Evaluation & the health professions
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Disparities exist between rural and urban emergency departments with respect to knowledge resources such as online journals and clinical specialists. As knowledge is a critical element in the delivery of quality care, a web-based learning project was proposed to address the knowledge needs of emergency clinicians. One objective of this project was to evaluate the effectiveness of the online environment for knowledge exchange among rural and urban emergency clinicians. ⋯ Postings were used to establish a clinical presence (87/202), seek clinical information (52/202), and share clinical information (63/202). Postintervention survey results indicate that this modality introduced participants to new clinical experts and resources. The results provide direction for design of a virtual community of practice, which may reduce current knowledge resource disparities.
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A cross-sectional survey was carried out on a random sample of Italian physicians through a self-administered questionnaire to describe knowledge, attitudes, and professional behavior toward economic evaluations of health interventions. A response rate of 74.1% was achieved (760 questionnaires). ⋯ Multiple logistic regression analysis showed that adequate knowledge and positive attitudes are associated with increased physicians' use of health economic evaluations, as well as time dedicated to continuing medical education and previous training experience about health economics and management. Education and specific training may play an important role in promoting a more cost-conscious behavior of physicians.
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Many applied researchers analyzing longitudinal data share a common misconception: that specialized statistical software is necessary to fit hierarchical linear models (also known as linear mixed models [LMMs], or multilevel models) to longitudinal data sets. Although several specialized statistical software programs of high quality are available that allow researchers to fit these models to longitudinal data sets (e.g., HLM), rapid advances in general purpose statistical software packages have recently enabled analysts to fit these same models when using preferred packages that also enable other more common analyses. One of these general purpose statistical packages is SPSS, which includes a very flexible and powerful procedure for fitting LMMs to longitudinal data sets with continuous outcomes. This article aims to present readers with a practical discussion of how to analyze longitudinal data using the LMMs procedure in the SPSS statistical software package.