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Updated: May 9, 2025

A Novel Approach for the Administration of Medications and Fluids in Emergency Scenarios and Settings
Published on: November 9, 2016
Factors associated with delayed order-to-administration time in the emergency department: a retrospective analysis
Yen-Wen Chen1, Jian-Heng Lee1, Cheng-Ying Chiang1
1Department of Emergency Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, No. 539, Zhongxiao Road, East District, Chiayi City, 600, Taiwan.
Background:
Timely medication administration in the emergency department (ED) is critical for improving patient outcomes. This study aimed to identify predictors of delayed order-to-administration (OTA) time, defined as exceeding 30 min for stat medications.
Methods:
A retrospective analysis was conducted in the ED of a 1,000-bed tertiary hospital. Patients aged 20 years or older who received stat medications between June 1 and August 31, 2020, were included. Only the first stat medication order per patient was analyzed. Data on patient demographics, triage characteristics, environmental factors, prescription details, and OTA times were extracted from the hospital's electronic medical record and nursing information system. Multivariable logistic regression with backward elimination was used to identify predictors of OTA delays.
Results:
Among the 11,429 patient visits included, 9.9% experienced OTA delays exceeding 30 min. Predictors of higher odds of delay included older age (adjusted odds ratio [aOR]: 1.01, 95% CI: 1.00-1.01), female sex (aOR: 1.49, 95% CI: 1.31-1.69), limited mobility (aOR: 1.38, 95% CI: 1.17-1.63 for ambulatory with assistance; aOR: 1.24, 95% CI: 1.03-1.48 for non-ambulatory patients), trauma (aOR: 1.35, 95% CI:1.09-1.66), hourly patient visits (aOR: 1.07, 95% CI: 1.05-1.10), concurrent intravenous fluid use (aOR:1.42, 95% CI:1.04-1.93), blood tests (aOR: 1.73, 95% CI: 1.30-2.30), radiography (aOR: 2.22, 95% CI: 1.87-2.64), and computed tomography (aOR: 1.57, 95% CI: 1.37-1.80). Reduced odds of delay were observed among patients with triage level 1 compared to level 3 (aOR 0.25, 95% CI:0.16-0.39), those arriving during night shifts compared to day shifts (aOR: 0.33, 95% CI: 0.18-0.63), and those receiving intramuscular medications compared to intravenous administration (aOR 0.71; 95% CI, 0.55-0.93).
Conclusions:
Several patient, environmental, and diagnostic-related factors were associated with OTA delays in stat medication administration. Understanding these predictors may help inform strategies to optimize ED workflows. Further research is warranted to validate these findings in other ED settings.
Clinical Trial Number:
Not applicable.
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