Disparities in access to left ventricular assist device therapy

J Surg Res. 2009 Mar;152(1):111-7. doi: 10.1016/j.jss.2008.02.065. Epub 2008 Apr 1.


Background: Implantation of a left ventricular assist device (LVAD) has been shown to improve survival and quality of life among selected patients with end-stage heart failure. We hypothesized that utilization of this complex and expensive treatment modality would be influenced by disparities in access to health care.

Materials and methods: We reviewed data from the National Inpatient Sample from 2002 to 2003. Patients were included in the study if they were admitted to the hospital with a primary diagnosis of congestive heart failure or cardiogenic shock. Patients older than 85 years of age and those with contraindications to LVAD therapy due to pre-existing medical conditions were excluded from the study. A multivariate logistic regression analysis was performed to determine the influence of patient characteristics (age, gender, race, comorbidities, socioeconomic status, insurance status, and population density of residence) as well as hospital characteristics (academic versus private and geographic region) on LVAD implantation.

Results: A total of 297,866 patients met the inclusion criteria for the study. Only 291 of these patients underwent LVAD implantation. Factors that adversely influenced access to therapy included age >65 (OR = 0.14), female gender (OR = 0.44), black race (OR = 0.29), admission to a non-academic center (OR = 0.16), and geographic region.

Conclusions: LVAD implantation was significantly influenced by disparities in access to treatment. Systematic reform in the delivery of evolving medical technologies to patients is needed to eliminate these disparities.

MeSH terms

  • Academic Medical Centers
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Comorbidity
  • Female
  • Healthcare Disparities*
  • Heart Failure / epidemiology
  • Heart Failure / therapy*
  • Heart-Assist Devices / statistics & numerical data*
  • Humans
  • Insurance Coverage
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Population Density
  • Racial Groups
  • Retrospective Studies
  • Sex Factors
  • Socioeconomic Factors
  • United States / epidemiology