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Obstacles and Challenges Affecting Quality Indicators in a Complex Tertiary Emergency Center
Mohammad J Jaber1, Alanoud A Bindahmsh1, Mohammad A Abu Dawwas1
1Department of Nursing, Emergency Administration, King Fahad Medical City, Riyadh Second Health Cluster, Riyadh, Saudi Arabia.
Introduction:
Hospital performance is significantly affected by external factors (political and economic) rather than internal factors (effectiveness and efficiency). Emergency department (ED) overcrowding is a significant issue for emergency care services globally, characterized by a rising number of visits and persistent unsolved issues, resulting in increased challenges faced by ED staff and decreased patient satisfaction. This study aimed to explore the obstacles and challenges that cause variation in ED quality indicators (QIs) based on five domains: infrastructure, population, workflow, workforce, and administration.
Methods:
A tertiary emergency center in Saudi Arabia administered a questionnaire with standardized measures to 180 nurses, using a cross-sectional descriptive design.
Results:
Most nurses (75.5%) believed that crowded waiting rooms in the ED were the most influential factor affecting QIs. Many other challenges were identified, including bed capacity, triage area/workflow, increased volume during peak periods, demand for nonemergency visits, staff and shortages. Significant differences in nurses' responses were found on the basis of education level (for infrastructure only, p = 0.004), specialty (for nursing administration only, p = 0.052), and ED experience (for all variables, p = 0.008-0.039).
Conclusion:
The analysis uncovered various critical aspects of infrastructure, workflow, population, workforce, and nursing administration that have a major effect on patient flow in the ED. Comprehending these aspects will greatly affect the quality measures of ED performance and assist policymakers in formulating strategic plans to enhance ED performance. Therefore, successful implementation and optimization of ED resources depend greatly on considering the right decision variables and resource restrictions.
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