Modelling Neonatal Care Pathways for Babies Born Preterm: An Application of Multistate Modelling
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Modelling length of stay in neonatal care is vital to inform service planning and the counselling
of parents. Preterm babies, at the highest risk of mortality, can have long stays in neonatal
care and require high resource use. Previous work has incorporated babies that die
into length of stay estimates, but this still overlooks the levels of care required during their
stay. This work incorporates all babies, and the levels of care they require, into length of
stay estimates. Data were obtained from the National Neonatal Research Database for singleton
babies born at 24–31 weeks gestational age discharged from a neonatal unit in
England from 2011 to 2014. A Cox multistate model, adjusted for gestational age, was
used to consider a baby’s two competing outcomes: death or discharge from neonatal care,
whilst also considering the different levels of care required: intensive care; high dependency
care and special care. The probabilities of receiving each of the levels of care, or
having died or been discharged from neonatal care are presented graphically overall and
adjusted for gestational age. Stacked predicted probabilities produced for each week of
gestational age provide a useful tool for clinicians when counselling parents about length of
stay and for commissioners when considering allocation of resources. Multistate modelling
provides a useful method for describing the entire neonatal care pathway, where rates of
in-unit mortality can be high. For a healthcare service focussed on costs, it is important to
consider all babies that contribute towards workload, and the levels of care they require.
of parents. Preterm babies, at the highest risk of mortality, can have long stays in neonatal
care and require high resource use. Previous work has incorporated babies that die
into length of stay estimates, but this still overlooks the levels of care required during their
stay. This work incorporates all babies, and the levels of care they require, into length of
stay estimates. Data were obtained from the National Neonatal Research Database for singleton
babies born at 24–31 weeks gestational age discharged from a neonatal unit in
England from 2011 to 2014. A Cox multistate model, adjusted for gestational age, was
used to consider a baby’s two competing outcomes: death or discharge from neonatal care,
whilst also considering the different levels of care required: intensive care; high dependency
care and special care. The probabilities of receiving each of the levels of care, or
having died or been discharged from neonatal care are presented graphically overall and
adjusted for gestational age. Stacked predicted probabilities produced for each week of
gestational age provide a useful tool for clinicians when counselling parents about length of
stay and for commissioners when considering allocation of resources. Multistate modelling
provides a useful method for describing the entire neonatal care pathway, where rates of
in-unit mortality can be high. For a healthcare service focussed on costs, it is important to
consider all babies that contribute towards workload, and the levels of care they require.
Date Issued
2016-10-20
Date Acceptance
2016-10-07
Citation
PLoS ONE, 2016, 11 (10)
ISSN
1932-6203
Publisher
Public Library of Science
Journal / Book Title
PLoS ONE
Volume
11
Issue
10
Copyright Statement
© 2016 Seaton et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Sponsor
National Institute for Health Research
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000386204500133&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
N/A
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
PREMATURE BABIES
COMPETING RISKS
SURVIVAL
INFANTS
LENGTH
STAY
POPULATION
VARIABLES
DEATH
TIME
Databases, Factual
Female
Gestational Age
Humans
Infant, Newborn
Infant, Premature
Intensive Care, Neonatal
Male
Models, Theoretical
Proportional Hazards Models
UK Neonatal Collaborative
MD Multidisciplinary
General Science & Technology
Publication Status
Published
Article Number
ARTN e0165202