{"title":"Challenges faced by the Iranian health system in response process to terrorist explosive attacks: a descriptive phenomenology qualitative study of live experiences.","authors":"Asghar Tavan, Ahmad Mashkoori, Asiye Aminafshar, Afshin Khazaei, Sahar Salahi, Hojjat Farahmandnia","doi":"10.1186/s12873-025-01338-1","DOIUrl":"10.1186/s12873-025-01338-1","url":null,"abstract":"<p><strong>Introduction: </strong>Mass casualty incidents present significant challenges not only for healthcare providers and emergency service responders at the incident scene, but also for the hospitals that receive those affected. Terrorism related mass casualty incidents can lead to a diverse array of circumstances, necessitating those hospitals and their personnel be adequately prepared to manage more complex and demanding requirements. This study aimed to explore the health system challenges related to the response process to terrorist explosive bombing attacks from the perspective of Iranian health system managers and experts.</p><p><strong>Methods: </strong>The present qualitative study employs a descriptive phenomenology approach conducted in Iran. Data were gathered through in-depth individual interviews with 16 health managers and experts, using purposive sampling. The Data analysis was conducted utilizing Colaizzi's 7-step method. To ensure the trustworthiness of the findings, the study adhered to the recommendations set forth by Lincoln and Guba.</p><p><strong>Results: </strong>After multiple rounds of analyzing and summarizing the data and taking into consideration similarities and differences, 230 initial codes, 18 sub-categories, 5 categories and 2 main themes were created based on the results of data analysis. Theme 1: Intra-organizational challenges including categories of (prehospital and hospital challenges). Theme 2: Inter-organizational challenges including categories of (chain of command, insufficient security and ineffective communication and information).</p><p><strong>Conclusion: </strong>This study explored healthcare workers and managers experiences with internal and external organizational challenges in responding to terrorist explosive bombing attacks. Findings reveal that such incidents pose unique demands distinct from other emergencies, requiring tailored preparedness strategies, especially in prehospital, hospital, and logistical sectors, despite existing general disaster plans. An effective response needs multisectoral collaboration with security forces and aid organizations. The presentation of real-world insights can inform targeted preparedness programs for high-risk, chaotic terrorist scenarios.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"175"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12403913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Performance of ChatGPT, Gemini and DeepSeek for non-critical triage support using real-world conversations in emergency department.","authors":"Sukyo Lee, Sumin Jung, Jong-Hak Park, Hanjin Cho, Sungwoo Moon, Sejoong Ahn","doi":"10.1186/s12873-025-01337-2","DOIUrl":"10.1186/s12873-025-01337-2","url":null,"abstract":"<p><strong>Background: </strong>Timely and accurate triage is crucial for the emergency department (ED) care. Recently, there has been growing interest in applying large language models (LLMs) to support triage decision-making. However, most existing studies have evaluated these models using simulated scenarios rather than real-world clinical cases. Therefore, we evaluated the performance of multiple commercial LLMs for non-critical triage support in ED using real-world clinical conversations.</p><p><strong>Methods: </strong>We retrospectively analyzed real-world triage conversations prospectively collected from three tertiary hospitals in South Korea. Multiple commercial LLMs-including OpenAI GPT-4o, GPT-4.1, O3, Google Gemini 2.0 flash, Gemini 2.5 flash, Gemini 2.5 pro, DeepSeek V3, and DeepSeek R1-were evaluated for the accuracy in triaging patient urgency based solely on unsummarized dialogue. The Korean Triage and Acuity Scale (KTAS) assigned by triage nurses was used as the gold standard for evaluating the LLM classifications. Model performance was assessed under both a zero-shot prompting condition and a few-shot prompting condition that included representative examples.</p><p><strong>Results: </strong>A total of 1,057 triage cases were included in the analysis. Among the models, Gemini 2.5 flash achieved the highest accuracy (73.8%), specificity (88.9%), and PPV (94.0%). Gemini 2.5 pro demonstrated the highest sensitivity (90.9%) and F1-score (82.4%), though with lower specificity (23.3%). GPT-4.1 also showed balanced high accuracy (70.6%) and sensitivity (81.3%) with practical response times (1.79s). Performance varied widely between models and even between different versions from the same vendor. With few-shot prompting, most models showed further improvements in accuracy and F1-score.</p><p><strong>Conclusions: </strong>LLMs can accurately triage ED patient urgency using real-world clinical conversations. Several models demonstrated both high sensitivity and acceptable response times, supporting the feasibility of LLM in non-critical triage support tools in diverse clinical environments. These findings apply to non-critical patients (KTAS 3-5), and further research should address integration with objective clinical data and real-time workflow.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"176"},"PeriodicalIF":2.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12403343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Astrid K V Harring, Magnus Hjortdahl, Kristin Häikiö, Trine M Jørgensen
