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지역 119구급자원이 119구급대 반응시간 충족 여부에 미치는 영향에 관한 다수준 분석A multilevel analysis of the impact of regional 119 emergency resources on the compliance with 119 ambulance response time

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A multilevel analysis of the impact of regional 119 emergency resources on the compliance with 119 ambulance response time
Authors
권혜지신영전
Issue Date
Apr-2025
Publisher
사단법인 한국응급구조학회
Keywords
119 emergency services; 119 emergency resources; 119 ambulance response time; multilevel logistic regression
Citation
한국응급구조학회지, v.29, no.1, pp 201 - 213
Pages
13
Indexed
KCI
Journal Title
한국응급구조학회지
Volume
29
Number
1
Start Page
201
End Page
213
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/208173
DOI
10.14408/KJEMS.2025.29.1.201
ISSN
1738-1606
2384-2091
Abstract
Purpose: To determine the impact of regional 119 emergency resources on the compliance with 119 ambulance response times. Methods: We used 432,777 emergency activity reports from 2022, and local data from 85 areas via the National Statistics Portal. The 119 ambulance response times were categorized as RTt, RT1, RT2, and RT3 and classified as meeting or not meeting the national median based on the 2023 emergency service quality control report. Frequency analysis, descriptive statistics, and multilevel logistic regression(only RT1-4 and RT1-9) were conducted to identify the factors influencing response time compliance. All statistical analyses were performed using SAS version 9.4. Results: The median time was 34 min for RTt(range:2-712 min) and 9 min for RT1(range:1-688 min). RT2-2 had the highest fulfillment rate(79.8%), and RT1-4 had the lowest(1.7%). Multilevel analysis showed higher fulfillment rates among younger patients, out-of-hospital cardiac arrest cases, shorter scene distances, regions with greater population density, older persons populations, lower single-person household ratios, and more ambulances per 100,000 people. Conclusion: Optimizing 119 ambulance response times requires enhanced paramedic resource allocation, considering both individual-level factors (patient characteristics) and community-level determinants (population density and demographics), necessitating adjusted paramedic-to-population ratios.
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서울 의과대학 (DEPARTMENT OF PREVENTIVE MEDICINE)
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