Reducing emergency department length of stay for hematology patients of tikur anbessa specialized hospital: An improvement initiative

PLoS One. 2025 Sep 8;20(9):e0329316. doi: 10.1371/journal.pone.0329316. eCollection 2025.

Abstract

Introduction: Prolonged Emergency Department (ED) stays, a global issue driving overcrowding, were exacerbated at our hospital by lab delays and extended waits, increasing patient stress. This study aimed to reduce hematology patients' length of stay (LOS). Using the fishbone method to identify care barriers, three interventions were implemented: redesigned lab referral systems, an online specialist communication platform, and patient navigation floor maps.

Methods: At Tikur Anbessa Specialized Hospital (Ethiopia), a quality improvement initiative targeted hematology patients (n = 203 baseline; n = 63 post-intervention) with prolonged emergency department (ED) stays. Using two PDSA cycles, interventions included an online consultation platform, floor markings for navigation, and digitizing peripheral smear workflows via the I-Care system. Weekly data on consultation time, lab turnaround time (TAT), navigation errors, and length of stay (LOS) were analyzed with run charts and Interrupted Time Series (ITS) regression.

Results: Median LOS decreased by 62.5% (144-54 hours; p < 0.001), remaining stable during a 5-week pause. Consultation time fell 80% (12 to 2.4 hours; 95% CI: 1.8-3.0), and lab TAT improved by 70% (78 to 23.25 hours). Navigation errors dropped from 53% to ≤7%, with minor fluctuations. Clinical outcomes (e.g., mortality) were not assessed, and long-term sustainability requires further study.

Conclusions: Targeted interventions improved care and efficiency at Tikur Anbessa Hospital, but sustained reductions in ED LOS were limited by data gaps and discontinued initiatives. Future efforts in resource-limited settings should prioritize continuous monitoring, stakeholder collaboration, and staff well-being.

MeSH terms

  • Adult
  • Emergency Service, Hospital* / statistics & numerical data
  • Female
  • Hematology
  • Hospitals, Special*
  • Humans
  • Length of Stay* / statistics & numerical data
  • Male
  • Middle Aged
  • Quality Improvement*