4.7 Article

Overcoming Spatial and Temporal Barriers to Public Access Defibrillators Via Optimization

Journal

JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
Volume 68, Issue 8, Pages 836-845

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jacc.2016.03.609

Keywords

automated external defibrillator; cardiac arrest; emergency cardiac care; resuscitation

Funding

  1. ZOLL Foundation (ZOLL Foundation Research Grant)
  2. National Heart, Lung, and Blood Institute in partnership
  3. National Institute of Neurological Disorders and Stroke
  4. Canadian Institutes of Health Research-Institute of Circulatory and Respiratory Health
  5. Defense Research and Development Canada
  6. Heart and Stroke Foundation of Canada
  7. American Heart Association
  8. Laerdal Foundation
  9. Canadian Institutes of Health Research
  10. Ontario Graduate Scholarship
  11. [5U01 HL077863]

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BACKGROUND Immediate access to an automated external defibrillator (AED) increases the chance of survival for out-of-hospital cardiac arrest (OHCA). Current deployment usually considers spatial AED access, assuming AEDs are available 24 h a day. OBJECTIVES The goal of this study was to develop an optimization model for AED deployment, accounting for spatial and temporal accessibility, to evaluate if OHCA coverage would improve compared with deployment based on spatial accessibility alone. METHODS This study was a retrospective population-based cohort trial using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public location OHCAs in Toronto, Ontario, Canada (January 2006 through August 2014) and obtained a list of registered AEDs (March 2015) from Toronto Paramedic Services. Coverage loss due to limited temporal access was quantified by comparing the number of OHCAs that occurred within 100 meters of a registered AED (assumed coverage 24 h per day, 7 days per week) with the number that occurred both within 100 meters of a registered AED and when the AED was available (actual coverage). A spatiotemporal optimization model was then developed that determined AED locations to maximize OHCA actual coverage and overcome the reported coverage loss. The coverage gain between the spatiotemporal model and a spatial-only model was computed by using 10-fold cross-validation. RESULTS A total of 2,440 nontraumatic public OHCAs and 737 registered AED locations were identified. A total of 451 OHCAs were covered by registered AEDs under assumed coverage 24 h per day, 7 days per week, and 354 OHCAs under actual coverage, representing a coverage loss of 21.5% (p < 0.001). Using the spatiotemporal model to optimize AED deployment, a 25.3% relative increase in actual coverage was achieved compared with the spatial-only approach (p < 0.001). CONCLUSIONS One in 5 OHCAs occurred near an inaccessible AED at the time of the OHCA. Potential AED use was significantly improved with a spatiotemporal optimization model guiding deployment. (C) 2016 by the American College of Cardiology Foundation.

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