Literature DB >> 35074290

Factors influencing door-to-triage- and triage-to-patient administration-time.

Calvin Lukas Kienbacher1, Anna Steinacher1, Verena Fuhrmann1, Harald Herkner2, Anton N Laggner1, Dominik Roth1.   

Abstract

BACKGROUND: Overcrowding decreases quality of care. Triage and patient administration are possible bottlenecks. We aimed to identify factors influencing door-to-triage- and triage-to-patient administration-time in a prospective observational study at a tertiary care center with 70,000 patients per year.
METHODS: Measurement of aforementioned times at convenience-sampled time intervals on 16 days. Linear regression modelling with times as dependent variable, and demographic, medical and structural factors as covariables, testing for interactions with risk factor "weekend".
RESULTS: We included 360 patients (183 female (51%)). Median door-to-triage-time was 6 (IQR 3-11) minutes, triage-to-patient administration-time was 5 (IQR 3-8) minutes. Overall door-to-triage-time was significantly shorter during weekends compared to weekdays (absolute difference 3 (IQR 1-7) minutes; 5 (IQR 3-8) vs. 8 (IQR 4-15) minutes, p < 0.01). Other influencing factors were closing hours of non-emergency department healthcare facilities (3.5 min more), number of ESI 2 patients seen during the interval (3 min more for each patient per hour), and ambulance activity (2 min more for each patient per hour brought by ambulance).
CONCLUSIONS: Day of time and week as well as frequency of patients with urgent conditions and those brought by ambulance significantly increased door-to-triage times. This should be kept in mind when organizing ED workflow.
Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Crowding; Emergency Department; Emergency medical service; Patient handoff; Triage

Mesh:

Year:  2022        PMID: 35074290     DOI: 10.1016/j.auec.2022.01.001

Source DB:  PubMed          Journal:  Australas Emerg Care        ISSN: 2588-994X


  1 in total

1.  Predicting Patient Length of Stay in Australian Emergency Departments Using Data Mining.

Authors:  Sai Gayatri Gurazada; Shijia Caddie Gao; Frada Burstein; Paul Buntine
Journal:  Sensors (Basel)       Date:  2022-06-30       Impact factor: 3.847

  1 in total

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