Literature DB >> 20662678

Use of geographic information systems to determine new helipad locations and improve timely response while mitigating risk of helicopter emergency medical services operations.

Cheryl P Z Foo1, Mahvareh Ahghari, Russell D MacDonald.   

Abstract

INTRODUCTION: Traumatic injury is a leading cause of morbidity and mortality, but these can be minimized by timely transport to definite care. Helicopter emergency medical services (HEMS) provide timely transport and can influence survival. However, accident analyses indicate that landing at an unsecured landing zone (LZ), particularly at night, increases the risk of aviation accidents. To ensure safety, some HEMS operations land only at designated, secured LZs.
OBJECTIVE: This study utilized geographic information systems (GISs) to compare locations of scene call requests and secure LZs. The goal was to determine the optimal placement of new helipads as a strategy to improve access while mitigating the risk of aviation accidents.
METHODS: Call request data from a large air medical transport service were used to determine the geographic locations of all requests for scene responses in 2006. Request locations were compared with the locations of existing helipads, and straight-line distances between scene and helipad were determined using the GIS application. The application was then used to determine potential locations for new helipads.
RESULTS: During the study period, 748 requests for scene calls and 269 helipads were available. There were 476 (52.4%) requests at least 10 kilometers from a helipad and 356 (36.6%) requests at least 15 kilometers from a helipad. One particular region, Southwestern Ontario, was identified as having the highest number of requests >15 kilometers from the closest helipad.
CONCLUSION: GISs can be used to determine potential locations for new helipad construction using historical call request data. This evidence-based approach can improve HEMS access while mitigating operational risk.

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Year:  2010        PMID: 20662678     DOI: 10.3109/10903127.2010.493983

Source DB:  PubMed          Journal:  Prehosp Emerg Care        ISSN: 1090-3127            Impact factor:   3.077


  5 in total

1.  Predicting ambulance time of arrival to the emergency department using global positioning system and Google maps.

Authors:  Ross J Fleischman; Mark Lundquist; Jonathan Jui; Craig D Newgard; Craig Warden
Journal:  Prehosp Emerg Care       Date:  2013-07-18       Impact factor: 3.077

2.  Toward an all-inclusive trauma system in Central South Ontario: development of the Trauma-System Performance Improvement and Knowledge Exchange (T-SPIKE) project.

Authors:  Paul T Engels; Angela Coates; Russell D MacDonald; Mahvareh Ahghari; Michelle Welsford; Tim Dodd; Katie Turcotte; Jeffrey D Doyle; Arthur M Eugenio; Jason P Green; J Eric Irvine; Paul J Lysecki; Simerpreet K Sandhanwalia; Sunjay V Sharma
Journal:  Can J Surg       Date:  2021-03-15       Impact factor: 2.089

3.  Developing an analytical tool for evaluating EMS system design changes and their impact on cardiac arrest outcomes: combining geographic information systems with register data on survival rates.

Authors:  Björn Sund
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2013-02-15       Impact factor: 2.953

4.  The Effect of Psychological Hotwash on Resilience of Emergency Medical Services Personnel.

Authors:  Abbasali Ebrahimian; Seyed-Mahdi Esmaeili; Arash Seidabadi; Ali Fakhr-Movahedi
Journal:  Emerg Med Int       Date:  2021-08-20       Impact factor: 1.112

5.  Accuracy of Perceived Estimated Travel Time by EMS to a Trauma Center in San Bernardino County, California.

Authors:  Michael M Neeki; Colin MacNeil; Jake Toy; Fanglong Dong; Richard Vara; Joe Powell; Troy Pennington; Eugene Kwong
Journal:  West J Emerg Med       Date:  2016-06-21
  5 in total

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