The Korean Journal of Emergency Medical Services (한국응급구조학회지)

The Korea Society of Emergency Medical Services (한국응급구조학회)
권호 표지
DOI QR코드

DOI QR Code

Analysis of patients transported in ambulances by season and daily temperatures

계절 및 기온에 따른 119 구급대 환자 이송 건수 및 병력의 차이

  • 이경열 (국립공주대학교 응급구조학과) ;
  • 이정혁 (국립공주대학교 응급구조학과)
  • Received : 2019.11.10
  • Accepted : 2019.12.13
  • Published : 2019.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: This study aimed to analyze the number of patients with and without medical history transported to the emergency department due to changes in daily temperature and season. Methods: Data on emergency activity sheet and daily weather were collected from March 2016 to February 2017 in the city of Gyeonggi-do. In total, 13,531 patients were transferred to the emergency department in 119 ambulance. Data were analyzed using the Statistical Package for the Social Sciences (version 21). Results: The daily average number of patients transferred was the highest in August and September, i.e., the summer season. The higher the daily highest and lowest temperatures, higher the daily average number of patients transferred. In contrast, patients with medical history of hypertension, diabetes, heart disease, cerebrovascular disease, and pulmonary disease had a higher incidence of transfers in the winter season and on days with lower temperature. Conclusion: The results indicate that as people become more active during the summer when temperatures are high, the chances of daily emergencies increases, whereas patients with medical history are more likely to experience emergencies when the temperatures were lower. Hence, 119 ambulances will have to be prepared in advance to deal with this trend.

Keywords

References

  1. Korea National Fire agency. 2017 Emergency medical service activity analysis. Available at:http://www.nfa.go.kr/nfa/releaseinformation/statisticalinformation/main/?boardId=bbs_0000000000000019&mode=view&cntId=15&category=&pageIdx=&searchCondition=&searchKeyword=, 2018.
  2. Kim YH, Kim CH, Lee WS, Noh MS. A Study on association between local climate change and disease deaths caused by ischaemic heart and cerebrovascular disease. Journal of the Korean Data Analysis Society 2015:17(4):1911-8.
  3. Cao J, Cheng Y, Zhao N, Song W, Jiang C, Chen R et al. Diurnal temperature range is a risk factor for coronary heart disease death. J Epidemiol 2009;19(6):328-32. https://doi.org/10.2188/jea.JE20080074
  4. Barnett AG, Tong S, Clements AC. What measure of temperature is the best predictor of mortality?. Environ Res 2010;110:604-11. https://doi.org/10.1016/j.envres.2010.05.006
  5. Gemmell I, McLoone P, Boddy F, Dickinson GJ, Watt GCM. Seasonal variation in mortality in Scotland. Int J Epidemiol 2000;29:274-9. https://doi.org/10.1093/ije/29.2.274
  6. Zanobetti A, Schwartz J. Temperature and mortality in nine US cities. Epidemiology 2008;19(4):563-70. https://doi.org/10.1097/EDE.0b013e31816d652d
  7. Michelozzi P, Sario MD. Temperature changes and the risk of cardiac events. BMJ 2010;341:c3720. https://doi.org/10.1136/bmj.c3720
  8. Bang JS. Air temperature effects to emergency visits of acute myocardial infarction patients -A hospital case study-. Unpublished master's thesis, Korea University 2012, Seoul, Korea.
  9. Kim JE. An Effect of Temperature on the Number of Patient Visits to the Emergency Department, Unpublished master's thesis, Korea University 2011, Seoul, Korea.
  10. Ha J, Yoon J, Kim H. Relationship between winter temperature and mortality in Seoul, South Korea, from 1994 to 2006. Science of The Total Environment 2009;407(7):2158-64. https://doi.org/10.1016/j.scitotenv.2008.12.029
  11. Schweiger L, Younger J, Ionides E, Desmond J. Autoregression models can reliably forecast emergency department occupancy levels 12 hours in advance. Acad Emerg Med 2007;14(5S):S82. https://doi.org/10.1197/j.aem.2007.03.928
  12. Jones SS, Evans RS, Allen TL, Thomas A, Haug PJ, Welch SJ et al. A multivariate time series approach to modeling and forecasting demand in the emergency department. Journal of biomedical informatics 2009;42(1):123-39. https://doi.org/10.1016/j.jbi.2008.05.003
  13. Lee JY, Min JH, Park JS, Chung SP, Park JS. The association of meterological and day-of-the-week factors with patient visits to emergency centers. Korean J Soc Emerg Med 2005;16(2):287-91.
  14. Diehl AK, Morris MD, Mannis SA. Use of calendar and weather data to predict walkin attendance. Southern Medical Journal 1981;74(6):709-12. https://doi.org/10.1097/00007611-198106000-00020
  15. Kim JH, Lee KY. Prehospital care and improvement of 119 emergency medical technician for the insect bite patients. Korean J Emerg Med Ser 2013;17(1):63-78. https://doi.org/10.14408/KJEMS.2013.17.1.063
  16. Kim HK. Study on the emergency dispatch factor. Unpublished master's thesis, Kyonggi University 2017, Suwon, Korea.
  17. Sung JO. Time series forecasting modeling for demand of emergency department. Unpublished master's thesis, Ajou University 2010, Suwon, Korea.