title: Geographic access to cancer care in the U.S.
abstract: BACKGROUND
  Although access to cancer care is known to influence patient outcomes, to the authors' knowledge, little is known regarding geographic access to cancer care, and how it may vary by population characteristics. This study estimated travel time to specialized cancer care settings for the continental U.S. population and calculated per capita oncologist supply.
  
  
  METHODS
  The closest travel times were estimated using a network analysis of the road distance weighted by travel speeds from the population or geographic centroid of every ZIP area in the continental U.S. to that of the nearest cancer care setting under consideration: National Cancer Institute (NCI)-designated Cancer Centers, academic medical centers, and oncologists. Alaska and Hawaii were excluded because travel in these states is often not road-based. Population and geographic characteristics including race/ethnicity, income, education, and region were derived from U.S. Census 2000 data and from rural-urban commuting area classifications. Oncologist supply per 100,000 residents in Hospital Referral Regions (pHRRs) was estimated by region.
  
  
  RESULTS
  Travel times of <or=1 hour were estimated for 45.2% of the population to the nearest NCI Cancer Center, 69.4% to the nearest academic-based care, and 91.8% to any specialized cancer care. Native Americans, nonurban dwellers, and residents in the South had the longest travel times to the nearest NCI Cancer Center compared with the overall U.S. population (median [interquartile range (IQR)] in minutes: 155 [62-308], 173 [111-257], and 164 [70-272], vs 78 [27-172], respectively). Travel burdens persisted for Native Americans and nonurban populations across all 3 cancer care settings. For all population strata, travel times markedly increased as the degree of cancer care specialization increased. The median oncologist supply for pHRRs was 2.83 per 100,000 individuals.
  
  
  CONCLUSIONS
  There are population groups with limited access to the most specialized cancer care settings.
authors.affiliation: The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth Medical School, Lebanon, New Hampshire 03756, USA. Tracy.L.Onega@dartmouth.edu
authors.forename: Tracy
authors.initials: T
authors.lastname: Onega
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Duell
authors.forename: Xun
authors.initials: X
authors.lastname: Shi
authors.forename: Dongmei
authors.initials: D
authors.lastname: Wang
authors.forename: Eugene
authors.initials: E
authors.lastname: Demidenko
authors.forename: David
authors.initials: D
authors.lastname: Goodman
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data; D000368:Aged; D001213:Asian / Q000706:statistics & numerical data; D004522:Educational Status; D005843:Geography; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D007198:Indians, North American / Q000706:statistics & numerical data; D008875:Middle Aged; D009369:Neoplasms / Q000208:ethnology / Q000628:therapy*; D011320:Primary Health Care / Q000706:statistics & numerical data*; D011365:Professional Practice Location / Q000706:statistics & numerical data*; D012424:Rural Population / Q000706:statistics & numerical data; D013997:Time Factors; D014481:United States; D014505:Urban Population / Q000706:statistics & numerical data; D044465:White People / Q000706:statistics & numerical data