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Modelling time to death or discharge in neonatal care: an application of competing risks

Sally R Hinchliffe1, Sarah E Seaton, Paul C Lambert

  • 1Department of Health Sciences, University of Leicester, Leicester, UK.

Paediatric and Perinatal Epidemiology
|June 19, 2013
PubMed

Insights

This study introduces a statistical method to model neonatal intensive care unit (NICU) length of stay, considering both infant survival and death. This approach is crucial for accurate resource planning and parental counseling in neonatal care.

Area of Science:

  • Neonatal medicine
  • Biostatistics
  • Health services research

Background:

  • Accurate length of stay (LOS) data for neonatal intensive care units (NICUs) is essential for service planning and parental support.
  • Previous LOS analyses often excluded infants who died in NICU, potentially underestimating resource use.
  • This study incorporates both infant mortality and survival to discharge using a competing risks methodology.

Purpose of the Study:

  • To apply competing risks methodology to simultaneously model infant death and survival to discharge in NICU.
  • To provide a more comprehensive understanding of length of stay in neonatal care.
  • To inform resource allocation and parental counseling by accounting for all outcomes.

Main Methods:

  • Utilized data from 2723 infants born between 24-28 weeks gestational age (2006-2010).
  • Employed a flexible parametric modeling approach to analyze death and discharge alive as competing risks.
  • Calculated absolute probabilities of death or discharge over time.

Main Results:

  • Presents cause-specific cumulative incidence curves for death and discharge by infant characteristics (gender, gestational age, birthweight).
  • Demonstrates that infants with lower gestational age and birthweight generally have longer lengths of stay, whether they survive or not.
  • Highlights variations in discharge timing based on infant demographics.

Conclusions:

  • The study validates a statistical method for modeling LOS in settings with significant in-unit mortality.
  • Emphasizes the necessity of including mortality data in LOS analyses for effective healthcare resource planning.
  • Advocates for a holistic approach to neonatal care resource management, considering all patient trajectories.
Abstract

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