INTRODUCTION: In The Netherlands there is no consensus about criteria for cancelling helicopter emergency medical services (HEMS) dispatches. This study assessed the ability of the primary HEMS dispatch criteria to identify major trauma patients. The predictive power of other early prehospital parameters was evaluated to design a safe triage model for HEMS dispatch cancellations. METHODS: All trauma-related dispatches of HEMS during a period of 6 months were included. Data concerning prehospital information and inhospital treatment were collected. Patients were divided into two groups (major and minor trauma) according to the following criteria: injury severity score 16 or greater, emergency intervention, intensive care unit admission, or inhospital death. Logistic regression analysis was used to design a prediction model for the early identification of major trauma patients. RESULTS: In total, 420 trauma-related dispatches were evaluated, of which 155 concerned major trauma patients. HEMS was more often cancelled for minor trauma patients than for major trauma patients (57.7% vs 20.6%). Overall, HEMS dispatch criteria had a sensitivity of 87.7% and a specificity of 45.3% for identifying major trauma patients. Significant differences were found for vital sign abnormalities, anatomical components and several parameters of the mechanism of injury. A triage model designed for cancelling HEMS correctly identified major trauma patients (sensitivity 99.4%). CONCLUSION: The accuracy of the current HEMS dispatch criteria is relatively low, resulting in high cancellation rates and low predictability for major trauma. The new HEMS cancellation triage model identified all major trauma patients with an acceptable overtriage and will probably reduce unjustified HEMS dispatches.
INTRODUCTION: In The Netherlands there is no consensus about criteria for cancelling helicopter emergency medical services (HEMS) dispatches. This study assessed the ability of the primary HEMS dispatch criteria to identify major traumapatients. The predictive power of other early prehospital parameters was evaluated to design a safe triage model for HEMS dispatch cancellations. METHODS: All trauma-related dispatches of HEMS during a period of 6 months were included. Data concerning prehospital information and inhospital treatment were collected. Patients were divided into two groups (major and minor trauma) according to the following criteria: injury severity score 16 or greater, emergency intervention, intensive care unit admission, or inhospital death. Logistic regression analysis was used to design a prediction model for the early identification of major traumapatients. RESULTS: In total, 420 trauma-related dispatches were evaluated, of which 155 concerned major traumapatients. HEMS was more often cancelled for minor traumapatients than for major traumapatients (57.7% vs 20.6%). Overall, HEMS dispatch criteria had a sensitivity of 87.7% and a specificity of 45.3% for identifying major traumapatients. Significant differences were found for vital sign abnormalities, anatomical components and several parameters of the mechanism of injury. A triage model designed for cancelling HEMS correctly identified major traumapatients (sensitivity 99.4%). CONCLUSION: The accuracy of the current HEMS dispatch criteria is relatively low, resulting in high cancellation rates and low predictability for major trauma. The new HEMS cancellation triage model identified all major traumapatients with an acceptable overtriage and will probably reduce unjustified HEMS dispatches.
Authors: Kuan-Chen Chin; Yu-Chia Cheng; Wen-Chu Chiang; Albert Y Chen; Jen-Tang Sun; Chih-Yen Ou; Chun-Hua Hu; Ming-Chi Tsai; Matthew Huei-Ming Ma Journal: J Med Internet Res Date: 2022-06-10 Impact factor: 7.076
Authors: Annelieke Maria Karien Harmsen; Leo Maria George Geeraedts; Georgios Fredericus Giannakopoulos; Maartje Terra; Herman Martinus Timotheus Christiaans; Lidwine Brigitta Mokkink; Frank Willem Bloemers Journal: Scand J Trauma Resusc Emerg Med Date: 2015-02-08 Impact factor: 2.953
Authors: Annelieke Maria Karien Harmsen; Leo Maria George Geeraedts; Georgios Fredericus Giannakopoulos; Maartje Terra; Herman M T Christiaans; Lidwine Brigitta Mokkink; Frank Willem Bloemers Journal: Scand J Trauma Resusc Emerg Med Date: 2017-07-11 Impact factor: 2.953
Authors: E Ter Avest; E Lambert; R de Coverly; H Tucker; J Griggs; M H Wilson; A Ghorbangholi; J Williams; R M Lyon Journal: Scand J Trauma Resusc Emerg Med Date: 2019-05-08 Impact factor: 2.953
Authors: Dag Ståle Nystøyl; Jo Røislien; Øyvind Østerås; Steinar Hunskaar; Hans Johan Breidablik; Erik Zakariassen Journal: BMC Emerg Med Date: 2020-11-02
Authors: Robert Larribau; Victor Nathan Chappuis; Philippe Cottet; Simon Regard; Hélène Deham; Florent Guiche; François Pierre Sarasin; Marc Niquille Journal: Int J Environ Res Public Health Date: 2020-11-09 Impact factor: 3.390
Authors: Scott Munro; Mark Joy; Richard de Coverly; Mark Salmon; Julia Williams; Richard M Lyon Journal: Scand J Trauma Resusc Emerg Med Date: 2018-09-25 Impact factor: 2.953