In this study, a modular discrete event simulation (computer modeling) has been presented to support process improvements in a hospital's emergency department (ED) to streamline admitted patient flow to inpatient units. Because the ED in this study has less than 10 beds, unnecessary occupation of beds affects the patient wait time dramatically. Additionally, ED overcrowding diminishes the quality of care, increases costs, and decreases employee and patient satisfaction. The modular simulation model evaluated the effectiveness of several recommended workflow improvements, resulting from comprehensive statistical analysis, based on their impact on cycle time and time traps in the process. The results suggested that, to ensure better efficiency and optimal cycle time, all of the suggested workflow improvements should be implemented simultaneously. The model also suggested that achieving customer satisfaction is possible 96.26% of the time with the current resource allocations in the ED.

Background: The United States Agency for Healthcare Research and Quality endorses the importance of a clinician's accurate diagnosis of skin and soft tissue infection as a way to improve patient safety especially with the nation wide emergence of community-acquired methicillin resistant Staphylococcus aureus. A reliable and accurate bedside ultrasound imaging classification approach to skin and soft tissue infection may assist the emergency department (ED) triage nurse in safely identifying those patients with skin and soft tissue infection in both light-skinned and darkskinned patients and help the ED triage nurse stratify those patients who need medical versus surgical therapy. Study Objectives: To assess the reliability of ED triage nurse-performed bedside ultrasound imaging (inter-rater reliability testing) for the detection and classification of skin and soft tissue infections into surgical vs non-surgical levels of skin and soft tissue infection in patients with light skin and dark skin (Fitzpatrick Skin Color Classification stratification). Methods: Prospective, blinded, convenience sample, in urban teaching hospital ED. Adult volume approximately 120,000 patients/year. All enrolled patients received bedside ultrasound by an ED triage nurse who underwent point-of-care ultrasonography training and criterion standard image review (experienced RDMS, RMSK ED attending physician) assessed for possible skin and soft tissue infection. Groups were compared via a two-rater linear weighted kappa statistic. A total sample size of 160 patients was determined to attain a desired kappa of > 0.6 in each group. Results: ED triage nurse pre-ultrasound versus post-ultrasound assessment of patients changed clinical management in 19/163 ¼11.7% cases. Conclusion: ED triage nurses can reliably use bedside utrasound imaging to evaluate for skin and soft tissue infection. Substantial inter-rater agreement for light skinned and dark-skinned patients was revealed. Substantial inter-rater agreement was found overall. ED triage nurse-performed bedside point of care ultrasonography can reliably assist the emergency physician to initiate medical vs. surgical therapy for patients with skin and soft tissue infections. Table. Reliability of ED Nurse Ultrasound for Detecting Skin-ST Infection in Light & Dark Skin Patients.