Insurance status is an independent predictor of long-term survival after lung transplantation in the United States.
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.
Allen
Jeremiah G
JG
Department of Surgery, Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, Maryland, USA.
Arnaoutakis
George J
GJ
Orens
Jonathan B
JB
McDyer
John
J
Conte
John V
JV
Shah
Ashish S
AS
Merlo
Christian A
CA
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