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The use of a self-check-in kiosk for early patient identification and queuing in the emergency department

  • Natalie Coyle (a1), Andrew Kennedy (a1), Michael J. Schull (a1) (a2) (a3), Alex Kiss (a2) (a3), Darren Hefferon (a1), Paul Sinclair (a1) and Zuhair Alsharafi (a1)...

Delays in triage processes in the emergency department (ED) can compromise patient safety. The aim of this study was to provide proof-of-concept that a self-check-in kiosk could decrease the time needed to identify ambulatory patients arriving in the ED. We compared the use of a novel automated self-check-in kiosk to identify patients on ED arrival to routine nurse-initiated patient identification.


We performed a prospective trail with random weekly allocation to intervention or control processes during a 10-week study period. During intervention weeks, patients used a self-check-in kiosk to self-identify on arrival. This electronically alerted triage nurses to patient arrival times and primary complaint before triage. During control weeks, kiosks were unavailable and patients were identified using routine nurse-initiated triage. The primary outcome was time-to-first-identification, defined as the interval between ED arrival and identification in the hospital system.


Median (interquartile range) time-to-first-identification was 1.4 minutes (1.0–2.08) for intervention patients and 9 minutes (5–18) for control patients. Regression analysis revealed that the adjusted time-to-first-identification was 13.6 minutes (95% confidence interval 12.8–14.5) faster for the intervention group.


A self-check-in kiosk significantly reduced the time-to-first-identification for ambulatory patients arriving in the ED.


Les délais d'attente inhérents au processus de triage des malades au service des urgences (SU) peuvent mettre en péril leur sécurité. L’étude visait donc à valider le principe selon lequel l'utilisation d'un guichet d'auto-inscription diminuerait le temps nécessaire pour signaler l'arrivée des malades ambulatoires au SU. A été comparé le processus d'utilisation d'un guichet d'auto-inscription d'un nouveau type pour signaler l'arrivée des malades au SU avec le processus habituel d'inscription des malades par le personnel infirmier.


L’étude consistait en un essai prospectif, à répartition aléatoire et hebdomadaire, d'inscription, réalisé selon le processus expérimental ou le processus témoin, sur une période de 10 semaines. Durant les semaines d'expérimentation, les malades se dirigeaient vers le guichet d'auto-inscription à leur arrivée; un signal électronique informait le personnel infirmier affecté au triage de l'heure d'arrivée des malades et des motifs de consultation avant le triage lui-même. Durant les semaines témoins, les guichets étaient fermés et les malades étaient inscrits selon le processus habituel de triage effectué par le personnel infirmier. Le principal critère d’évaluation était le temps écoulé avant le signal d'arrivée, défini comme l'intervalle entre l'arrivée des malades au SU et leur inscription dans le système de l'hôpital.


Le temps médian (écart interquartile) écoulé avant le signal d'arrivée était de 1,4 minute (1,0–2,08) durant les semaines d'expérimentation contre 9 minutes (5 –18) durant les semaines témoins. D'après les résultats de l'analyse de régression, le temps rajusté écoulé avant le signal d'arrivée était de 13,6 minutes (IC à 95% : 12,8–14,5) plus court dans le groupe d'expérimentation que dans le groupe témoin.


L'utilisation d'un guichet d'auto-inscription a permis de réduire considérablement le temps écoulé avant le signal d'arrivée des malades ambulatoires au SU.

Corresponding author
Correspondence to: Dr. Zuhair Alsharafi, Department of Emergency Services, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, C753, Toronto, ON M4N 3M5; Email:
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1.Guttman, A, Schull, MJ, Vermeulen, MJ, Stukel, TA. Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ 2011;342:d2983.
2.Rondeau, KV, Francescutti, LH, Zanardelli, JJ. Emergency department overcrowding: the impact of resource scarcity on physician job satisfaction/practitioner application. J Healthc Manag 2005;50(5):327–42.
3.Derlet, RW, Richards, JR. Overcrowding in the nation's emergency departments: complex causes and disturbing effects. Ann Emerg Med 2000;35:63–8.
4.Iverson, KV, Moskop, JC. Triage in medicine, part I: concept, history and types. Ann Emerg Med 2007;49(3):275–81.
5.Betz, M, Stempien, J, Trivedi, S, Bryce, R. A determination of emergency department pre-triage times in patient not arriving by ambulance compared to widely used guideline recommendations. CJEM 2017;19(4):265–70.
6.Wiler, JL, Gentle, C, Halfpenny, JM, et al. Optimizing emergency department front-end operations. Ann Emerg Med 2010;55(2):142–60.
7.Porter, SC, Cai, Z, Gribbons, W, et al. The asthma kiosk: a patient-centered technology for collaborative decision support in the emergency department. J Am Med Inform Assoc 2004;11(6):458–67.
8.Houry, D, Kaslow, NJ, Kemball, RS, et al. Does screening in the emergency department hurt or help victims of intimate partner violence? Ann Emerg Med 2008;51(4):433–42.e7.
9.Sinha, M, Khor, KN, Amresh, A, Drachman, D. The use of a kiosk-model bilingual self-triage system in the pediatric emergency department. Pediatr Emerg Care 2014;30(1):63–8.
10.The Canadian Triage and Acuity Scale. Combined adult/paediatric educational program. Triage training resources. Version 2.5b; 2013. Available at: (accessed August 2, 2016).
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Canadian Journal of Emergency Medicine
  • ISSN: -
  • EISSN: 1481-8035
  • URL: /core/journals/canadian-journal-of-emergency-medicine
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