IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v163y2015icp112-123.html
   My bibliography  Save this article

Cost-effective analyses for emergency medical services deployment: A case study in Shanghai

Author

Listed:
  • Su, Qiang
  • Luo, Qinyi
  • Huang, Samuel H.

Abstract

The response speed of emergency medical services (EMS) is extremely critical for pre-hospital lifesaving. Each second plays a vital role in emergent cases. Therefore, the EMS network should be carefully designed to provide timely and reliable services. This paper focuses on improving the classical ambulance deployment method to optimize the distribution of first-aid resources. We refine the double coverage model with a new objective function that minimizes the expected cost for delayed emergencies plus the operational cost for EMS. EMS operators can use this refined model to analyze the cost-effectiveness of the emergency network, as demonstrated in a real-world EMS deployment case study. To solve this large-scale integer-programming problem, we compared several heuristic algorithms and finally chose ant colony optimization algorithm. Several modifications are made to adapt the traditional ant colony algorithm to solve our problem. The paper concludes with an optimized and cost-effective plan for ambulance deployment in the downtown area of Shanghai. After optimization, the objective cost is lowered by about 11% each year and 10% less emergency calls are missed or delayed. In addition, we use our modified model to test scenarios with relaxed limit of resources. Potential improvement of future EMS network is discovered. It turns out that increasing the number of first-aid stations from 35 (current number of stations) to 50 and adding 10 vehicles will achieve a surprising 49% cost saving while maintaining a satisfactory service level.

