Integrated locating of helicopter stations and helipads for wounded transfer under demand location uncertainty

Am J Emerg Med. 2017 Mar;35(3):410-417. doi: 10.1016/j.ajem.2016.11.024. Epub 2016 Nov 11.

Abstract

Health emergency medical service (HEMS) plays an important role in reducing injuries by providing advanced medical care in the shortest time and reducing the transfer time to advanced treatment centers. In the regions without ground relief coverage, it would be faster to transfer emergency patients to the hospital by a helicopter. In this paper, an integer nonlinear programming model is presented for the integrated locating of helicopter stations and helipads by considering uncertainty in demand points. We assume three transfer modes: (1) direct transfer by an ambulance, (2) transfer by an ambulance to a helicopter station and then to the hospital by a helicopter, (3) transfer by an ambulance to a predetermined point and then to the hospital by a helicopter. We also assume that demands occur in a square-shaped area, in which each side follows a uniform distribution. It is also assumed that demands in an area decrease errors in the distances between each two cities. The purpose of this model is to minimize the transfer time from demand points to the hospital by considering different modes. The proposed model is examined in terms of validity and applicability in Lorestan Province and a sensitivity analysis is also conducted on the total allocated budget.

Keywords: Emergency medical service; Helicopter emergency medical service; Transfer point location problem; Uncertainty.

MeSH terms

  • Air Ambulances / organization & administration
  • Air Ambulances / supply & distribution*
  • Aircraft
  • Emergency Medical Services / methods
  • Emergency Medical Services / organization & administration
  • Emergency Medical Services / supply & distribution
  • Health Services Needs and Demand*
  • Humans
  • Iran
  • Models, Organizational
  • Models, Theoretical
  • Needs Assessment / organization & administration
  • Organizational Case Studies
  • Time Factors
  • Transportation of Patients / methods*
  • Transportation of Patients / organization & administration
  • Transportation of Patients / statistics & numerical data