Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology.

Objective: Our objective was to apply neural network methodology to determine whether adding coded chief complaint (CCC) data to triage information would result in an improved hospital admission prediction model than one without CCC data.

Participants And Methods: We carried out a retrospective derivation and validation cohort study of all adult emergency department visits to a single center. We downloaded triage, chief complaint, and admission/discharge data on each included visit.

Perceptions of participating emergency nurses regarding an ED seasonal influenza vaccination program.

Introduction: Numerous professional organizations have recommended that emergency departments provide influenza vaccine to patients. However, no study has reported on the perceptions of participating emergency nurses regarding ED influenza vaccination programs.

Methods: We conducted an anonymous Web-based survey to assess the post-participation perceptions of emergency nurses regarding an ED influenza vaccination protocol.

Feasibility of integrating a clinical decision support tool into an existing computerized physician order entry system to increase seasonal influenza vaccination in the emergency department.

While emergency department (ED) seasonal influenza vaccination programs are feasible, reported implementation barriers include added staffing requirements to identify eligible patients and getting busy ED personnel to order and provide vaccination. We present a prospective, observational trial of integrating a clinical decision support tool into an existing ED computerized physician order entry (CPOE) system to increase ED seasonal influenza vaccination without added staffing resources, the operational barriers identified to program implementation, the revenue generated and data on opportunities for future quality improvement. Compared to the comparable pre-protocol period, ED influenza vaccination rose by 17.