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This paper is in the following e-collection/theme issue:

Clinical Informatics (2436) Clinical Information and Decision Making (3965) Adoption and Change Management of eHealth Systems (1175) Organizational Issues (277) Design of Processes and Workflows (313) Electronic Health Records (1813) Clinical Communication, Electronic Consultation and Telehealth (972)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45593, first published .
Infographic: Effects of Triage Time Targets in the Emergency Department, showing study results.

The Effects of Displaying the Time Targets of the Manchester Triage System to Emergency Department Personnel: Prospective Crossover Study

The Effects of Displaying the Time Targets of the Manchester Triage System to Emergency Department Personnel: Prospective Crossover Study

Authors of this article:

Jonas Bienzeisler1 Author Orcid Image ;   Guido Becker2 Author Orcid Image ;   Bernadett Erdmann3 Author Orcid Image ;   Alexander Kombeiz1 Author Orcid Image ;   Raphael W Majeed1, 4 Author Orcid Image ;   Rainer Röhrig1 Author Orcid Image ;   Felix Greiner5, 6 Author Orcid Image ;   Ronny Otto6 Author Orcid Image ;   Fabian Otto-Sobotka7 Author Orcid Image ;   AKTIN Research Group AKTIN Research Group8
Article Authors Cited by (3) Tweetations (18) Metrics

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  1. Andika I, Safaruddin , Christina T, Baso Y, Utami S, Tayeb B, Bin Mohd Aboobaider B, Budi Prasetio A, Asmaningrum N, Wantonoro , Gusman T, Muntiari N. Effectiveness of the manchester triage system in the emergency department: A literature review. BIO Web of Conferences 2025;152:01004 View
  2. Selva‐Medrano D, Laredo‐Aguilera J, Serrano‐Fernández V, Carmona‐Torres J, López‐González Á, Pérez‐Rodríguez I, Guerrero‐Agenjo C, Fernández‐Sánchez J, Mota‐Cátedra G, Rabanales‐Sotos J. Evaluation of Nurse‐Led Triage in the Emergency Department: A Retrospective Observational Study. Journal of Clinical Nursing 2026;35(8):3441 View
  3. Chabab N, Gabli M. A hybrid approach of machine learning, deep learning and metaheuristics for patient prioritization in emergency department. Neural Computing and Applications 2026;38(21) View