GIS served ambulance arrival time in the Kvemo Kartli region, Georgia

Mariam Elizbarashvili, Bela Kvirkvelia, Nino Chikhradze, Tamar Khuntselia, Elizbar Elizbarashvili

Article ID: 5152
Vol 8, Issue 8, 2024

VIEWS - 1207 (Abstract)

Abstract


We aimed to estimate the arrival time of the ambulance based on a GIS in Kvemo Kartli, one of the regions of Georgia, analyze contextual factors that affect this time, and support defining the target response time standards in the region and country. For this purpose, the isochrone map of ambulance travel time intervals to patients was created based on GIS, taking into account the location of the emergency bases, settlements, the length of the roads, and data on the maximum permitted speeds of the vehicle, based on which it is estimated what percentage of the population will and will not be reached by ambulance in the different time intervals. The results show that in the underserved areas where the ambulance cannot reach the patients, within 8 minutes lives 52 percent of the population of Kvemo Kartli, which is almost 222,976 people. Thus, the 8-minute reachability area of an ambulance should be expanded, and it is also necessary to define response time standards in the Kvemo Kartli region, Georgia. These actions will enhance the quality of emergency medical services and benefit the population.

Keywords


population; maximum allowed speeds; a life-threatening call; emergency

Full Text:

PDF


References

  1. Ambulance care in Europe Organization (2015) and practices of ambulance services in 14 European countries. Available online: https://www.nivel.nl/sites/default/files/bestanden/Rapport_ambulance_care_europe.pdf. (accessed on 1 February 2024).
  2. Aringhieri, R., Carello, G., & Morale, D. (2013). Supporting decision making to improve the performance of an Italian Emergency Medical Service. Annals of Operations Research, 236(1), 131–148. https://doi.org/10.1007/s10479-013-1487-0
  3. Blanchard, I. E., Doig, C. J., Hagel, B. E., et al. (2012). Emergency Medical Services Response Time and Mortality in an Urban Setting. Prehospital Emergency Care, 16(1), 142–151. https://doi.org/10.3109/10903127.2011.614046
  4. Bhattarai, H. K., Bhusal, S., Barone-Adesi, F., et al. (2023). Prehospital Emergency Care in Low- and Middle-Income Countries: A Systematic Review. Prehospital and Disaster Medicine, 38(4), 495–512. https://doi.org/10.1017/s1049023x23006088
  5. Carr, B. G., Branas, C. C., Metlay, J. P., et al. (2009). Access to Emergency Care in the United States. Annals of Emergency Medicine, 54(2), 261–269. https://doi.org/10.1016/j.annemergmed.2008.11.016
  6. Cabral, E. L. dos S., Castro, W. R. S., Florentino, D. R. de M., et al. (2018). Response time in the emergency services. Systematic review. Acta Cirurgica Brasileira, 33(12), 1110–1121. https://doi.org/10.1590/s0102-865020180120000009
  7. Colla, M., Santos, G. D., Oliveira, G. A., et al. (2023). Ambulance response time in a Brazilian emergency medical service. Socio-Economic Planning Sciences, 85, 101434. https://doi.org/10.1016/j.seps.2022.101434
  8. Elmqvist, C., Fridlund, B., & Ekebergh, M. (2008). More than medical treatment: The patient’s first encounter with prehospital emergency care. International Emergency Nursing, 16(3), 185–192. https://doi.org/10.1016/j.ienj.2008.04.003
  9. Fitrinitia, I. S. (2019). Integration Of Spatial Characteristic To Health Services For Improvement Of Children Health. International Journal of GEOMATE, 17(61). https://doi.org/10.21660/2019.61.8267
  10. Guagliardo, M. F. (2004). International Journal of Health Geographics, 3(1), 3. https://doi.org/10.1186/1476-072x-3-3
  11. Hsia, R., Razzak, J., Tsai, A. C., et al. (2010). Placing Emergency Care on the Global Agenda. Annals of Emergency Medicine, 56(2), 142–149. https://doi.org/10.1016/j.annemergmed.2010.01.013
  12. Lao, R., M. S., Paringit, R., et al. (2022). GIS-based site suitability analysis for healthcare facility development in Tacloban city, Philippines. International Journal of GEOMATE, 22(92), 16–23. https://doi.org/10.21660/2022.92.162
  13. Lawner, B. J., Hirshon, J. M., Comer, A. C., et al. (2016). The impact of a freestanding ED on a regional emergency medical services system. The American Journal of Emergency Medicine, 34(8), 1342–1346. https://doi.org/10.1016/j.ajem.2015.11.042
  14. Lovett, A., Haynes, R., Sünnenberg, G., et al. (2002). Car travel time and accessibility by bus to general practitioner services: a study using patient registers and GIS. Social Science & Medicine, 55(1), 97-111, https://doi.org/10.1016/S0277-9536(01)00212-X
  15. Mell, H. K., Mumma, S. N., Hiestand, B., et al. (2017). Emergency Medical Services Response Times in Rural, Suburban, and Urban Areas. JAMA Surgery, 152(10), 983. https://doi.org/10.1001/jamasurg.2017.2230
  16. Nogueira, L. C., Pinto, L. R., & Silva, P. M. S. (2014). Reducing Emergency Medical Service response time via the reallocation of ambulance bases. Health Care Management Science, 19(1), 31–42. https://doi.org/10.1007/s10729-014-9280-4
  17. Robert, K.Y. (2014). Case study research design and methods, 5th ed. Thousand Oaks, CA: Sage.
  18. Sade, R. M. (2011). Brain death, cardiac death, and the dead donor rule. Journal of the South Carolina Medical Association, 107(4), 146-149.
  19. Snooks, H. A., Khanom, A., Cole, R., et al. (2019). What are emergency ambulance services doing to meet the needs of people who call frequently? A national survey of current practice in the United Kingdom. BMC Emergency Medicine, 19(1). https://doi.org/10.1186/s12873-019-0297-3
  20. Takeda, R. A., Widmer, J. A., & Morabito, R. (2007). Analysis of ambulance decentralization in an urban emergency medical service using the hypercube queueing model. Computers & Operations Research, 34(3), 727–741. https://doi.org/10.1016/j.cor.2005.03.022
  21. Tanser, F., Gijsbertsen, B., & Herbst, K. (2006). Modelling and understanding primary health care accessibility and utilization in rural South Africa: An exploration using a geographical information system. Social Science & Medicine, 63(3), 691–705. https://doi.org/10.1016/j.socscimed.2006.01.015
  22. The Ambulance Response Program Review (2018). Available online: https://www.england.nhs.uk/publication/the-ambulance-response-programme-review/ (accessed on 1 February 2024).
  23. Vile, J. L., Gillard, J. W., Harper, P. R., et al. (2016). Time-dependent stochastic methods for managing and scheduling Emergency Medical Services. Operations Research for Health Care, 8, 42–52. https://doi.org/10.1016/j.orhc.2015.07.002


DOI: https://doi.org/10.24294/jipd.v8i8.5152

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Mariam Elizbarashvili, Bela Kvirkvelia, Nino Chikhradze, Tamar Khuntselia, Elizbar Elizbarashvili

License URL: https://creativecommons.org/licenses/by/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License.