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Background: Understanding the characteristics of patients and temporal patterns of emergency department visits is crucial for improving service management and optimizing resource allocation. Objectives: This study aimed to characterize the demograph…
Background: Understanding the characteristics of patients and temporal patterns of emergency department visits is crucial for improving service management and optimizing resource allocation. Objectives: This study aimed to characterize the demographic and clinical profiles of patients and determine the reasons and temporal patterns of visits to the emergency department of Al-Hakeem Hospital in Najaf, Iraq, in 2025.
Methods: This cross-sectional study was conducted on patients visiting the emergency department during a consecutive three-month period in the spring of 2025. Data on demographics, clinical profiles, visit patterns, diagnoses, and treatment were collected using a structured form. Data were analyzed using SPSS version 23, along with descriptive statistics, Chi-square test, Fisher’s exact test, and Kruskal-Wallis test.
Results: The mean patient age was 33.75 years. The majority were uninsured, married, urban-residing males, arriving most frequently at night via private transport. Common presentations included abdominal pain/fever/vomiting (25.5%) and trauma (13.9%), with food poisoning being the predominant diagnosis. Most patients were triaged as semi-urgent (67.1%) and had no comorbidities. Average consultation time and ED length of stay were 25.17 minutes and 3.3 hours, respectively. The majority recovered. Visit time (morning, afternoon, night, midnight) showed significant associations with multiple variables such as residence, marital status, occupation, insurance status, triage level, chief complaints, diagnosis, disease severity, physical activity, and performed tests (P < 0.05).
Conclusion: Temporal patterns and individual characteristics have a significant influence on ED visits. These findings can help optimize staffing during peak hours, target training for common conditions, and improve resource planning for uninsured patients.
