Multi-stage emergency medicine logistics system optimization based on survival probability

Abstract

Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distribution model of survival is built, drone and ambulance arrival probability over time are discussed, a formula is proposed for maximum possible survival rate based on the probability of emergency medical logistics reaching the patient, and the results are analyzed using empirical data fitting distribution and numerical experiments performed with the model. The model is discussed as a reference point for management decision making by changing model parameters. Results show that compared to using current ambulance vehicles, ambulance drones delivering medical equipment for first aid on-site in emergencies can significantly increase survival rate, and the effect of collaborative multi-stage logistics optimization is better than that of any single stage logistics response optimization. Simulation results show that the medical rescue logistics service radius, speed, loading capacity and performance of ambulance drones impact the probability of survival, and there is an optimal service radius depending on the shape of probability distribution, which provides new information for management decisions.

Keywords

emergency medicine logistics / ambulance drone / survival probability / critical illness

References

[1] Budge S, Ingolfsson A, Zerom D (2010). Empirical analysis of ambulance travel times: The case of Calgary emergency medical services. Management Science, 56(4): 716–723

[2] Capucci A, Aschieri D, Guerra F, Pelizzoni V, Nani S, Villani G Q, Bardy G H (2016). Community-based automated external defibrillator only resuscitation for out-of-hospital cardiac arrest patients. American Heart Journal, 172: 192–200

[3] Chen H, Zhang J J, Jun M A, Zhao Y C (2008). The survey on the capacity of reaction for emergency in Beijing. Academic Journal of PLA Postgraduate Medical School, 29(5): 392–393 (in Chinese)

[4] Chong K, Henderson S G, Lewis M E (2016). The vehicle mix decision in emergency medical service systems. Manufacturing & Service Operations Management: M & SOM, 18(3): 347–360

[5] European Society of Cardiology (2013). Out-of-hospital cardiac arrest survival just 7 percent. Science Daily. 2017-3-30

[6] Fikar C, Gronalt M, Hirsch P (2016). A decision support system for coordinated disaster relief distribution. Expert Systems with Applications, 57: 104–116

[7] Gold L S, Fahrenbruch C E, Rea T D, Eisenberg M S (2010). The relationship between time to arrival of emergency medical services (EMS) and survival from out-of-hospital ventricular fibrillation cardiac arrest. Resuscitation, 81(5): 622–625

[8] Gu M, Li Z H, He Z J, Zhao Z W, Liu S Q (2016). A meta-analysis of the success rates of heartbeat restoration within the platinum 10 min among outpatients suffering from sudden cardiac arrest in China. Military Medical Research, 3: 6

[9] Haidari L A, Brown S T, Ferguson M, Bancroft E, Spiker M, Wilcox A, Ambikapathi R, Sampath V, Connor D L, Lee B Y (2016). The economic and operational value of using drones to transport vaccines. Vaccine, 34(34): 4062–4067

[10] Hansen C M, Kragholm K, Granger C B, Pearson D A, Tyson C, Monk L, Corbett C, Nelson R D, Dupre M E, Fosbøl E L, Strauss B, Fordyce C B, McNally B, Jollis J G (2015). The role of bystanders, first responders, and emergency medical service providers in timely defibrillation and related outcomes after out-of-hospital cardiac arrest: Results from a statewide registry. Resuscitation, 96: 303– 309

[11] He M J, Xu L L, Mindy D (2016). Status of pre-hospital emergency medical service in China and abroad. Journal of Nursing Management, 16(1): 24–26 (in Chinese)

[12] He S F, Huang Y, LI Q (2015). Application of quality control circle in the improvement of hospital emergency response rate in basic level hospitals. Nursing Practice and Research, 12(9): 148–150 (in Chinese)

[13] Hua W, Zhang L F, Wu Y F, Liu X Q, Guo D S, Zhou H L, Gou Z P, Zhao L C, Niu H X, Chen K P, Mai J Z, Chu L N, Zhang S (2009). Incidence of sudden cardiac death in China. Journal of the American College of Cardiology, 54(12): 1110–1118

[14] Huang Q (2014). Correlation analysis between emergency cardiopulmonary resuscitation time window and the success rate of resuscitation. Chinese Journal of Medicinal Guide, 16(1): 62–63

[15] Maxwell M S, Ni E C, Tong C, Henderson S G, Topaloglu H, Hunter S R (2014). A bound on the performance of an optimal ambulance redeployment policy. Operations Research, 62(5): 1014–1027

[16] MedSci (2013). Shenzhen sudden cardiac death patients survival rates less than 1 per thousand. 2017-3-30 (in Chinese)

[17] Merghani A, Narain R, Sharma S (2013). Sudden cardiac death: Detecting the warning signs. Clinical Medicine, 13(6): 614–617

[18] Musolino G, Polimeni A, Rindone C, Vitetta A (2013). Travel time forecasting and dynamic routes design for emergency vehicles. Procedia: Social and Behavioral Sciences, 87: 193–202

[19] Nielsen A M, Folke F, Lippert F K, Rasmussen L S (2013). Use and benefits of public access defibrillation in a nation-wide network. Resuscitation, 84(4): 430–434

[20] Olshansky B (2016). Automatic external defibrillator-only resuscitation in cardiac arrest? The approach may be shocking! American Heart Journal, 172: 182–184

[21] Thiels C A, Aho J M, Zietlow S P, Jenkins D H (2015). Use of unmanned aerial vehicles for medical product transport. Air Medical Journal, 34(2): 104–108

[22] Van Barneveld T C, Bhulai S, Rd V D M (2017). A dynamic ambulance management model for rural areas: Computing redeployment actions for relevant performance measures. Health Care Management Science, 20(2): 165–186

[23] Weisfeldt M L, Sitlani C M, Ornato J P, Rea T, Aufderheide T P, Davis D, Dreyer J, Hess E P, Jui J, Maloney J, Sopko G, Powell J, Nichol G, Morrison L J (2010). Survival after application of automatic external defibrillators before arrival of the emergency medical system. Journal of the American College of Cardiology, 55(16): 1713–1720

RIGHTS & PERMISSIONS

The Author(s) 2017. Published by Higher Education Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0)