title: Geographic variation in the demand for emergency care: A local population-level analysis.
abstract: BACKGROUND
  Geographic variation in healthcare has been traditionally studied in large areas such as hospital referral regions or service areas. These analyses are limited by variation that exists within local communities.
  
  
  METHODS
  Using a New York claims database, we analyzed variation in emergency department use using 35 million visits from 2008 to 2012 among 4797 Census tracts, a smaller unit than usually studied. Using multivariate analysis, we studied associations between population characteristics and proximity to healthcare with rates of emergency department use. We analyzed how factors associated with emergency department utilization differed among urban, suburban, and rural regions.
  
  
  RESULTS
  We found significant geographic variation in emergency department use among Census tracts. Public insurance and uninsurance were correlated with high emergency department utilization across all types of regions. We found that race, ethnicity, and poverty were only associated with high emergency department use in urban regions. In suburban and rural regions, a lower proportion of elderly residents and shorter distances to the nearest ED were correlated with high emergency department use.
  
  
  CONCLUSIONS
  Significant variation in emergency department use exists locally when studied within small geographic areas. Insurance type is significantly associated with variation in emergency department use across urban, suburban, and rural regions, whereas the significance of other factors depended on urbanicity.
  
  
  CONCLUSIONS
  Studying geographic variation at a more granular level can lead to better understanding of local population health, drivers of healthcare utilization, and inform targeted interventions. Given heterogeneity in emergency department use by Census tract, policies directed at shaping acute care utilization must consider these local geographic differences.
authors.affiliation: Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY, United States; Department of Population Health, New York University School of Medicine, New York, NY, United States. Electronic address: david.lee@nyumc.org.
authors.forename: David C
authors.initials: DC
authors.lastname: Lee
authors.affiliation: Ronald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY, United States; Department of Population Health, New York University School of Medicine, New York, NY, United States.
authors.forename: Kelly M
authors.initials: KM
authors.lastname: Doran
authors.affiliation: Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States; Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, PA, United States.
authors.forename: Daniel
authors.initials: D
authors.lastname: Polsky
authors.affiliation: Robert Wood Johnson Foundation Clinical Scholars Program, University of Pennsylvania, Philadelphia, PA, United States.
authors.forename: Emmanuel
authors.initials: E
authors.lastname: Cordova
authors.affiliation: Department of Emergency Medicine, Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, United States.
authors.forename: Brendan G
authors.initials: BG
authors.lastname: Carr
mesh_terms: D016208:Databases, Factual; D003710:Demography; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D005843:Geography; D006801:Humans; D008297:Male; D017057:Medically Uninsured / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D009518:New York; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data*; D012044:Regression Analysis
keywords: Emergency care; GIS; Geographic variation; Population health