Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data

Submitted: 23 March 2023
Accepted: 18 June 2023
Published: 20 July 2023
Abstract Views: 1711
PDF: 524
Supplementary Materials: 76
HTML: 51
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

This study integrates geographical information systems (GIS) with a mathematical optimization technique to enhance emergency medical services (EMS) coverage in a county in the northeast of Iran. EMS demand locations were determined through one-year EMS call data analysis. We formulated a maximal covering location problem (MCLP) as a mixed-integer linear programming model with a capacity threshold for vehicles using the CPLEX optimizer, an optimization software package from IBM. To ensure applicability to the EMS setting, we incorporated a constraint that maintains an acceptable level of service for all EMS calls. Specifically, we implemented two scenarios: a relocation model for existing ambulances and an allocation model for new ambulances, both using a list of candidate locations. The relocation model increased the proportion of calls within the 5-minute coverage standard from 69% to 75%. With the allocation model, we found that the coverage proportion could rise to 84% of total calls by adding ten vehicles and eight new stations. The incorporation of GIS techniques into optimization modelling holds promise for the efficient management of scarce healthcare resources, particularly in situations where time is of the essence.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Alifi MR, Hayati H, Supangkat SH, 2017. Optimization of school network using location-allocation analysis: Case study: Bandung, Indonesia. 2017 IEEE Region 10 Symposium (TENSYMP) held 14-15 July 2017, pp 1-6. Avalable from: https://ieeexplore.ieee.org/xpl/conhome/8062174/proceeding DOI: https://doi.org/10.1109/TENCONSpring.2017.8070099
Aringhieri R, Bruni ME, Khodaparasti S, Van Essen JT, 2017. Emergency medical services and beyond: Addressing new challenges through a wide literature review. Comput Oper Res 78:349-68. DOI: https://doi.org/10.1016/j.cor.2016.09.016
Azimi A, Bagheri N, Mostafavi S M, Furst M A, Hashtarkhani S, Amin F H, Eslami S, Kiani F, Vafaeinezhad R, Akbari T, Golabpour A , Kiani B, 2021. Spatial-time analysis of cardiovascular emergency medical requests: enlightening policy and practice. BMC Public Health 21:7. DOI: https://doi.org/10.1186/s12889-020-10064-1
Brotcorne L, Laporte G , Semet F, 2003. Ambulance location and relocation models. Eur J Oper Res 147:451-463. DOI: https://doi.org/10.1016/S0377-2217(02)00364-8
Buczkowska S, Coulombel N, De Lapparent M, 2019. A comparison of euclidean distance, travel times, and network distances in location choice mixture models. Netw Spat Econ 19:1215-48. DOI: https://doi.org/10.1007/s11067-018-9439-5
Cabral ELdS, Castro WRS, Florentino DRdM, Viana DdA, Costa Junior JFd, Souza RPd, Rêgo ACM, Araújo-Filho I, Medeiros AC, 2018. Response time in the emergency services. Systematic review. Acta Cir Bras 33:1110-21 DOI: https://doi.org/10.1590/s0102-865020180120000009
Cazabat G, Belu MG, Popa I, Paraschiv DM, 2017. Models and practice of retail location on the romanian market. Amfiteatru Econ 19:493.
Church R, Revelle C, 1974. The maximal covering location problem. Papers of the regional science association, Springer-Verlag, 101-118. DOI: https://doi.org/10.1007/BF01942293
Church RL, 2002. Geographical information systems and location science. Comput Oper Res 29:541-62. DOI: https://doi.org/10.1016/S0305-0548(99)00104-5