Suggested Citation

  • Su, Qiang & Luo, Qinyi & Huang, Samuel H., 2015. "Cost-effective analyses for emergency medical services deployment: A case study in Shanghai," International Journal of Production Economics, Elsevier, vol. 163(C), pages 112-123.
    • Handle: RePEc:eee:proeco:v:163:y:2015:i:c:p:112-123
    DOI: 10.1016/j.ijpe.2015.02.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527315000493
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2015.02.015?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Mark S. Daskin, 1983. "A Maximum Expected Covering Location Model: Formulation, Properties and Heuristic Solution," Transportation Science, INFORMS, vol. 17(1), pages 48-70, February.
    3. Richard C. Larson, 1975. "Approximating the Performance of Urban Emergency Service Systems," Operations Research, INFORMS, vol. 23(5), pages 845-868, October.
    4. Kalfakakou, Ria & Tsouros, Constantin C., 2001. "Determining the size and location of suppliers for a minimum total distribution route problem," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 401-405, May.
    5. A J Scott, 1971. "Dynamic Location-Allocation Systems: Some Basic Planning Strategies," Environment and Planning A, , vol. 3(1), pages 73-82, March.
    6. Constantine Toregas & Ralph Swain & Charles ReVelle & Lawrence Bergman, 1971. "The Location of Emergency Service Facilities," Operations Research, INFORMS, vol. 19(6), pages 1363-1373, October.
    7. Rajan Batta & June M. Dolan & Nirup N. Krishnamurthy, 1989. "The Maximal Expected Covering Location Problem: Revisited," Transportation Science, INFORMS, vol. 23(4), pages 277-287, November.
    8. Geroliminis, Nikolas & Kepaptsoglou, Konstantinos & Karlaftis, Matthew G., 2011. "A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network," European Journal of Operational Research, Elsevier, vol. 210(2), pages 287-300, April.
    9. Mark S. Daskin & Edmund H. Stern, 1981. "A Hierarchical Objective Set Covering Model for Emergency Medical Service Vehicle Deployment," Transportation Science, INFORMS, vol. 15(2), pages 137-152, May.
    10. Marianov, Vladimir & Revelle, Charles, 1994. "The queuing probabilistic location set covering problem and some extensions," Socio-Economic Planning Sciences, Elsevier, vol. 28(3), pages 167-178.
    11. Iannoni, Ana Paula & Morabito, Reinaldo, 2007. "A multiple dispatch and partial backup hypercube queuing model to analyze emergency medical systems on highways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 755-771, November.
    12. Egan, M. Jude, 2010. "Private goods and services contracts: Increased emergency response capacity or increased vulnerability?," International Journal of Production Economics, Elsevier, vol. 126(1), pages 46-56, July.
    13. Charles ReVelle & Kathleen Hogan, 1989. "The Maximum Availability Location Problem," Transportation Science, INFORMS, vol. 23(3), pages 192-200, August.
    14. Davis, Lauren B. & Samanlioglu, Funda & Qu, Xiuli & Root, Sarah, 2013. "Inventory planning and coordination in disaster relief efforts," International Journal of Production Economics, Elsevier, vol. 141(2), pages 561-573.
    15. Schmid, Verena & Doerner, Karl F., 2010. "Ambulance location and relocation problems with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1293-1303, December.
    16. Kunz, Nathan & Reiner, Gerald & Gold, Stefan, 2014. "Investing in disaster management capabilities versus pre-positioning inventory: A new approach to disaster preparedness," International Journal of Production Economics, Elsevier, vol. 157(C), pages 261-272.
    17. F C Mendonça & R Morabito, 2001. "Analysing emergency medical service ambulance deployment on a Brazilian highway using the hypercube model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(3), pages 261-270, March.
    18. Zied Jemai & L. Aboueljinane & E. Sahin, 2013. "A review on simulation models applied to emergency medical service operations," Post-Print hal-01672393, HAL.
    19. Michael O. Ball & Feng L. Lin, 1993. "A Reliability Model Applied to Emergency Service Vehicle Location," Operations Research, INFORMS, vol. 41(1), pages 18-36, February.
    20. Geroliminis, Nikolas & Karlaftis, Matthew G. & Skabardonis, Alexander, 2009. "A spatial queuing model for the emergency vehicle districting and location problem," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 798-811, August.
    21. Ana Iannoni & Reinaldo Morabito & Cem Saydam, 2008. "A hypercube queueing model embedded into a genetic algorithm for ambulance deployment on highways," Annals of Operations Research, Springer, vol. 157(1), pages 207-224, January.
    22. Fujiwara, Okitsugu & Makjamroen, Thanet & Gupta, Kapil Kumar, 1987. "Ambulance deployment analysis: A case study of Bangkok," European Journal of Operational Research, Elsevier, vol. 31(1), pages 9-18, July.
    23. Lin, C.K.Y., 2009. "Stochastic single-source capacitated facility location model with service level requirements," International Journal of Production Economics, Elsevier, vol. 117(2), pages 439-451, February.
    24. Hung, Yi-Feng & Hsiao, Jui-Yi, 2013. "Inventory rationing decision models during replenishment lead time," International Journal of Production Economics, Elsevier, vol. 144(1), pages 290-300.
    25. Thévenaz, Céline & Resodihardjo, Sandra L., 2010. "All the best laid plans...conditions impeding proper emergency response," International Journal of Production Economics, Elsevier, vol. 126(1), pages 7-21, July.
    26. Oloruntoba, Richard, 2010. "An analysis of the Cyclone Larry emergency relief chain: Some key success factors," International Journal of Production Economics, Elsevier, vol. 126(1), pages 85-101, July.
    27. Iannoni, Ana Paula & Morabito, Reinaldo & Saydam, Cem, 2009. "An optimization approach for ambulance location and the districting of the response segments on highways," European Journal of Operational Research, Elsevier, vol. 195(2), pages 528-542, June.
