title: What brings children home? A prognostic study to predict length of hospitalisation.
abstract: Adequate discharge planning could improve patient health and reduce readmissions. Increased accessibility and adequate use of hospital capacity are asking for an adequate discharge planning by means of efficient prediction of length of stay (LOS). Predictive factors of LOS for paediatric patients are lacking in the current available evidence. We aimed to identify these predictive factors in order to predict an optimal LOS. We conducted a prognostic study of all patients admitted to five different paediatric wards of Emma Children's Hospital, a tertiary university hospital in the Netherlands. We investigated possible predictive factors based on the literature and an expert panel categorised in patient characteristics and medical and non-medical factors. This preliminary list was scored for all patients at the moment of discharge. All significant or relevant factors were used in a linear regression model to predict the LOS. We included 142 patients and explored the relationship between 28 variables, reflecting a mix of patient characteristics, medical and non-medical factors and LOS. In a univariable analysis, 17 variables were significantly related with LOS. Multivariable analysis found seven independent variables: sex, age category, specialism, risk of malnutrition, complications, home care and the involvement of other disciplines. These seven variables explained 48 % of the LOS (R(2) of 0.476).
  
  
  CONCLUSIONS
  Predictors of LOS consist patient characteristics, medical factors as well as non-medical factors (i.e. the need for home care and other disciplines). The latter factors can be influenced by changes in hospital policies.
authors.affiliation: Department of Quality Assurance & Process Innovation, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Evelien
authors.initials: E
authors.lastname: Tump
authors.forename: Jolanda M
authors.initials: JM
authors.lastname: Maaskant
authors.forename: Fleur E
authors.initials: FE
authors.lastname: Brölmann
authors.forename: Diederik K
authors.initials: DK
authors.lastname: Bosman
authors.forename: Dirk T
authors.initials: DT
authors.lastname: Ubbink
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007902:Length of Stay / Q000706:statistics & numerical data*; D016014:Linear Models; D008297:Male; D009426:Netherlands; D010351:Patient Discharge / Q000706:statistics & numerical data*; D011379:Prognosis; D012044:Regression Analysis