Medical first response models in rural villages and towns: A simulation study of response times
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Keywords

emergency medical services
rural health services
spatial analysis
computer simulation

How to Cite

1.
Pappinen J, Olkinuora A, Laukkanen-Nevala P. Medical first response models in rural villages and towns: A simulation study of response times. Australasian Journal of Paramedicine [Internet]. 2021Jan.3 [cited 2021Apr.20];18. Available from: https://ajp.paramedics.org/index.php/ajp/article/view/815

Abstract

Introduction

Medical first responders (MFR) shorten the response times and improve outcomes in, for example, out-of-hospital cardiac arrests. This study demonstrates the usability of open geographic data for analysing MFR service performance by comparing simulated response times of different MFR models in rural town and village settings in Finland.

Methods

Community first response (CFR) models with one to three responders obeying the speed limit were compared to a volunteer/retained fire department (FD) model where three responders first gather at a fire station and then drive to the scene with lights and siren. Five villages/towns, each with a volunteer/retained FD but no ambulance base within a 10 km radius, were selected to test the models. A total of 50,000 MFR responses with randomly selected buildings as potential responder and patient locations were simulated.

Results

In central areas, the simulated median response time for the one-responder model was 1.6 minutes, outperforming the FD model’s simulated response time median by 4.5 minutes. In surrounding rural areas, the median response times of one- and two-responder CFR models were still shorter (15.0 and 15.9 minutes, respectively) than in the FD model (16.4 minutes), but the FD model outperformed the three-responder CFR model (16.8 minutes).

Conclusion

Open geographic datasets were useful in performing logistic simulations of MFR. Based on the simulations, CFR without emergency vehicles may reach patients faster than FD-based MFR in central areas, whereas in surrounding rural areas the difference is less pronounced.

https://doi.org/10.33151/ajp.18.815
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References

Hansen C, Kragholm K, Pearson DA, et al. Association of bystander and first-responder intervention with survival after out-of-hospital cardiac arrest in North Carolina, 2010-2013. JAMA 2015;314:255-64. doi: 10.1001/jama.2015.7938

Capucci A, Aschieri D, Piepoli MF, et al. Tripling survival from sudden cardiac arrest via early defibrillation without traditional education in cardiopulmonary resuscitation. Circulation 2002;106:1065-70. doi: 10.1161/01.cir.0000028148.62305.69

Van Alem AP, Vrenken RH, de Vos R, Tijssen JG, Koster RW. Use of automated external defibrillator by first responders in out of hospital cardiac arrest: prospective controlled trial. BMJ 2003;327:1312-5. doi: 10.1136/bmj.327.7427.1312

White RD, Asplin BR, Bugliosi TF, Hankins DG. High discharge survival rate after out-of-hospital ventricular fibrillation with rapid defibrillation by police and paramedics. Ann Emerg Med 1996;28:480-5. doi: 10.1016/s0196-0644(96)70109-9/

Husum H, Gilbert M, Wisborg T, Heng Y, Murad M. Rural prehospital trauma systems improve trauma outcome in low-income countries: a prospective study from North Iraq and Cambodia. J Trauma 2003;54:1188-96. doi: 10.1097/01.TA.0000073609.12530.19

Murad M, Husum H. Trained lay first responders reduce trauma mortality: a controlled study of rural trauma in Iraq. Prehosp Disaster Med 2010;25:533-9. doi: 10.1017/s1049023x00008724

Harve H, Silfvast T. The use of automated external defibrillators by non-medical first responders in Finland. Eur J Emerg Med 2004;11:130-3. doi: 10.1097/01.mej.0000129166.59063.1a

Roberts A, Nimegeer A, Farmer J, Heaney DJ. The experience of community first responders in co-producing rural health care: in the liminal gap between citizen and professional. BMC Health Serv Res 2014;14:460. doi: 10.1186/1472-6963-14-460

O’Meara P, Duthie S. Paramedicine in Australia and New Zealand: a comparative overview. Aust J Rural Health 2018;26:363-8. doi: 10.1111/ajr.12464

Andelius L, Hansen C, Lippert F, et al. 68 risks and benefits using a mobile-phone positioning system to activate lay volunteers to out-of-hospital cardiac arrests. BMJ Open 2018;8:A26. doi: 10.1136/bmjopen-2018-EMS.68

Berglund E, Claesson A, Nordberg P, et al. A smartphone application for dispatch of lay responders to out-of-hospital cardiac arrests. Resuscitation 2018;126:160-5. doi: 10.1016/j.resuscitation.2018.01.039

Yonekawa C, Suzukawa M, Yamashita K, et al. Development of a first-responder dispatch system using a smartphone. J Telemed Telecare 2014;20:75-81. doi: 10.1177/1357633X14524152

Addresses, postal codes and WGS84-coordinates of Finnish buildings [Internet]. 2017. Available at: www.avoindata.fi/data/en_GB/dataset/postcodes/ [Accessed1 July 2017].

Finland’s Environmental Institution. Delineation of Localities (Densely Populated Areas) [Internet]. Available at: www.ymparisto.fi/en-US/Living_environment_and_planning/Community_structure/Information_about_the_community_structure/Delineation_of_densely_populated_areas/ [Accessed 5 September 2020].

Ruth B, Apichat S. Using Monte Carlo simulation to refine emergency logistics response models: a case study. Int J Phys Distr Log 2010;40:709-21. doi: 10.1108/09600031011079346

OpenStreetMap. Planet dump [Internet]. 2015. Available at: https://planet.openstreetmap.org/ [Accessed 1 July 2017].

Karich P, Schroder S. GraphHopper directions API with route optimization [Internet]. 2017. Available at: www.graphhopper.com/

Murray B, Kue R. The use of emergency lights and sirens by ambulances and their effect on patient outcomes and public safety: a comprehensive review of the literature. Prehosp Disaster Med 2017;32:209-16. doi: 10.1017/S1049023X16001503

Valenzuela T, Roe D, Cretin S, Spaite D, Larsen M. Estimating effectiveness of cardiac arrest interventions: a logistic regression survival model. Circulation 1997;96:3308-13. doi: 10.1161/01.cir.96.10.3308

Hara M, Hayashi K, Hikoso S, Sakata Y, Kitamura T. Different impacts of time from collapse to first cardiopulmonary resuscitation on outcomes after witnessed out-of-hospital cardiac arrest in adults. Circ Cardiovasc Qual Outcomes 2015;8:277-84. doi: 10.1161/CIRCOUTCOMES.115.001864

Ko S, Do Shin S, Ro Y, et al. Effect of detection time interval for out-of-hospital cardiac arrest on outcomes in dispatcher-assisted cardiopulmonary resuscitation: a nationwide observational study. Resuscitation 129:61-69. doi: 10.1016/j.resuscitation.2018.06.002

Karam N, Marijon E, Dumas F, et al. Characteristics and outcomes of out-of-hospital sudden cardiac arrest according to the time of occurrence. ibid. 2017;116:16-21. doi: 10.1016/j.resuscitation.2017.04.024

Petzäll K, Petzäll J, Jansson J, Nordström G. Time saved with high speed driving of ambulances. Accid Anal Prev 2011;43:818-22. doi: 10.1016/j.aap.2010.10.032