title: Association of socioeconomic position and medical insurance with fetal diagnosis of critical congenital heart disease.
abstract: BACKGROUND
  Access to beneficial novel healthcare technology has been inequitable in the United States. Fetal echocardiography, used with increasing frequency for prenatal diagnosis (PD) of congenital heart disease, allows for optimal neonatal management and possible improved outcomes. We sought to evaluate whether PD of critical congenital heart disease is related to socioeconomic (SE) position, medical insurance, and race.
  
  
  RESULTS
  In a retrospective review of infants with critical congenital heart disease who underwent surgical or catheter intervention at age <30 days in our institution during 2003 to 2006, we extracted 6 SE variables for the block groups of patient residence from 2000 US Census and calculated a previously validated composite SE score for each patient. PD occurred in 222 (50%) infants. Race was not significantly associated with PD. Private insurance patients were much more likely to have PD (odds ratio, 3.7 versus public insurance; 95% CI, 2.4 to 5.7; P<0.001), as were patients of higher SE position (PD, 62% in highest quartile versus 35% in lowest quartile; P=0.001). Odds of PD increased with increasing SE score (odds ratio, 1.7, 2.3, and 2.9 for each quartile of higher SE score versus those in lowest SE quartile; P<0.001). Patients from economically poor neighborhoods were less likely to have PD (odds ratio, 1.2 for each 10% increase in prevalence of poverty; P=0.04). Private medical insurance (odds ratio, 3.4; 95% CI, 2.1 to 5.5; P<0.001) was the strongest predictor of PD in the logistic regression model.
  
  
  CONCLUSIONS
  Patients with public insurance and lower SE position are less likely to have a PD of critical congenital heart disease.
authors.affiliation: Department of Cardiology, Children's Hospital Boston, and Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA. Vasum@aya.yale.edu
authors.forename: Vasum
authors.initials: V
authors.lastname: Peiris
authors.forename: Tajinder P
authors.initials: TP
authors.lastname: Singh
authors.forename: Wayne
authors.initials: W
authors.lastname: Tworetzky
authors.forename: Erin C
authors.initials: EC
authors.lastname: Chong
authors.forename: Kimberlee
authors.initials: K
authors.lastname: Gauvreau
authors.forename: David W
authors.initials: DW
authors.lastname: Brown
mesh_terms: D000293:Adolescent; D000328:Adult; D004452:Echocardiography / Q000706:statistics & numerical data; D005260:Female; D005315:Fetal Diseases / Q000175:diagnosis* / Q000453:epidemiology*; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006330:Heart Defects, Congenital / Q000175:diagnosis* / Q000453:epidemiology*; D006801:Humans; D007231:Infant, Newborn; D007348:Insurance, Health / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D015999:Multivariate Analysis; D011203:Poverty / Q000706:statistics & numerical data; D011247:Pregnancy; D015995:Prevalence; D044469:Racial Groups / Q000706:statistics & numerical data; D012189:Retrospective Studies; D012959:Socioeconomic Factors; D016216:Ultrasonography, Prenatal / Q000706:statistics & numerical data; D014481:United States / Q000453:epidemiology; D055815:Young Adult