Search Articles

View query in Help articles search

Search Results (1 to 10 of 76 Results)

Download search results: CSV END BibTex RIS


Impact of a Symptom Checker App on Patient-Physician Interaction Among Self-Referred Walk-In Patients in the Emergency Department: Multicenter, Parallel-Group, Randomized, Controlled Trial

Impact of a Symptom Checker App on Patient-Physician Interaction Among Self-Referred Walk-In Patients in the Emergency Department: Multicenter, Parallel-Group, Randomized, Controlled Trial

Key inclusion criteria were self-referred walk-in patients aged 18 years or older with sufficient German or English language proficiency, the ability to provide informed consent, and a treatment urgency rating of yellow, green, or blue according to the Manchester Triage System (ie, MTS 3-5, respectively) as assigned by the triage nurse.

Malte L Schmieding, Marvin Kopka, Myrto Bolanaki, Hendrik Napierala, Maria B Altendorf, Doreen Kuschick, Sophie K Piper, Lennart Scatturin, Konrad Schmidt, Claudia Schorr, Alica Thissen, Cornelia Wäscher, Christoph Heintze, Martin Möckel, Felix Balzer, Anna Slagman

J Med Internet Res 2025;27:e64028

Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review

Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review

In addition, AI systems hold great promise to make patient flows more efficient at the admission of patients by improving triage [4,5]. Traditionally, triage involves a health care professional taking the patient’s medical history to systematically decide the optimal prioritization and assess the appropriate treatment for the patient.

Elin Siira, Hanna Johansson, Jens Nygren

J Med Internet Res 2025;27:e53741

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study

A triage system is a standardized system for rapid patient decision-making used in emergency departments (EDs) worldwide. Most systems classify patients into different emergency levels based on symptoms and clinical signs [1]. Triage systems are frequently established on the basis of expert opinion and may not consistently undergo validation [2]. Preventing triage misclassification is the main objective of triage.

Sage Wyatt, Dagfinn Lunde Markussen, Mounir Haizoune, Anders Strand Vestbø, Yeneabeba Tilahun Sima, Maria Ilene Sandboe, Marcus Landschulze, Hauke Bartsch, Christopher Martin Sauer

J Med Internet Res 2024;26:e56382

The Triage and Diagnostic Accuracy of Frontier Large Language Models: Updated Comparison to Physician Performance

The Triage and Diagnostic Accuracy of Frontier Large Language Models: Updated Comparison to Physician Performance

The triage (level/urgency of care to seek) and diagnostic accuracy of the GPT-3 model were recently compared with 5000 lay individuals using the internet and 21 practicing primary care physicians [4]. The triage ability of GPT-3 was significantly inferior to that of physicians, having similar accuracy to lay individuals. The diagnostic ability was close to but below that of physicians [4]. It is uncertain whether more recent frontier LLMs are still inferior to physicians on this benchmark.

Michael Joseph Sorich, Arduino Aleksander Mangoni, Stephen Bacchi, Bradley Douglas Menz, Ashley Mark Hopkins

J Med Internet Res 2024;26:e67409

Evaluation of an App-Based Mobile Triage System for Mass Casualty Incidents: Within-Subjects Experimental Study

Evaluation of an App-Based Mobile Triage System for Mass Casualty Incidents: Within-Subjects Experimental Study

The triage app is developed using Google’s Flutter framework [18], which supports multiple platforms from a single codebase—an essential feature for training and future use by different organizations. The app’s user interface is designed for ease of use during triage, transitioning from flowchart-based designs to a page flow that represents the triage algorithms.

