2 resultados para Specialization and Integration

em Nottingham eTheses


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This paper reports the results of a postal survey of intermediate care co-ordinators (ICCs) on the organization and delivery of intermediate care services for older people in England, conducted between November 2003 and May 2004. Questionnaires, which covered a range of issues with a variety of quantitative, ‘tick-box’ and open-ended questions, were returned by 106 respondents, representing just over 35% of primary care trusts (PCTs). We discuss the role of ICCs, the integration of local systems of intermediate care provision, and the form, function and model of delivery of services described by respondents. Using descriptive and statistical analysis of the responses, we highlight in particular the relationship between provision of admission avoidance and supported discharge, the availability of 24-hour care, and the locations in which care is provided, and relate our findings to the emerging evidence base for intermediate care, guidance on implementation from central government, and debate in the literature. Whilst the expansion and integration of intermediate care appear to be continuing apace, much provision seems concentrated in supported discharge services rather than acute admission avoidance, and particularly in residential forms of post-acute intermediate care. Supported discharge services tend to be found in residential settings, while admission avoidance provision tends to be non-residential in nature. Twenty-four hour care in non-residential settings is not available in several responding PCTs. These findings raise questions about the relationship between the implementation of intermediate care and the evidence for and aims of the policy as part of NHS modernization, and the extent to which intermediate care represents a genuinely novel approach to the care and rehabilitation of older people.

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Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.