Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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In September 2006, the Centers for Disease Control and Prevention released its revised recommendations for human immunodeficiency virus (HIV) testing. Prominent among these were the recommendations that emergency departments should perform routine screening for HIV infection. ⋯ It contains the lessons that were learned when such a program was initiated at an academic emergency department. Consideration of these steps will help streamline the establishment of the program, but there should be careful consideration of the program's costs and sustainability before embarking on the process.
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Multicenter Study
Lack of agreement in pediatric emergency department discharge diagnoses from clinical and administrative data sources.
Diagnosis information from existing data sources is used commonly for epidemiologic, administrative, and research purposes. The quality of such data for emergency department (ED) visits is unknown. ⋯ ED diagnoses retrieved from electronic administrative sources and manual chart review frequently disagree, even if similar diagnosis codes are grouped. Agreement varies by institution and by diagnosis. Further work is needed to improve the accuracy of diagnosis coding; development of a grouping system specific to pediatric emergency care may be beneficial.
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Comparative Study
Prospective study of the clinical features and outcomes of emergency department patients with delayed diagnosis of pulmonary embolism.
The authors hypothesized that emergency department (ED) patients with a delayed diagnosis of pulmonary embolism (PE) will have a higher frequency of altered mental status, older age, comorbidity, and worsened outcomes compared with patients who have PE diagnosed by tests ordered in the ED. ⋯ In this single-center study, the diagnosis of PE was frequently delayed and outcomes of patients with delayed diagnosis were worse than those of patients with PE diagnosed in the ED.
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In part 1 of this series, the authors describe the importance of incomplete data in clinical research, and provide a conceptual framework for handling incomplete data by describing typical mechanisms and patterns of censoring, and detailing a variety of relatively simple methods and their limitations. In part 2, the authors will explore multiple imputation (MI), a more sophisticated and valid method for handling incomplete data in clinical research. This article will provide a detailed conceptual framework for MI, comparative examples of MI versus naive methods for handling incomplete data (and how different methods may impact subsequent study results), plus a practical user's guide to implementing MI, including sample statistical software MI code and a deidentified precoded database for use with the sample code.
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Missing data are commonly encountered in clinical research. Unfortunately, they are often neglected or not properly handled during analytic procedures, and this may substantially bias the results of the study, reduce study power, and lead to invalid conclusions. ⋯ In part 1, the authors will describe relatively simple approaches to handling missing data, including complete-case analysis, available-case analysis, and several forms of single imputation, including mean imputation, regression imputation, hot and cold deck imputation, last observation carried forward, and worst case analysis. In part 2, the authors will describe in detail multiple imputation, a more sophisticated and valid method for handling missing data.