Open AccessNeonatal intensive care unit: predictive models for length of stay
Author(s) -
G. Jesse Bender,
Devin C. Koestler,
Hernando Ombao,
Maureen F. McCourt,
B Alskinis,
Lewis P. Rubin,
Jamés F. Padbury
Publication year - 2012
Publication title -
journal of perinatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 94
eISSN - 1476-5543
pISSN - 0743-8346
DOI - 10.1038/jp.2012.62
Subject(s) - medicine , akaike information criterion , gestational age , neonatal intensive care unit , prospective cohort study , birth weight , retrospective cohort study , pediatrics , intensive care , predictive modelling , illness severity , predictive validity , predictive value of tests , predictive value , severity of illness , emergency medicine , pregnancy , intensive care medicine , statistics , clinical psychology , genetics , mathematics , biology
Hospital length of stay (LOS) is important to administrators and families of neonates admitted to the neonatal intensive care unit (NICU). A prediction model for NICU LOS was developed using predictors birth weight, gestational age and two severity of illness tools, the score for neonatal acute physiology, perinatal extension (SNAPPE) and the morbidity assessment index for newborns (MAIN).