    28. Gilbert Laporte & François V Louveaux & Frédéric Semet & Arnaud Thirion, 2009. "Application of the Double Standard Model for Ambulance Location," Lecture Notes in Economics and Mathematical Systems, in: Jo A.E.E. Nunen & M. Grazia Speranza & Luca Bertazzi (ed.), Innovations in Distribution Logistics, chapter 12, pages 235-249, Springer.
    29. Schmid, Verena, 2012. "Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 219(3), pages 611-621.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    2. F. Javier Otamendi & David García-Heredia, 2015. "Isochrones as Indicators of the Influence of Traffic in Public Health: A Visual Simulation Application in Ávila, Spain," IJERPH, MDPI, vol. 12(10), pages 1-21, October.
    3. ShuJie Liao & Haiting Tu & Cheng Hu & Wulin Pan & Jianwu Xiong & Dongyang Yu & Lei Jing & Wei Pan, 2019. "Fuzzy multi-objective medical service organization selection model considering limited resources and stochastic demand in emergency management," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-15, March.
    4. Junhu Ruan & Felix T. S. Chan & Xiaofeng Zhao, 2018. "Re-Planning the Intermodal Transportation of Emergency Medical Supplies with Updated Transfer Centers," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
    5. Wang, Wei & Wu, Shining & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2021. "Emergency facility location problems in logistics: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    6. Shayesta Wajid & N. Nezamuddin, 2023. "Optimizing emergency services for road safety using a decomposition method: a case study of Delhi," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 155-173, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Boyacı, Burak & Geroliminis, Nikolas, 2015. "Approximation methods for large-scale spatial queueing systems," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 151-181.
    2. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    3. Shariat-Mohaymany, Afshin & Babaei, Mohsen & Moadi, Saeed & Amiripour, Sayyed Mahdi, 2012. "Linear upper-bound unavailability set covering models for locating ambulances: Application to Tehran rural roads," European Journal of Operational Research, Elsevier, vol. 221(1), pages 263-272.
    4. Caio Vitor Beojone & Regiane Máximo de Souza & Ana Paula Iannoni, 2021. "An Efficient Exact Hypercube Model with Fully Dedicated Servers," Transportation Science, INFORMS, vol. 55(1), pages 222-237, 1-2.
    5. Sun Hoon Kim & Young Hoon Lee, 2016. "Iterative optimization algorithm with parameter estimation for the ambulance location problem," Health Care Management Science, Springer, vol. 19(4), pages 362-382, December.
    6. Bélanger, V. & Lanzarone, E. & Nicoletta, V. & Ruiz, A. & Soriano, P., 2020. "A recursive simulation-optimization framework for the ambulance location and dispatching problem," European Journal of Operational Research, Elsevier, vol. 286(2), pages 713-725.
    7. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    8. Wang, Wei & Wu, Shining & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2021. "Emergency facility location problems in logistics: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    9. Cheng, Yung-Hsiang & Liang, Zheng-Xian, 2014. "A strategic planning model for the railway system accident rescue problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 75-96.
    10. Brotcorne, Luce & Laporte, Gilbert & Semet, Frederic, 2003. "Ambulance location and relocation models," European Journal of Operational Research, Elsevier, vol. 147(3), pages 451-463, June.
    11. M Gendreau & G Laporte & F Semet, 2006. "The maximal expected coverage relocation problem for emergency vehicles," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 22-28, January.
    12. Sorensen, Paul & Church, Richard, 2010. "Integrating expected coverage and local reliability for emergency medical services location problems," Socio-Economic Planning Sciences, Elsevier, vol. 44(1), pages 8-18, March.
    13. Geroliminis, Nikolas & Kepaptsoglou, Konstantinos & Karlaftis, Matthew G., 2011. "A hybrid hypercube - Genetic algorithm approach for deploying many emergency response mobile units in an urban network," European Journal of Operational Research, Elsevier, vol. 210(2), pages 287-300, April.
    14. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    15. Iannoni, Ana Paula & Morabito, Reinaldo & Saydam, Cem, 2011. "Optimizing large-scale emergency medical system operations on highways using the hypercube queuing model," Socio-Economic Planning Sciences, Elsevier, vol. 45(3), pages 105-117, September.
    16. Ansari, Sardar & Yoon, Soovin & Albert, Laura A., 2017. "An approximate hypercube model for public service systems with co-located servers and multiple response," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 143-157.
    17. McCormack, Richard & Coates, Graham, 2015. "A simulation model to enable the optimization of ambulance fleet allocation and base station location for increased patient survival," European Journal of Operational Research, Elsevier, vol. 247(1), pages 294-309.
    18. Sardar Ansari & Laura Albert McLay & Maria E. Mayorga, 2017. "A Maximum Expected Covering Problem for District Design," Transportation Science, INFORMS, vol. 51(1), pages 376-390, February.
    19. Iannoni, Ana Paula & Chiyoshi, Fernando & Morabito, Reinaldo, 2015. "A spatially distributed queuing model considering dispatching policies with server reservation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 49-66.
    20. Leknes, Håkon & Aartun, Eirik Skorge & Andersson, Henrik & Christiansen, Marielle & Granberg, Tobias Andersson, 2017. "Strategic ambulance location for heterogeneous regions," European Journal of Operational Research, Elsevier, vol. 260(1), pages 122-133.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:163:y:2015:i:c:p:112-123. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.