Pediatrics and Neonatology (Dec 2019)

The association of Trisomy 13 and 18 and hospital discharge outcomes among neonates in California: A retrospective cohort study

  • Edith Haghnazarian,
  • Jiaqi Hu,
  • Ashley Y. Song,
  • Philippe S. Friedlich,
  • Ashwini Lakshmanan

Journal volume & issue
Vol. 60, no. 6
pp. 617 – 622

Abstract

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Background: Despite Trisomy 13 and 18 being among the most fatal congenital anomalies, limited information exists about resource utilization and factors associated with length of stay (LOS) and total hospital charges (THC) for these anomalies. Methods: We studied data sets of the patient discharge data set from the California Office of Statewide Health Planning and Development from 2006 to 2010, to determine differences in resource utilization for survivors and non-survivors and identify the predictors of LOS and total hospital charges. Descriptive statistics were assessed for demographic and clinical characteristics. General linear regression models were used to identify predictors of LOS and THC. Results: Seventy-six Trisomy 13 and 115 Trisomy 18 patients were identified, for whom inpatient mortality was 27.6% and 20.9%, respectively. In patients with Trisomy 13, after adjusting for gender, ethnicity, advanced directive (DNR), insurance and co-morbidities on multivariate analysis, the provision of more than 96 h of mechanical ventilation was associated with significantly increased LOS (standard error, SE) by 18.0 ± 5.3 days and THC (SE) by $399,000 ± $85,000. In terms of insurance type, patients with private coverage had 10.8 ± 4.9 days more than patients with Medicaid. In patients with Trisomy 18, on multivariate analysis, after adjusting for gender, ethnicity, DNR, insurance and co-morbidities, more than 96 h of mechanical ventilation was associated with increased LOS (SE) by 36.8 ± 6.8 days and THC (SE) by $365,000 ± $59,000. Conclusion: Understanding predictors that are associated with longer LOS and higher THC may be associated in hospital resource allocation for this vulnerable population of infants. Key Words: neonate, resource utilization, Trisomy 13, Trisomy 18