{"title":"Disparities between two possible thresholds for frequent contacts to a Norwegian emergency medical communication centre: ≥5 contacts in one month vs. ≥12 contacts in three months.","authors":"Astrid K V Harring, Magnus Hjortdahl, Kristin Häikiö, Trine M Jørgensen","doi":"10.1186/s12873-025-01333-6","DOIUrl":"https://doi.org/10.1186/s12873-025-01333-6","url":null,"abstract":"","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"173"},"PeriodicalIF":2.3,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12395745/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erik J Wanberg, Greg Scott, Kristina M Dostal, Aidan F Mullan, Sarayna S McGuire
{"title":"It's time to talk to emergency medical dispatchers: survey study on performance feedback and patient outcome follow-up to EMDs.","authors":"Erik J Wanberg, Greg Scott, Kristina M Dostal, Aidan F Mullan, Sarayna S McGuire","doi":"10.1186/s12873-025-01332-7","DOIUrl":"https://doi.org/10.1186/s12873-025-01332-7","url":null,"abstract":"","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"172"},"PeriodicalIF":2.3,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12392557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reyhan İrem Mutlu Eren, Çağdaş Yıldırım, Alp Şener, Fatih Ahmet Kahraman, Mehmet Ergin, Şervan Gökhan, Osman Ersoy
{"title":"Diagnostic accuracy of ultrasound and computed tomography in obstructive jaundice at emergency department: a retrospective study.","authors":"Reyhan İrem Mutlu Eren, Çağdaş Yıldırım, Alp Şener, Fatih Ahmet Kahraman, Mehmet Ergin, Şervan Gökhan, Osman Ersoy","doi":"10.1186/s12873-025-01328-3","DOIUrl":"https://doi.org/10.1186/s12873-025-01328-3","url":null,"abstract":"","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"169"},"PeriodicalIF":2.3,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12382190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fabien Coisy, Florian Ajavon, Alberto Di Castri, Mélodie Lagarrigue, Céline Occelli, Xavier Bobbia, Romain Genre Grandpierre
{"title":"Exploration of patient blood management metrics for emergency departments: a 4-year retrospective monocenter study.","authors":"Fabien Coisy, Florian Ajavon, Alberto Di Castri, Mélodie Lagarrigue, Céline Occelli, Xavier Bobbia, Romain Genre Grandpierre","doi":"10.1186/s12873-025-01329-2","DOIUrl":"https://doi.org/10.1186/s12873-025-01329-2","url":null,"abstract":"<p><strong>Background: </strong>Red blood cell (RBC) transfusions are essential in emergency departments (ED), but their practices lack standardization, often leading to inefficiencies and risks. Patient blood management is poorly developed in ED, particularly because of the diverse and acute nature of patients.</p><p><strong>Objectives: </strong>Describe RBC transfusions in ED and develop a metric to benchmark RBC transfusion efficiency in the ED.</p><p><strong>Methods: </strong>This retrospective study analyzed red blood cells transfusions at a French University Hospital (2020-2023). The yearly adjusted number of transfusions per ED-patient (YANTED) was calculated by adjusting the number of ED visits to exclude low-acuity cases. Metrics included transfusion timing, urgency level (immediate life-threatening emergency, life-threatening emergency, relative emergency and nonemergency), and the proportion of RBC transfused in the ED compared with hospital-wide transfusions.</p><p><strong>Results: </strong>A total of 5,537 RBC units were transfused in the ED over four years, with a median YANTED of 16.3 (15.6-17.3) per 1,000 ED patients. Relative emergency transfusions accounted for 67% of all transfusions. Nighttime transfusions represented 45% of the total. The median time from RBC order to transfusion initiation was 182 min. The delivery and transfusion times for the immediate life-threatening emergency, life-threatening emergency patients were detailed, with 23% completed within the 30-minute threshold. ED accounted for 11% (95% CI: 10-12%) of total hospital transfusions.</p><p><strong>Conclusion: </strong>Over a 4-year period, the YANTED was 16.7 (15.6-17.3) RBC units per 1,000 ED patients. Relative emergency prescriptions accounted for 67% of the transfusions and occurred mostly at night. Further studies should focus on how to decrease these indicators in the ED.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"170"},"PeriodicalIF":2.3,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12382135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahdi Nabi Foodani, Amir Hossein Goudarzian, Özkan Görgülü, Kelly Jo Cone, Khosro Shakeri, Zahra Abbasi Dolatabadi
{"title":"Validation of the Persian Triage Decision-Making Inventory (TDMI): a cross-cultural adaptation study.","authors":"Mahdi Nabi Foodani, Amir Hossein Goudarzian, Özkan Görgülü, Kelly Jo Cone, Khosro Shakeri, Zahra Abbasi Dolatabadi","doi":"10.1186/s12873-025-01326-5","DOIUrl":"https://doi.org/10.1186/s12873-025-01326-5","url":null,"abstract":"","PeriodicalId":9002,"journal":{"name":"BMC Emergency Medicine","volume":"25 1","pages":"168"},"PeriodicalIF":2.3,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12382209/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}