Chuvieco E, 1993. Integration of linear programming and GIS for land-use modelling. Int J Geogr Inf Sci 7:71-83. DOI: https://doi.org/10.1080/02693799308901940
Current JR , Storbeck JE, 1988. Capacitated covering models. Environ Plan B Urban Anal City Sci 15:153-163. DOI: https://doi.org/10.1068/b150153
Daskin M S, 1983. A maximum expected covering location model: formulation, properties and heuristic solution. Transp Sci 17:48-70. DOI: https://doi.org/10.1287/trsc.17.1.48
Daskin M S , Maass K L 2015. The p-median problem. Location science. Springer. DOI: https://doi.org/10.1007/978-3-319-13111-5_2
de Assis Corrêa F, Lorena LaN , Ribeiro GM, 2009. A decomposition approach for the probabilistic maximal covering location-allocation problem. Comput Oper Res 36:2729-2739. DOI: https://doi.org/10.1016/j.cor.2008.11.015
Farahani R Z, Asgari N, Heidari N, Hosseininia M, Goh M, 2012. Covering problems in facility location: A review. Comput Ind Eng 62:368-407. DOI: https://doi.org/10.1016/j.cie.2011.08.020
Ferguson WJ, Kemp K, Kost G, 2016. Using a geographic information system to enhance patient access to point-of-care diagnostics in a limited-resource setting. Int J Health Geogr 15:1-12. DOI: https://doi.org/10.1186/s12942-016-0037-9
Galvão RD, Chiyoshi FY, Morabito R, 2005. Towards unified formulations and extensions of two classical probabilistic location models. Comput Ind Eng 32:15-33. DOI: https://doi.org/10.1016/S0305-0548(03)00200-4
Gazani M , Niaki S, 2021. The capacitated maximal covering location problem with heterogeneous facilities and vehicles and different setup costs: An effective heuristic approach. Int J Ind Eng 12:79-90. DOI: https://doi.org/10.5267/j.ijiec.2020.9.002
Haddadi M, Sarvar M, Soori H, Ainy E, 2017. The pattern of pre-hospital medical service delivery in Iran; a cross sectional study. Emerg (Tehran) 5:e57.
Haghani A, 1996. Capacitated maximum covering location models: Formulations and solution procedures. J Adv Transp 30:101-36. DOI: https://doi.org/10.1002/atr.5670300308
Hashtarkhani S, Kiani B, Bergquist R, Bagheri N, Vafaeinejad R , Tara M, 2020. An age-integrated approach to improve measurement of potential spatial accessibility to emergency medical services for urban areas. Int J Health Plann Manage 35:788-798. DOI: https://doi.org/10.1002/hpm.2960
Hashtarkhani S, Kiani B, Mohammadi A, Mohammadebrahimi S, Dehghan-Tezerjani M, Samimi T, Tara M , Matthews S A, 2021. Spatio-temporal epidemiology of emergency medical requests in a large urban area. A scan-statistic approach. Geospat Health 16:1043 DOI: https://doi.org/10.4081/gh.2021.1043
Kafashpor A, Ghasempour Ganji S F, Sadeghian S , Johnson L W, 2018. Perception of tourism development and subjective happiness of residents in Mashhad, Iran. Asia Pac J Tour Res 23:521-31. DOI: https://doi.org/10.1080/10941665.2018.1476392
Kiani B, Bagheri N, Tara A, Hoseini B, Hashtarkhani S, Tara M, 2018. Comparing potential spatial access with self-reported travel times and cost analysis to haemodialysis facilities in North-eastern Iran. Geospat Health 13:703. DOI: https://doi.org/10.4081/gh.2018.703
Liao K, Guo D, 2008. A clustering‐based approach to the capacitated facility location problem 1. Trans GIS 12:323-339. DOI: https://doi.org/10.1111/j.1467-9671.2008.01105.x
Marianov V, Serra D, 1998. Probabilistic, maximal covering location—allocation models forcongested systems. J Reg Sci 38:401-24. DOI: https://doi.org/10.1111/0022-4146.00100
Martinez R, 1998. New vision for the role of emergency medical services. Ann Emerg Med 32:594-9. DOI: https://doi.org/10.1016/S0196-0644(98)70039-3
