Literature DB >> 23772944

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

Sally R Hinchliffe1, Sarah E Seaton, Paul C Lambert, Elizabeth S Draper, David J Field, Bradley N Manktelow.   

Abstract

BACKGROUND: Understanding length of stay for babies in neonatal care is vital for planning services and for counselling parents. While previous work has focused on the length of stay of babies who survive to discharge, when investigating resource use within neonatal care, it is important to also incorporate information on those babies who die while in care. We present an analysis using competing risks methodology which allows the simultaneous modelling of babies who die in neonatal care and those who survive to discharge.
METHODS: Data were obtained on 2723 babies born at 24-28 weeks gestational age in 2006-10 and admitted to neonatal care. Death and discharge alive are two mutually exclusive events and can be treated as competing risks. A flexible parametric modelling approach was used to analyse these two competing events and obtain estimates of the absolute probabilities of death or discharge.
RESULTS: The absolute probabilities of death or discharge are presented in graphical form showing the cause-specific cumulative incidence over time by gender, gestational age and birthweight. The discharge of babies alive generally occurred over a longer time period for babies of lower gestational age and smaller birthweight than for bigger babies.
CONCLUSION: This study has presented a useful statistical method for modelling the length of stay where there are significant rates of in-unit mortality. In health care systems that are increasingly focusing on costs and resource planning, it is essential to consider not only length of stay of survivors but also for those patients who die before discharge.
© 2013 John Wiley & Sons Ltd.

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Year:  2013        PMID: 23772944     DOI: 10.1111/ppe.12053

Source DB:  PubMed          Journal:  Paediatr Perinat Epidemiol        ISSN: 0269-5022            Impact factor:   3.980


  5 in total

Review 1.  What factors predict length of stay in a neonatal unit: a systematic review.

Authors:  Sarah E Seaton; Lisa Barker; David Jenkins; Elizabeth S Draper; Keith R Abrams; Bradley N Manktelow
Journal:  BMJ Open       Date:  2016-10-18       Impact factor: 2.692

2.  Modelling Neonatal Care Pathways for Babies Born Preterm: An Application of Multistate Modelling.

Authors:  Sarah E Seaton; Lisa Barker; Elizabeth S Draper; Keith R Abrams; Neena Modi; Bradley N Manktelow
Journal:  PLoS One       Date:  2016-10-20       Impact factor: 3.240

3.  Competing risk survival analysis of time to in-hospital death or discharge in a large urban neonatal unit in Kenya.

Authors:  Jalemba Aluvaala; Gary S Collins; Beth Maina; Catherine Mutinda; Mary Wayiego; James A Berkley; Mike English
Journal:  Wellcome Open Res       Date:  2019-06-17

4.  Sociodemographic factors associated with time to discharge for hospitalised patients with asthma and asthma exacerbation using the Ghana Health Service District Information Management System 2 (DHIMS-2) database, 2012-2017.

Authors:  Clement T Narh; Joyce B Der; Maxwell Afetor; Anthony Ofosu; Maria Blettner; Daniel Wollschlaeger
Journal:  BMJ Open Respir Res       Date:  2021-11

5.  Estimating neonatal length of stay for babies born very preterm.

Authors:  Sarah E Seaton; Lisa Barker; Elizabeth S Draper; Keith R Abrams; Neena Modi; Bradley N Manktelow
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  2018-03-27       Impact factor: 5.747

  5 in total

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