Examining Emergency Medical Services: Delay Time, Response Time, On-Scene Time In Six Peaks of the COVID-19 Pandemic in Eastern Iran

J Emerg Med. 2024 Nov;67(5):e475-e485. doi: 10.1016/j.jemermed.2024.07.008. Epub 2024 Aug 10.

Abstract

Background: Time indices are key elements in prehospital medical emergencies. The number of calls to Emergency Medical Services (EMS) and the number of missions they have undertaken have been impacted by the COVID-19 epidemic.

Objectives: This study's goal was to evaluate prehospital EMS time indices at the apex of the COVID-19 outbreak.

Methods: Data were extracted retrospectively from the Asayar Automation System, which records details on all emergency medical calls resulting in patient transport. The study period was from March 2018 to March 2021, covering the pre-COVID period and the first through sixth peaks of the pandemic in Iran. Standardized data extraction procedures were used to minimize bias in this retrospective review.

Results: In this study, most transport missions occurred during the fifth peak (n = 2811). In addition, the most missions were related to the age group above 60 years (31.1%), and the highest rate of patient transport (65.9%) was observed in male patients. Traumatic events, cardiac emergencies, impaired consciousness, and psychiatric disorders were, respectively, the main causes of patient transport. Moreover, a significant difference was observed between time indices of various COVID-19 peaks (p < 0.001).

Conclusions: Even though the structure of Iran's emergency system is based on the American-Anglo model, and rapid patient transfers to medical facilities are prioritized, the COVID-19 epidemic resulted in increased calls and missions and affected time indices. Therefore, it is suggested that the method and type of service provision be modified during similar crises.

Keywords: COVID-19; peaks of pandemic; prehospital EMS; time indices.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • COVID-19* / epidemiology
  • Emergency Medical Services* / statistics & numerical data
  • Female
  • Humans
  • Iran / epidemiology
  • Male
  • Middle Aged
  • Pandemics
  • Retrospective Studies
  • SARS-CoV-2
  • Time Factors
  • Time-to-Treatment / statistics & numerical data
  • Transportation of Patients / methods
  • Transportation of Patients / statistics & numerical data