Small Area Variations in Out-of-Hospital Cardiac arrest: Does the Neighborhood Matter?

• Type of Material: Article
• Authors: Comilla Sasson, University of Michigan; Carla C. Keirns, Stony Brook University; Dylan Smith, Stony Brook University; Michael Sayre, Ohio State University; Michelle Macy, University of Michigan; William Meurer, University of Michigan; Bryan McNally, Emory University; Arthur L. Kellermann, Emory University; Theodore J. Iwashyna, University of Michigan
• Language: English
• Date: 2010-07-06
• Publisher: American College of Physicians
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2014 American College of Physicians. All Rights Reserved.
• Final Published Version (URL): http://annals.org/article.aspx?articleid=745860
• Title of Journal or Parent Work: Annals of Internal Medicine
• ISSN: 0003-4819
• Volume: 153
• Issue: 1
• Start Page: 19
• End Page: 22
• Research Categories: Health Sciences, Medicine and Surgery

Abstract

Background The incidence and outcomes of out-of-hospital cardiac arrest vary widely across cities. It is unknown whether similar differences exist at the neighborhood level. Objective Determine the extent to which different neighborhoods experience persistently high rates of cardiac arrest, but low rates of bystander CPR. Design & Setting Multi-level Poisson regression of 1,018 cardiac arrests from 161 census tracts in Fulton County (Atlanta), Georgia, between October 1, 2005 to November 30, 2008, as captured by the Cardiac Arrest Registry to Enhance Survival (CARES). Measurements Incidence of cardiac arrest by census tract and year and bystander cardiopulmonary resuscitation (CPR) rates. Results Adjusted rates of cardiac arrests varied from across neighborhoods (IQR:0.57–0.73/1000 people; mean 0.64/1000 people, SD 0.10), but were stable from year to year, (ICC=0.36, 95% CI, 0.26–0.50, p value<0.001). Adjusted bystander CPR rates by census tract also varied (IQR: 19–29 percent; mean 0.25, SD 0.10). Limitation Analysis based on data from single city. Conclusion Surveillance data can identify neighborhoods with persistently high incidence of cardiac arrest and low bystander CPR rates. These represent promising targets for community-based interventions.