Mindahun W, Asefa B, 2019. Location allocation analysis for urban public services using GIS techniques: A case of primary schools in Yeka sub-city, Addis Ababa, Ethiopia. Am J Geogr Inf Syst 8:26-38.
Nguyen NA 2015. Quantitative Analysis of Ambulance Location-allocation and Ambulance State Prediction.
Nickel S, Steinhardt C, Schlenker H, Burkart W. 2022. Decision Optimization with IBM ILOG CPLEX Optimization Studio: A Hands-On Introduction to Modeling with the Optimization Programming Language (OPL). Springer Nature. DOI: https://doi.org/10.1007/978-3-662-65481-1
Nykiforuk CI , Flaman LM, 2011. Geographic information systems (GIS) for Health Promotion and Public Health: a review. Health Promot Pract 12:63-73. DOI: https://doi.org/10.1177/1524839909334624
Ong ME, Ng FS, Overton J, Yap S, Andresen D, Yong DK, Lim SH, Anantharaman V, 2009. Geographic-time distribution of ambulance calls in Singapore: utility of geographic information system in ambulance deployment (CARE 3). Ann Acad Med Singap 38:184-91. DOI: https://doi.org/10.47102/annals-acadmedsg.V38N3p184
Openshaw S, 1981. The modifiable areal unit problem. Quantitative geograph: A British view, pp.60-69.
Openstreetmap. 2021. OSM tags for routing [Online]. Available: https://wiki.openstreetmap.org/wiki/OSM_tags_for_routing/Maxspeed [Accessed].
Pons PT , Markovchick VJ, 2002. Eight minutes or less: does the ambulance response time guideline impact trauma patient outcome? J Emerg Med 23:43-8. DOI: https://doi.org/10.1016/S0736-4679(02)00460-2
Rhodes H, Rourke B, Pepe A, 2023. Ambulance Response in Eight Minutes or Less: Are Comorbidities a Factor. Am Surg. 6:31348231161792 DOI: https://doi.org/10.1177/00031348231161792
Sasaki S, Comber A J, Suzuki H , Brunsdon C, 2010. Using genetic algorithms to optimise current and future health planning--the example of ambulance locations. Int J Health Geogr. 9:4. DOI: https://doi.org/10.1186/1476-072X-9-4
Schietzelt TH , Densham P J, 2003. Location-allocation in GIS. Advanced spatial analysis: the CASA book of GIS. pp. 345.
Sher M, Adler N , Hakkert A, 2008. The police vehicle location-allocation problem. International Conference on Industrial Logistics, Citeseer.
Tabari P, Shabanikiya H, Bagheri N, Bergquist R, Hashtarkhani S, Kiani F, Mohammadi A , Kiani B, 2020. Paediatric, pedestrian road traffic injuries in the city of Mashhad in north-eastern Iran 2015-2019: a data note. BMC Res Notes 13:363. DOI: https://doi.org/10.1186/s13104-020-05203-1
Tomintz, M, Clarke G. P, Alfadhli N, 2015. Location-allocation models. In: Brunsdon C, Singleton A (eds), Geocomputation. A practical primer, 185-197. https://doi.org/10.4135/9781473916432 DOI: https://doi.org/10.4135/9781473916432.n11
Toregas C, Swain R, Revelle C , Bergman L, 1971. The location of emergency service facilities. Oper Res 19:1363-73. DOI: https://doi.org/10.1287/opre.19.6.1363
Vafaeinejad A, Bolouri S, Alesheikh A A, Panahi M , Lee C-W, 2020. The Capacitated Location-Allocation Problem Using the VAOMP (Vector Assignment Ordered Median Problem) Unified Approach in GIS (Geospatial Information Systam). Appl Sci 10:8505. DOI: https://doi.org/10.3390/app10238505
Yin P, Mu L, 2012. Modular capacitated maximal covering location problem for the optimal siting of emergency vehicles. Appl Geogr 34:247-54. DOI: https://doi.org/10.1016/j.apgeog.2011.11.013

How to Cite

Hashtarkhani, S. ., A. Matthews, S., Yin, P., Mohammadi, A. ., Mohammad Ebrahimi, S., Tara, M., & Kiani, B. (2023). Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data. Geospatial Health, 18(2). https://doi.org/10.4081/gh.2023.1198

List of Cited By :

Crossref logo