title: Regional variation in spending and survival for older adults with advanced cancer.
abstract: BACKGROUND
  Medicare spending varies substantially across the United States. We evaluated the association between mean regional spending and survival in advanced cancer.
  
  
  METHODS
  We identified 116 523 subjects with advanced cancer from 2002 to 2007, using Surveillance, Epidemiology and End Results (SEER)-Medicare linked data. Subjects were aged 65 years and older with non-small cell lung, colon, breast, prostate, or pancreas cancer. Of these subjects, 61 083 had incident advanced-stage cancer (incident cohort) and 98 935 had death from cancer (decedent cohort); 37% of subjects were included in both cohorts. Subjects were linked to one of 80 hospital referral regions within SEER areas. We estimated mean regional spending in both cohorts. We assessed the primary outcome, survival, in the incident cohort; the exposure measure was the quintile of regional spending in the decedent cohort. Survival in quintiles 2 through 5 was compared with that in quintile 1 (lowest spending quintile) using Cox regression models.
  
  
  RESULTS
  From quintile 1 to 5, mean regional spending increased by 32% and 41% in the incident and decedent cohorts (incident cohort: $28 854 to $37 971; decedent cohort: $27 446 to $38 630). The association between spending and survival varied by cancer site and quintile; hazard ratios ranged from 0.92 (95% confidence interval [CI] = 0.82 to 1.04, pancreas cancer quintile 5) to 1.24 (95% CI = 1.11 to 1.39, breast cancer quintile 3). In most cases, differences in survival between quintile 1 and quintiles 2 through 5 were not statistically significant.
  
  
  CONCLUSIONS
  There is substantial regional variation in Medicare spending for advanced cancer, yet no consistent association between mean regional spending and survival.
authors.affiliation: Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02215, USA. gabrooks@partners.org
authors.forename: Gabriel A
authors.initials: GA
authors.lastname: Brooks
authors.forename: Ling
authors.initials: L
authors.lastname: Li
authors.forename: Dhruv B
authors.initials: DB
authors.lastname: Sharma
authors.forename: Jane C
authors.initials: JC
authors.lastname: Weeks
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Hassett
authors.forename: K Robin
authors.initials: KR
authors.lastname: Yabroff
authors.forename: Deborah
authors.initials: D
authors.lastname: Schrag
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000191:economics / Q000401:mortality; D002289:Carcinoma, Non-Small-Cell Lung / Q000191:economics / Q000401:mortality; D005260:Female; D005102:Health Expenditures; D006760:Hospitalization / Q000191:economics; D006801:Humans; D053208:Kaplan-Meier Estimate; D008175:Lung Neoplasms / Q000191:economics / Q000401:mortality; D008297:Male; D008498:Medical Record Linkage; D006278:Medicare; D009367:Neoplasm Staging; D009369:Neoplasms / Q000191:economics* / Q000401:mortality* / Q000473:pathology; D010166:Palliative Care / Q000191:economics; D010190:Pancreatic Neoplasms / Q000191:economics / Q000401:mortality; D018802:Patient-Centered Care / Q000191:economics; D016016:Proportional Hazards Models; D011471:Prostatic Neoplasms / Q000191:economics / Q000401:mortality; D018426:SEER Program; D014481:United States / Q000453:epidemiology