Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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The objective was to describe patterns of rapid influenza test ordering, diagnosis of influenza, and antiviral prescribing by the treating physician for children and adults presenting to emergency departments (EDs) with fever and acute respiratory symptoms in Winston-Salem, North Carolina, over two influenza seasons. ⋯ In 2009/2010 compared to 2010/2011, the odds of rapid influenza test ordering were lower, whereas the odds of influenza-specific discharge diagnoses and antiviral prescriptions were higher among patients presenting to the ED with culture/PCR-confirmed influenza. These results demonstrated a gap between clinical practice and recommendations for the diagnosis and treatment of influenza from the Centers for Disease Control and Prevention (CDC).
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Early death after emergency department (ED) discharge may signal opportunities to improve care. Prior studies are limited by incomplete mortality ascertainment and lack of clinically important information in administrative data. The goal in this hypothesis-generating study was to identify patient and process of care themes that may provide possible explanations for early postdischarge mortality. ⋯ In this hypothesis-generating study, qualitative research techniques were used to identify clinical and process-of-care factors in patients who died within days after discharge from an ED. These potential predictors will be formally tested in a future quantitative study.
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This study aimed to develop different models to forecast the daily number of patients seeking emergency department (ED) care in a general hospital according to calendar variables and ambient temperature readings and to compare the models in terms of forecasting accuracy. ⋯ This study indicates that time-series models can be developed to provide forecasts of daily ED patient visits, and forecasting ability was dependent on the type of model employed and the length of the time horizon being predicted. In this setting, GLM and GEE models showed better accuracy than SARIMA models. Including information about ambient temperature in the models did not improve forecasting accuracy. Forecasting models based on calendar variables alone did in general detect patterns of daily variability in ED volume and thus could be used for developing an automated system for better planning of personnel resources.