Literature DB >> 20629415

Evaluating emergency medical service performance measures.

Laura A McLay1, Maria E Mayorga.   

Abstract

The ultimate goal of emergency medical service systems is to save lives. However, most emergency medical service systems have performance measures for responding to 911 calls within a fixed timeframe (i.e., a response time threshold), rather than measures related to patient outcomes. These response time thresholds are used because they are easy to obtain and to understand. This paper proposes a methodology for evaluating the performance of response time thresholds in terms of resulting patient survival rates. A model that locates ambulances to optimize patient survival rates is used for base comparison. Results are illustrated using real-world data collected from Hanover County, Virginia. The results indicate that locating ambulances to maximize seven and eight min response time thresholds simultaneously maximize patient survival. Nine and 10 min response time thresholds result in more equitable patient outcomes, with improved patient survival rates in rural regions.

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Year:  2010        PMID: 20629415     DOI: 10.1007/s10729-009-9115-x

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


  9 in total

1.  Survival models for out-of-hospital cardiopulmonary resuscitation from the perspectives of the bystander, the first responder, and the paramedic.

Authors:  R A Waalewijn; R de Vos; J G Tijssen; R W Koster
Journal:  Resuscitation       Date:  2001-11       Impact factor: 5.262

2.  Law enforcement agency defibrillation (LEA-D): proceedings of the National Center for Early Defibrillation Police AED Issues Forum.

Authors:  Vincent N Mosesso; Mary M Newman; Joseph P Ornato; Paul M Paris
Journal:  Resuscitation       Date:  2002-07       Impact factor: 5.262

3.  Response times: myths, measurement & management.

Authors:  Jay Fitch
Journal:  JEMS       Date:  2005-09

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Authors:  T D Valenzuela; D J Roe; S Cretin; D W Spaite; M P Larsen
Journal:  Circulation       Date:  1997-11-18       Impact factor: 29.690

5.  Paramedic response time: does it affect patient survival?

Authors:  Peter T Pons; Jason S Haukoos; Whitney Bludworth; Thomas Cribley; Kathryn A Pons; Vincent J Markovchick
Journal:  Acad Emerg Med       Date:  2005-07       Impact factor: 3.451

6.  Improved out-of-hospital cardiac arrest survival through the inexpensive optimization of an existing defibrillation program: OPALS study phase II. Ontario Prehospital Advanced Life Support.

Authors:  I G Stiell; G A Wells; B J Field; D W Spaite; V J De Maio; R Ward; D P Munkley; M B Lyver; L G Luinstra; T Campeau; J Maloney; E Dagnone
Journal:  JAMA       Date:  1999-04-07       Impact factor: 56.272

7.  Effectiveness of emergency medical services for victims of out-of-hospital cardiac arrest: a metaanalysis.

Authors:  G Nichol; A S Detsky; I G Stiell; K O'Rourke; G Wells; A Laupacis
Journal:  Ann Emerg Med       Date:  1996-06       Impact factor: 5.721

8.  Predicting survival from out-of-hospital cardiac arrest: a graphic model.

Authors:  M P Larsen; M S Eisenberg; R O Cummins; A P Hallstrom
Journal:  Ann Emerg Med       Date:  1993-11       Impact factor: 5.721

9.  Optimal defibrillation response intervals for maximum out-of-hospital cardiac arrest survival rates.

Authors:  Valerie J De Maio; Ian G Stiell; George A Wells; Daniel W Spaite
Journal:  Ann Emerg Med       Date:  2003-08       Impact factor: 5.721

  9 in total
  8 in total

1.  Characteristics of service requests and service processes of fire and rescue service dispatch centers: analysis of real world data and the underlying probability distributions.

Authors:  Ute Krueger; Katja Schimmelpfeng
Journal:  Health Care Manag Sci       Date:  2012-08-23

2.  A markov decision process model for the optimal dispatch of military medical evacuation assets.

Authors:  Sean K Keneally; Matthew J Robbins; Brian J Lunday
Journal:  Health Care Manag Sci       Date:  2014-09-16

3.  Time-dependent ambulance allocation considering data-driven empirically required coverage.

Authors:  Dirk Degel; Lara Wiesche; Sebastian Rachuba; Brigitte Werners
Journal:  Health Care Manag Sci       Date:  2014-03-08

4.  Timeliness of interfacility transfer for ED patients with ST-elevation myocardial infarction.

Authors:  Michael J Ward; Sunil Kripalani; Alan B Storrow; Dandan Liu; Theodore Speroff; Michael Matheny; Eric J Thomassee; Timothy J Vogus; Daniel Munoz; Carol Scott; Joseph L Fredi; Robert S Dittus
Journal:  Am J Emerg Med       Date:  2015-01-06       Impact factor: 2.469

Review 5.  Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges.

Authors:  Yiping Jiang; Yufei Yuan
Journal:  Int J Environ Res Public Health       Date:  2019-03-04       Impact factor: 3.390

6.  Identifying the vulnerable regions of emergency medical services based on the three-stage of accessibility: a case study in Xi'an, China.

Authors:  Ning Xu; Jianjun Bai; Ran Yan
Journal:  Int J Equity Health       Date:  2022-04-22

7.  Two-Tiered Ambulance Dispatch and Redeployment considering Patient Severity Classification Errors.

Authors:  Seong Hyeon Park; Young Hoon Lee
Journal:  J Healthc Eng       Date:  2019-12-09       Impact factor: 2.682

8.  Coverage versus response time objectives in ambulance location.

Authors:  Ľudmila Jánošíková; Peter Jankovič; Marek Kvet; Frederika Zajacová
Journal:  Int J Health Geogr       Date:  2021-07-02       Impact factor: 3.918

  8 in total

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