Emergency Department Trends and Outcomes: A Data-Driven Analysis

Area of Science:

• Healthcare Operations Research
• Public Health Analytics
• Emergency Medicine

Background:

• Hospital Emergency Departments (EDs) face persistent challenges in managing patient flow and resource allocation.
• Post-pandemic operational shifts have potentially exacerbated existing inefficiencies in healthcare delivery.

Purpose of the Study:

• To analyze trends in Emergency Department (ED) Waiting Times (WT) and Lengths of Stay (LoS) from 2016-2024.
• To investigate the impact of temporal factors and patient demographics on ED operational efficiency and outcomes.
• To explore the relationship between ED delays, patient characteristics, and mortality rates.

Main Methods:

• Retrospective analysis of hospital ED administrative data spanning 2016 to 2024.
• Temporal analysis to identify patterns in WT and LoS based on day of week and season.
• Demographic and mortality data linkage to assess patient-specific risk factors and outcomes.

Main Results:

• A significant increase in both WT and LoS was observed post-pandemic, contrasting with stable patient volumes.
• ED delays were more pronounced during weekends and winter months.
• Older patients and specific ethnic groups (NZ European/Pākehā, Māori) showed distinct patterns in ED utilization and mortality.
• An inverse correlation between WT and mortality was noted, while extended LoS correlated with increased patient severity.

Conclusions:

• Post-pandemic increases in ED Waiting Times and Lengths of Stay indicate critical operational inefficiencies.
• Temporal and demographic factors significantly influence ED performance and patient outcomes.
• Predictive analytics offers a promising avenue for optimizing ED operations and advancing health equity.