Martin Schmollinger, Jessica Gerstner, Eric Stricker, Alexander Muench, Benjamin Breckwoldt, Manuel Sigle, Peter Rosenberger, Robert Wunderlich

J Med Internet Res 2024;26:e65728

The Added Value of Using Video in Out-of-Hours Primary Care Telephone Triage Among General Practitioners: Cross-Sectional Survey Study

The Added Value of Using Video in Out-of-Hours Primary Care Telephone Triage Among General Practitioners: Cross-Sectional Survey Study

They cannot show up physically at the OOH-PC service without a prior telephone triage call. Triage GPs perform telephone triage with the use of video (video contact) or without the use of video (telephone contact), but without a clinical decision support tool. When answering a telephone triage contact, the triage GP gathers information about the reason for the encounter. Based on this information and their clinical experience, the triage GP decides if the telephone triage contact is suitable for video use.

Mette Amalie Nebsbjerg, Katrine Bjørnshave Bomholt, Claus Høstrup Vestergaard, Morten Bondo Christensen, Linda Huibers

JMIR Hum Factors 2024;11:e52301

Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study

Accuracy of a Commercial Large Language Model (ChatGPT) to Perform Disaster Triage of Simulated Patients Using the Simple Triage and Rapid Treatment (START) Protocol: Gage Repeatability and Reproducibility Study

Among the many possible uses for Chat GPT in medicine, patient triage is an interesting case study. AI-guided triage could be particularly useful in disaster medicine, where circumstances may require inexperienced health care providers to perform triage. One can imagine triage performed by AI where the provider enters patient information as text, and the patient’s triage code is outputted. This might allow physicians, first responders, nurses, or even the patients themselves to perform triage.

Jeffrey Micheal Franc, Attila Julius Hertelendy, Lenard Cheng, Ryan Hata, Manuela Verde

J Med Internet Res 2024;26:e55648

Triage Accuracy and the Safety of User-Initiated Symptom Assessment With an Electronic Symptom Checker in a Real-Life Setting: Instrument Validation Study

Triage Accuracy and the Safety of User-Initiated Symptom Assessment With an Electronic Symptom Checker in a Real-Life Setting: Instrument Validation Study

This is medical triage, and it involves directing patients to the most suitable location within an appropriate time frame. In clinical practice, triage assessment and guidance are usually done by health care professionals either over the phone or face to face, for example, at a health care center [14]. Triage takes up a lot of professionals’ time and its quality varies.

Ville Liu, Minna Kaila, Tuomas Koskela

JMIR Hum Factors 2024;11:e55099

The Use of Online Consultation Systems or Remote Consulting in England Characterized Through the Primary Care Health Records of 53 Million People in the OpenSAFELY Platform: Retrospective Cohort Study

The Use of Online Consultation Systems or Remote Consulting in England Characterized Through the Primary Care Health Records of 53 Million People in the OpenSAFELY Platform: Retrospective Cohort Study

An important enabler of this model is the use of OC systems for improving access and supporting care navigation and triage in general practice. OC system An OC system is an online facility that allows a patient or carer to seek advice or information related to the patient’s health or to make a clinical or administrative request through completing an electronic form.

Martina Fonseca, Brian MacKenna, Amir Mehrkar, The OpenSAFELY Collaborative, Caroline E Walters, George Hickman, Jonathan Pearson, Louis Fisher, Peter Inglesby, Seb Bacon, Simon Davy, William Hulme, Ben Goldacre, Ofra Koffman, Minal Bakhai

JMIR Public Health Surveill 2024;10:e46485

Improving Triage Accuracy in Prehospital Emergency Telemedicine: Scoping Review of Machine Learning–Enhanced Approaches

Improving Triage Accuracy in Prehospital Emergency Telemedicine: Scoping Review of Machine Learning–Enhanced Approaches

While there have been literature reviews outlining ML methods in emergency settings [14-16], no specific review touches on prehospital telemedicine triage services. Related reviews such as Sánchez-Salmerón et al [15] focused on in-person triage, as opposed to prehospital and remote triage.

Daniel Raff, Kurtis Stewart, Michelle Christie Yang, Jessie Shang, Sonya Cressman, Roger Tam, Jessica Wong, Martin C Tammemägi, Kendall Ho

Interact J Med Res 2024;13:e56729