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Determining Emergency Medical Service Vehicle Deployment in Austin, Texas

Author

Listed:
  • David J. Eaton

    (Lyndon B. Johnson School of Public Affairs, University of Texas at Austin, Austin, Texas 78712)

  • Mark S. Daskin

    (Department of Civil Engineering, Northwestern University, Evanston, Illinois 60201)

  • Dennis Simmons

    (The City of Austin, P.O. Box 1088, Austin, Texas 78767)

  • Bill Bulloch

    (Nash, Phillips-Copus Company, 6200 La Calma Drive, Austin, Texas 78752)

  • Glen Jansma

    (Jansma Consulting, Inc., 2101 Travis Heights Boulevard, Austin, Texas 78704)

Abstract

In 1978 the city of Austin, Texas, began a study of its emergency medical service (EMS) system to determine what services should be delivered, by whom, via what number and types of equipment, and sited at which locations. The resulting plan called for a system quite different from that in operation since 1976: four advanced life-support and eight basic life-support vehicles were to operate from two EMS-only stations and 10 shared-use fire stations. The plan, which the city council unanimously passed in 1980, has saved $3.4 million (1984 dollars) in construction costs and $1.2 million (1984 dollars) per year in operating costs. Average response time has been reduced despite an upsurge in calls for service, and equitable service is provided to those who need it most.

Suggested Citation

  • David J. Eaton & Mark S. Daskin & Dennis Simmons & Bill Bulloch & Glen Jansma, 1985. "Determining Emergency Medical Service Vehicle Deployment in Austin, Texas," Interfaces, INFORMS, vol. 15(1), pages 96-108, February.
    • Handle: RePEc:inm:orinte:v:15:y:1985:i:1:p:96-108
    DOI: 10.1287/inte.15.1.96
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    Cited by:

    1. Alan T. Murray, 2016. "Maximal Coverage Location Problem," International Regional Science Review, , vol. 39(1), pages 5-27, January.
    2. Batta, Rajan & Lejeune, Miguel & Prasad, Srinivas, 2014. "Public facility location using dispersion, population, and equity criteria," European Journal of Operational Research, Elsevier, vol. 234(3), pages 819-829.
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    6. He, Zhou & Fan, Bo & Cheng, T.C.E. & Wang, Shou-Yang & Tan, Chin-Hon, 2016. "A mean-shift algorithm for large-scale planar maximal covering location problems," European Journal of Operational Research, Elsevier, vol. 250(1), pages 65-76.
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    13. Jing Yao & Alan T. Murray, 2014. "Locational Effectiveness of Clinics Providing Sexual and Reproductive Health Services to Women in Rural Mozambique," International Regional Science Review, , vol. 37(2), pages 172-193, April.
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    16. Wajid, Shayesta & Nezamuddin, N., 2022. "A robust survival model for emergency medical services in Delhi, India," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    17. Huizhu Wang & Jianqin Zhou & Ling Zhou, 2024. "A Lattice Boltzmann Method-like Algorithm for the Maximal Covering Location Problem on the Complex Network: Application to Location of Railway Emergency-Rescue Spot," Mathematics, MDPI, vol. 12(2), pages 1-20, January.
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    20. Huang, Yongxi & Fan, Yueyue & Cheu, Ruey Long, 2008. "Optimal Allocation of Multiple Emergency Service Resources for Protection of Critical Transportation Infrastructure," Institute of Transportation Studies, Working Paper Series qt83m87669, Institute of Transportation Studies, UC Davis.
    21. James J. Cochran & Martin S. Levy & Jeffrey D. Camm, 2010. "Bayesian coverage optimization models," Journal of Combinatorial Optimization, Springer, vol. 19(2), pages 158-173, February.
    22. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
    23. Benneyan, James C. & Musdal, Hande & Ceyhan, Mehmet Erkan & Shiner, Brian & Watts, Bradley V., 2012. "Specialty care single and multi-period location–allocation models within the Veterans Health Administration," Socio-Economic Planning Sciences, Elsevier, vol. 46(2), pages 136-148.
    24. Juan Villegas & Fernando Palacios & Andrés Medaglia, 2006. "Solution methods for the bi-objective (cost-coverage) unconstrained facility location problem with an illustrative example," Annals of Operations Research, Springer, vol. 147(1), pages 109-141, October.

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