Journal of Emergencies, Trauma, and Shock
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ORIGINAL RESEARCH PAPER
Year : 2019  |  Volume : 12  |  Issue : 4  |  Page : 268-273

Application of queuing theory to optimize the triage process in a tertiary emergency care (“ER”) department


1 Department of Emergency, Hospital Universitario San Ignacio; Department of Internal Medicine, Emergency Medicine Program, Pontificia Universidad Javeriana, Bogotá, Colombia
2 Department of Internal Medicine, Emergency Medicine Program, Pontificia Universidad Javeriana, Bogotá, Colombia
3 Department of Internal Medicine, Hospital Universitario San Ignacio, Bogotá, Colombia
4 Department of Emergency, Hospital Universitario San Ignacio, Bogotá, Colombia
5 Department of Internal Medicine, Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Bogotá, Colombia

Correspondence Address:
Dr. Atilio Moreno-Carrillo
Department of Emergency, Hospital Universitario San Ignacio, Emergency Medicine Program, Pontificia Universidad Javeriana, Bogotá
Colombia
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/JETS.JETS_42_19

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Context: Time from triage to patient care is usually evaluated, but time elapsed between the arrival of patient to emergency room (ER) and triage (pretriage) is not usually measured. Aims: The present study evaluates how the application of the queuing (or “waiting line”) theory in the triage process can generate effective strategies to improve patient care in the ER. Settings and Design: A “before-and-after” study was conducted in the ER of the Hospital Universitario San Ignacio, a tertiary emergency care in Bogotá, Colombia. Subjects and Methods: The pretriage time was evaluated, and queuing theory was applied to the evaluation; according to the results, the number and distribution of the necessary nursing personnel were determined. Statistical Analysis Used: The change in waiting times was compared using a paired t-test. Results: In a first 7 months evaluation period, 89,898 patient visits were considered, with an average pretriage time of 22.15 min. According to the arrival distribution by hours and days of the week and considering the results of the calculations made using queuing theory, the number of nurses needed in the service per hour was determined for each day of the week, and schedule changes were implemented without increasing staff. In a second similar evaluation period, 94,497 patient visits were considered demonstrating a reduction of the pretriage time to 7.5 min (mean difference 14.64 min, 95% confidence interval 14.42–14.85, P < 0.001). Conclusions: The use of queuing theory in the planning of the daily personnel requirements in the triage area of ER can reduce the pretriage time by 65% without incurring additional cost.


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