title: Geographic and sociodemographic disparities in PET use by Medicare beneficiaries with cancer.
abstract: OBJECTIVE
  PET use for cancer care has increased unevenly, possibly because of regional health care market characteristics or underlying population characteristics. The aim of this study was to examine variation in advanced imaging use among individuals with cancer in relation to population and hospital service area (HSA) characteristics.
  
  
  METHODS
  A retrospective national study of fee-for-service Medicare beneficiaries with diagnoses of 1 of 5 cancers covered by Medicare for PET (2004-2008) was conducted. Crude and adjusted rates of PET, CT, and MRI were estimated for HSAs and sociodemographic subgroups. Generalized linear mixed models were used to assess the effects of race/ethnicity, area-level income, and HSA-level physician supply and spending on imaging utilization.
  
  
  RESULTS
  On the basis of an annual average of 116,452 beneficiaries with cancer, adjusted PET rates (imaging days per person-year) showed significantly higher use for whites compared with blacks in both 2004 (whites, 0.35 [95% confidence interval, 0.34-0.36]; blacks, 0.31 [95% confidence interval, 0.30-0.33]) and 2008 (whites, 0.64 [95% confidence interval, 0.63-0.65]; blacks, 0.57 [95% confidence interval, 0.55-0.59]). This trend was similar for the highest quartile of group-level median household income but was opposite for CT use, with blacks having higher rates than whites. The highest Medicare-spending HSAs had significantly higher adjusted PET rates compared with lower spending areas (0.57 [95% confidence interval, 0.55-0.60] vs 0.69 [95% confidence interval, 0.67-0.71] imaging days/person-year).
  
  
  CONCLUSIONS
  The use of PET among Medicare beneficiaries with cancer increased from 2004 to 2008, with higher rates observed among whites, among higher socioeconomic groups, and in higher Medicare spending areas. Sociodemographic differences in advanced imaging use are modality specific.
authors.affiliation: Department of Community and Family Medicine, Dartmouth Medical School, Lebanon, New Hampshire 03756, USA. tracy.l.onega@dartmouth.edu
authors.forename: Tracy
authors.initials: T
authors.lastname: Onega
authors.forename: Tor D
authors.initials: TD
authors.lastname: Tosteson
authors.forename: Qianfei
authors.initials: Q
authors.lastname: Wang
authors.forename: Bruce E
authors.initials: BE
authors.lastname: Hillner
authors.forename: Yunjie
authors.initials: Y
authors.lastname: Song
authors.forename: Barry A
authors.initials: BA
authors.lastname: Siegel
authors.forename: Anna N A
authors.initials: AN
authors.lastname: Tosteson
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D005260:Female; D006302:Health Services Research; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D008297:Male; D006278:Medicare; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000208:ethnology; D049268:Positron-Emission Tomography / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012923:Social Class; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data; D014481:United States