title: Insurance status is an independent predictor of long-term survival after lung transplantation in the United States.
abstract: BACKGROUND
  Socioeconomic factors such as education, health insurance, and race are known to affect health outcomes. The United Network for Organ Sharing (UNOS) database provides a large cohort of lung transplant (LTx) recipients in which to evaluate the effect of insurance on survival.
  
  
  METHODS
  We retrospectively reviewed UNOS data for 11,385 adult primary LTx patients (1998-2008). Patients were stratified by insurance (private/self-pay, Medicare, Medicaid, and other type). All-cause mortality was examined with Cox proportional hazard regression incorporating 14 variables. The Kaplan-Meier method was used to model survival after LTx.
  
  
  RESULTS
  Of 11,385 recipients, 7,100 (62.4%) had private insurance/self-pay; 2,966 (26.1%) had Medicare; 815 (7.2%) had Medicaid; and 504 (4.4%) had other type insurance. During the study, 4,943 patients (43.4%) died. Medicare and Medicaid patients had 7.0% and 8.1% lower 10-year survival than did private insurance/self-pay patients, respectively. Insurance did not affect 30-day, 90-day, or 1-year survival. Medicare and Medicaid patients had decreased survival at 3 years and longer. In multivariable analyses, Medicare (hazard ratio, 1.10; 95% confidence interval, 1.03-1.19) and Medicaid (hazard ratio, 1.29; 95% confidence interval, 1.15-1.45) significantly increased risk of death. When deaths in the first year were excluded, survival differences persisted.
  
  
  CONCLUSIONS
  This study represents the largest cohort evaluating the effect of insurance on post-LTx survival. Medicare and Medicaid patients have worse survival after LTx compared with private insurance/self-paying patients.
authors.affiliation: Department of Surgery, Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, Maryland, USA.
authors.forename: Jeremiah G
authors.initials: JG
authors.lastname: Allen
authors.forename: George J
authors.initials: GJ
authors.lastname: Arnaoutakis
authors.forename: Jonathan B
authors.initials: JB
authors.lastname: Orens
authors.forename: John
authors.initials: J
authors.lastname: McDyer
authors.forename: John V
authors.initials: JV
authors.lastname: Conte
authors.forename: Ashish S
authors.initials: AS
authors.lastname: Shah
authors.forename: Christian A
authors.initials: CA
authors.lastname: Merlo
mesh_terms: D000328:Adult; D000368:Aged; D016208:Databases, Factual; D005260:Female; D005382:Financing, Personal / Q000706:statistics & numerical data; D006801:Humans; D019458:Insurance Coverage / Q000706:statistics & numerical data*; D007348:Insurance, Health / Q000145:classification* / Q000706:statistics & numerical data*; D016040:Lung Transplantation / Q000401:mortality*; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D006278:Medicare / Q000706:statistics & numerical data; D008875:Middle Aged; D017149:Private Sector / Q000706:statistics & numerical data; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D017741:Survivors; D016896:Treatment Outcome; D014481:United States