Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
-
To determine whether patient clinical and socioeconomic characteristics predict patient delay in coming to the emergency department (ED). ⋯ A patient's decision to delay coming to the ED often reflects a belief that his or her illness is either self-limited or not serious. The decision to delay correlates with patient characteristics and access to a regular physician. The correlates of delay in seeking ED care may depend on the delay measure used. Better understanding of patients at risk for delaying care may influence interventions to reduce delay.
-
To implement a new five-level emergency department (ED) triage algorithm, the Emergency Severity Index (ESI), into nursing practice, and validate the instrument with a population-based cohort using hospitalization and ED length of stay as outcome measures. ⋯ Triage nurses at these two hospitals successfully implemented the ESI algorithm and provided useful feedback for further refinement of the instrument. Emergency Severity Index triage reproducibly stratifies patients into five groups with distinct clinical outcomes.
-
To determine interobserver agreement between triage registered nurses (RNs) and emergency physicians (EPs) regarding indication for knee radiographs by applying the Ottawa knee rule (OKR) and individual components of the rule. ⋯ The only criterion that resulted in almost perfect agreement between the RNs and EPs was patient age; agreement for the other four criteria and the overall decision to order x-rays was moderate.
-
To develop a multivariable model predicting the level of care required by pediatric patients for use as a risk-adjustment tool in the evaluation of emergency medical services for children. ⋯ A model based on easily and routinely measured variables can accurately predict the level of care rendered in the PED. The predicted probabilities from such a model correlate well with other outcomes of care and may be useful in adjusting for differences in risk when evaluating quality of care.