5 resultados para Medical lab data

em Nottingham eTheses


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The paper explores the attitudes of medical physicians towards adverse incident reporting in health care, with particular focus on the inhibiting factors or barriers to participation. It is recognised that there are major barriers to medical reporting, such as the ‘culture of blame’. There are, however, few detailed qualitative accounts of medical culture as it relates to incident reporting. Drawing on a 2-year qualitative case study in the UK, this paper presents data gathered from 28 semi-structured interviews with specialist physicians. The findings suggest that blame certainly inhibits medical reporting, but other cultural issues were also significant. It was commonly accepted by doctors that errors are an ‘inevitable’ and potentially unmanageable feature of medical work and incident reporting was therefore ‘pointless’. It was also found that reporting was discouraged by an anti-bureaucratic sentiment and rejection of excessive administrative duties. Doctors were also apprehensive about the increased potential for managers and non-physicians to engage in the regulation of medical quality through the use of incident data. The paper argues that the promotion of incident reporting must engage with more than the ubiquitous ‘culture of blame’ and instead address the ‘culture of medicine’, especially as it relates to the collegial and professional control of quality.

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Measuring and fulfilling user requirements during medical device development will result in successful products that improve patient safety, improve device effectiveness and reduce product recalls and modifications. Medical device users are an extremely heterogeneous group and for any one device the users may include patients, their carers as well as various healthcare professionals. There are a number of factors that make capturing user requirements for medical device development challenging including the ethical and research governance involved with studying users as well as the inevitable time and financial constraints. Most ergonomics research methods have been developed in response to such practical constraints and a number of these have potential for medical device development. Some are suitable for specific points in the device cycle such as contextual inquiry and ethnography, others, such as usability tests and focus groups may be used throughout development. When designing user research there are a number of factors that may affect the quality of data collected including the sample of users studied, the use of proxies instead of real end-users and the context in which the research is performed. As different methods are effective in identifying different types of data, ideally more than one method should be used at each point in development, however financial and time factors may often constrain this.

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Efforts to ‘modernize’ the clinical workforce of the English National Health Service have sought to reconfigure the responsibilities of professional groups in pursuit of more effective, joined-up service provision. Such efforts have met resistance from professions eager to protect their jurisdictions, deploying legitimacy claims familiar from the insights of the sociology of professions. Yet to date few studies of professional boundaries have grounded these insights in the specific context of policy challenges to the inter- and intra-professional division of labour, in relation the medical profession and other health-related occupations. In this paper we address this gap by considering the experience of newly instituted general practitioners (family physicians) with a special interest (GPSIs) in genetics, introduced to improve genetics knowledge and practice in primary care. Using qualitative data from four comparative case studies, we discuss how an established intra-professional division of labour within medicine—between clinical geneticists and GPs—was opened, negotiated and reclosed in these sites. We discuss the contrasting attitudes towards the nature of genetics knowledge and its application of GPSIs and geneticists, and how these were used to advance conflicting visions of what the nascent GPSI role should involve. In particular, we show how the claims to knowledge of geneticists and GPSIs interacted with wider policy pressures to produce a rather more conservative redistribution of power and responsibility across the intra-professional boundary than the rhetoric of modernization might suggest.

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MATCH (Multidisciplinary Assessment of Technology Centre for Healthcare) is a new collaboration in the UK that aims to support the healthcare sector by creating methods to assess the value of medical devices from concept through to mature product. A major aim of MATCH is to encourage the inclusion of the user throughout the product lifecycle in order to achieve devices that truly meet the requirements of their users. A review of the published literature indicates that user requirements are mainly collected during the design and evaluation stage of the product lifecycle whilst other areas, including the concept stage, have less user involvement. Complementing the literature review is an in-depth consultation with the medical device industry, which has identified a number of barriers encountered by companies when attempting to capture user requirements. These will be addressed by a number of case study projects, performed in collaboration with our industrial partners, that will examine the application and utility of different approaches to collecting and analysing data on user requirements. MATCH is focused on providing advice to device developers on how to select and apply methods that have maximum theoretical strength, practical application, cost-effectiveness and likelihood of wide sector acceptance. Feedback will be sought in order to ensure that the needs of the diverse medical device sector are met.

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Inter-subject parcellation of functional Magnetic Resonance Imaging (fMRI) data based on a standard General Linear Model (GLM) and spectral clustering was recently proposed as a means to alleviate the issues associated with spatial normalization in fMRI. However, for all its appeal, a GLM-based parcellation approach introduces its own biases, in the form of a priori knowledge about the shape of Hemodynamic Response Function (HRF) and task-related signal changes, or about the subject behaviour during the task. In this paper, we introduce a data-driven version of the spectral clustering parcellation, based on Independent Component Analysis (ICA) and Partial Least Squares (PLS) instead of the GLM. First, a number of independent components are automatically selected. Seed voxels are then obtained from the associated ICA maps and we compute the PLS latent variables between the fMRI signal of the seed voxels (which covers regional variations of the HRF) and the principal components of the signal across all voxels. Finally, we parcellate all subjects data with a spectral clustering of the PLS latent variables. We present results of the application of the proposed method on both single-subject and multi-subject fMRI datasets. Preliminary experimental results, evaluated with intra-parcel variance of GLM t-values and PLS derived t-values, indicate that this data-driven approach offers improvement in terms of parcellation accuracy over GLM based techniques.