Increased risk of death among uninsured neonates

Health Serv Res. 2013 Aug;48(4):1232-55. doi: 10.1111/1475-6773.12042. Epub 2013 Feb 13.

Abstract

Objective: To estimate the contribution of health insurance status to the risk of death among hospitalized neonates.

Data sources: Kids' Inpatient Databases (KID) for 2003, 2006, and 2009.

Study design: KID 2006 subpopulation of neonatal discharges was analyzed by weighted frequency distribution and multivariable logistic regression analyses for the outcome of death, adjusted for insurance status and other variables. Multivariable linear regression analyses were conducted for the outcomes mean adjusted length of stay and hospital charges. The death analysis was repeated with KID 2003 and 2009.

Principal findings: Of 4,318,121 estimated discharges in 2006, 5.4 percent were uninsured. There were 17,892 deaths; 9.5 percent were uninsured. The largest risks of death were five clinical conditions with adjusted odds ratios (AOR) of 13.7-3.1. Lack of insurance had an AOR of 2.6 (95 percent CI: 2.4, 2.8), greater than many clinical conditions; AOR estimates in alternate models were 2.1-2.7. Compared with insureds, uninsureds were less likely to have been admitted in transfer, more likely to have died in rural hospitals and to have received fewer resources. Similar death outcome results were observed for 2003 and 2009.

Conclusions: Uninsured neonates had decreased care and increased risk of dying.

Keywords: Death; insurance; neonate.

MeSH terms

  • Female
  • Health Services Accessibility / statistics & numerical data
  • Healthcare Disparities / statistics & numerical data*
  • Hospital Charges / statistics & numerical data
  • Hospital Mortality*
  • Humans
  • Infant Mortality*
  • Infant, Newborn
  • Insurance Coverage / statistics & numerical data
  • Intensive Care Units, Neonatal / statistics & numerical data
  • Length of Stay / statistics & numerical data
  • Logistic Models
  • Male
  • Medically Uninsured / statistics & numerical data*
  • Multivariate Analysis
  • Patient Transfer / statistics & numerical data
  • Resource Allocation / statistics & numerical data
  • Retrospective Studies
  • Risk Factors
  • United States / epidemiology