Literature DB >> 26373555

A new preparedness policy for EMS logistics.

Seokcheon Lee1.   

Abstract

Response time in emergency medical services (EMS) is defined as the interval for an ambulance to arrive the scene after receipt of a 911 call. When several ambulances are available upon the receipt of a new call, a decision of selecting an ambulance has to be made in an effort to reduce response time. Dispatching the closest unit available is commonly used in practice; however, recently the Preparedness policy was designed that is in a simplistic form yet being capable of securing a long-term efficiency. This research aims to improve the Preparedness policy, resolving several critical issues inherent in the current form of the policy. The new Preparedness policy incorporates a new metric of preparedness based on the notion of centrality and involves a tuning parameter, weight on preparedness, which has to be appropriately chosen according to operational scenario. Computational experiment shows that the new policy significantly improves the former policy robustly in various scenarios.

Keywords:  Call-initiated dispatching; EMS logistics; Preparedness; Response time

Mesh:

Year:  2015        PMID: 26373555     DOI: 10.1007/s10729-015-9340-4

Source DB:  PubMed          Journal:  Health Care Manag Sci        ISSN: 1386-9620


  7 in total

Review 1.  The architecture of complex weighted networks.

Authors:  A Barrat; M Barthélemy; R Pastor-Satorras; A Vespignani
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-08       Impact factor: 11.205

2.  Analysis of weighted networks.

Authors:  M E J Newman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2004-11-24

3.  The importance of evidence-based disaster planning.

Authors:  Erik Auf der Heide
Journal:  Ann Emerg Med       Date:  2005-09-19       Impact factor: 5.721

4.  Why the closest ambulance cannot be dispatched in an urban emergency medical services system.

Authors:  Stephen F Dean
Journal:  Prehosp Disaster Med       Date:  2008 Mar-Apr       Impact factor: 2.040

5.  The association between ambulance hospital turnaround times and patient acuity, destination hospital, and time of day.

Authors:  Steve Vandeventer; Jonathan R Studnek; John S Garrett; Steven R Ward; Kevin Staley; Tom Blackwell
Journal:  Prehosp Emerg Care       Date:  2011-04-11       Impact factor: 3.077

6.  The centrality of a graph.

Authors:  G Sabidussi
Journal:  Psychometrika       Date:  1966-12       Impact factor: 2.500

Review 7.  A meta-analysis of prehospital care times for trauma.

Authors:  Brendan G Carr; Joel M Caplan; John P Pryor; Charles C Branas
Journal:  Prehosp Emerg Care       Date:  2006 Apr-Jun       Impact factor: 3.077

  7 in total
  2 in total

1.  Multicriteria decision frontiers for prescription anomaly detection over time.

Authors:  Babak Zafari; Tahir Ekin; Fabrizio Ruggeri
Journal:  J Appl Stat       Date:  2021-07-31       Impact factor: 1.416

2.  Quantum OPTICS and deep self-learning on swarm intelligence algorithms for Covid-19 emergency transportation.

Authors:  Habiba Drias; Yassine Drias; Naila Aziza Houacine; Lydia Sonia Bendimerad; Djaafar Zouache; Ilyes Khennak
Journal:  Soft comput       Date:  2022-04-08       Impact factor: 3.643

  2 in total

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