997 resultados para Haslemere Educational Museum


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Blood culture contamination (BCC) has been associated with unnecessary antibiotic use, additional laboratory tests and increased length of hospital stay thus incurring significant extra hospital costs. We set out to assess the impact of a staff educational intervention programme on decreasing intensive care unit (ICU) BCC rates to <3% (American Society for Microbiology standard). BCC rates during the pre-intervention period (January 2006-May 2011) were compared with the intervention period (June 2011-December 2012) using run chart and regression analysis. Monthly ICU BCC rates during the intervention period were reduced to a mean of 3·7%, compared to 9·5% during the baseline period (P < 0·001) with an estimated potential annual cost savings of about £250 100. The approach used was simple in design, flexible in delivery and efficient in outcomes, and may encourage its translation into clinical practice in different healthcare settings.

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Tactility Factory Story and Panels on display as part of Showcase of Northern Irish Innovation, Pump House. Organized by Innovation Centre, NI Science Park, Belfast. Showcasing 14 of NI most innovative companies. (Jan 2013-ongoing) presented to HRH Prince Andrew (Jan 2013)

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Clinical clerks learn more than they are taught and not all they learn can be measured. As a result, curriculum leaders evaluate clinical educational environments. The quantitative Dundee Ready Environment Measure (DREEM) is a de facto standard for that purpose. Its 50 items and 5 subscales were developed by consensus. Reasoning that an instrument would perform best if it were underpinned by a clearly conceptualized link between environment and learning as well as psychometric evidence, we developed the mixed methods Manchester Clinical Placement Index (MCPI), eliminated redundant items, and published validity evidence for its 8 item and 2 subscale structure. Here, we set out to compare MCPI with DREEM. 104 students on full-time clinical placements completed both measures three times during a single academic year. There was good agreement and at least as good discrimination between placements with the smaller MCPI. Total MCPI scores and the mean score of its 5-item learning environment subscale allowed ten raters to distinguish between the quality of educational environments. Twenty raters were needed for the 3-item MCPI training subscale and the DREEM scale and its subscales. MCPI compares favourably with DREEM in that one-sixth the number of items perform at least as well psychometrically, it provides formative free text data, and it is founded on the widely shared assumption that communities of practice make good learning environments.

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Purpose
The Strengths and Difficulties Questionnaire (SDQ) is a behavioural screening tool for children. The SDQ is increasingly used as the primary outcome measure in population health interventions involving children, but it is not preference based; therefore, its role in allocative economic evaluation is limited. The Child Health Utility 9D (CHU9D) is a generic preference-based health-related quality of-life measure. This study investigates the applicability of the SDQ outcome measure for use in economic evaluations and examines its relationship with the CHU9D by testing previously published mapping algorithms. The aim of the paper is to explore the feasibility of using the SDQ within economic evaluations of school-based population health interventions.
Methods
Data were available from children participating in a cluster randomised controlled trial of the school-based roots of empathy programme in Northern Ireland. Utility was calculated using the original and alternative CHU9D tariffs along with two SDQ mapping algorithms. t tests were performed for pairwise differences in utility values from the preference-based tariffs and mapping algorithms.
Results
Mean (standard deviation) SDQ total difficulties and prosocial scores were 12 (3.2) and 8.3 (2.1). Utility values obtained from the original tariff, alternative tariff, and mapping algorithms using five and three SDQ subscales were 0.84 (0.11), 0.80 (0.13), 0.84 (0.05), and 0.83 (0.04), respectively. Each method for calculating utility produced statistically significantly different values except the original tariff and five SDQ subscale algorithm.
Conclusion
Initial evidence suggests the SDQ and CHU9D are related in some of their measurement properties. The mapping algorithm using five SDQ subscales was found to be optimal in predicting mean child health utility. Future research valuing changes in the SDQ scores would contribute to this research.