditions. The patient survey is organized in a sub-sample of countries and hospitals using a one-day census approach to measure the patient experiences with medical and nursing care. In addition to conducting a patient survey, hospital discharge abstract datasets will be used to calculate additional patient outcomes like in-hospital mortality and failure-to-rescue. Via the organizational survey, information about the organizational profile (e.g. bed size, types of technology available, teaching status) is collected to control the analyses for institutional differences. This information will be linked via common identifiers and the relationships between different aspects of the nursing work environment and patient and nurse outcomes will be studied by using multilevel regression type analyses. These results will be used to simulate the impact of changing different aspects of the nursing work environment on quality of care and satisfaction of the nursing workforce .Discussion: RN4CAST is one of the largest nurse workforce studies ever conducted in Europe, will add to accuracy of forecasting models and generate new approaches to more effective management of nursing resources in Europe.<br/
SHui open data research platform
No full textData collected and revised by individual instutions of the Shui-Consortium. Publication by the EU-China Consortium SHui.For each data-file, the author (institution) of the file is given as “operator”.-- At project end, June 30th, 2022.-- For each data-file, the author/data owner for citation is given as “operator” and “contact”.-- Plot data as .csv; catchment data ad libitum.Spatial situation data: Plot data and catchment data available; country, latitude, and longitude coordinates given.-- Temporal situation data: Long-term and single-season data available. Start and end date for each data file given.CC BY-SA. No embargo. The release on the Shui download site and CSIC repository implies expiration of any embargo delivered by the data owner.Project Co-ordinators: Dr. Jose Alfonso Gómez Calero (Instituto de Agricultura Sostenible (IAS-CISC), Dr. Weifeng Xu (Fujian Agriculture and Forest University, FAFU).This data set contains data from the SHui open-data platform for sharing long-term agricultural experiments aimed to optimizing yield and soil and water. Data and additional material are available under https://shui.boku.ac.at/shui/public/startAlphanumeric data measured at hydrologic and agronomical experiments (e.g., plant development, soil properties, hydrology, erosion, management).Further information on the data, project, partners, and publications under https://www.shui-eu.org/EU-China Consortium SHui: European Union Project 773903 and Chinese MOST.Peer reviewe
Enrichment and characterization of a bacteria consortium capable of heterotrophic nitrification and aerobic denitrification at low temperature
No full textNitrogen removal in wastewater treatment plants is usually severely inhibited under cold temperature. The present study proposes bioaugmentation using psychrotolerant heterotrophic nitrification-aerobic denitrification consortium to enhance nitrogen removal at low temperature. A functional consortium has been successfully enriched by stepped increase in DO concentration. Using this consortium, the specific removal rates of ammonia and nitrate at 10 degrees C reached as high as 3.1 mg N/(g SS h) and 9.6 mg N/ (g SS h), respectively. PCR-DGGE and clone library analysis both indicated a significant reduction in bacterial diversity during enrichment. Phylogenetic analysis based on nearly full-length 16S rRNA genes showed that Alphaproteobacteria. Deltaproteobacteria and particularly Bacteroidetes declined while Gammaproteobacteria (all clustered into Pseudomonas sp.) and Betaproteobacteria (mainly Rhodoferax ferrireducens) became dominant in the enriched consortium. It is likely that Pseudomonas spp. played a major role in nitrification and denitrification, while R. ferrireducens and its relatives utilized nitrate as both electron acceptor and nitrogen source. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.</p
Arabic Treebank : Part 2 v 3.1
No full textArabic Treebank: Part 2 (ATB2) v 3.1 , Linguistic Data Consortium (LDC) catalog number LDC2011T09 and isbn 1-58563-590-1, was developed at LDC. It consists of 501 newswire stories from Ummah Press with part-of-speech (POS), morphology, gloss and syntactic treebank annotation in accordance with the Penn Arabic Treebank (PATB) Guidelines developed in 2008 and 2009
Publisher Correction: Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes (Nature Genetics, (2018), 50, 4, (524-537), 10.1038/s41588-018-0058-3)
No full textIn the HTML version of this article initially published, the author groups ‘AFGen Consortium’, ‘Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium’, ‘International Genomics of Blood Pressure (iGEN-BP) Consortium’, ‘INVENT Consortium’, ‘STARNET’, ‘BioBank Japan Cooperative Hospital Group’, ‘COMPASS Consortium’, ‘EPIC-CVD Consortium’, ‘EPIC-InterAct Consortium’, ‘International Stroke Genetics Consortium (ISGC)’, ‘METASTROKE Consortium’, ‘Neurology Working Group of the CHARGE Consortium’, ‘NINDS Stroke Genetics Network (SiGN)’, ‘UK Young Lacunar DNA Study’ and ‘MEGASTROKE Consortium’ appeared at the end of the author list but should have appeared earlier in the list. In addition, the author group ‘MEGASTROKE Consortium’ was duplicated, and its members were not displayed in the ‘Author information’ section. The errors have been corrected in the HTML version of the article
Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes
No full textOnline Correction for: https://doi.org/10.1038/s41586-020-2493-4 | Erratum for https://bura.brunel.ac.uk/handle/2438/21299In the version of this article initially published, two members of the ENCODE Project Consortium were missing from the author list. Rizi Ai (Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA) and Shantao Li (Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA) are now included in the author list. These errors have been corrected in the online version of the article : 'Expanded encyclopaedias of DNA elements in the human and mouse genomes'.https://www.nature.com/articles/s41586-021-04226-3https://www.nature.com/articles/s41586-021-04226-
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