title: Relevance of hospital characteristics as performance indicators for treatment of very-low-birth-weight neonates.
abstract: BACKGROUND
  Current attempts at centralization of neonatal care in Germany focus on a minimum volume of 30 very-low-birth-weight (VLBW, weighing <1250 g) neonate admissions per year. However, the evidence for a selective referral strategy based on hospital volume is unclear.
  
  
  METHODS
  A total of 5575 neonates weighing <1250 g treated in 31 hospitals in Bavaria between 2000 and 2011 were analysed using population-based data. The relevance of different hospital characteristics (i.e. hospital volume, bed capacity and teaching status) for explaining individual in-hospital mortality as well as interhospital variation in mortality rates was analysed using multilevel logistic regression analysis.
  
  
  RESULTS
  In a risk-adjusted model, only dichotomized hospital volume (<30 admissions) was significantly associated with higher mortality in VLBW neonates (odds ratio: 1.74; 95% confidence interval: 1.02-2.99). However, the higher mortality risk only applied to neonates with higher Clinical Risk Index for Babies (CRIB) scores. There was considerable heterogeneity in mortality rates between Bavarian hospitals. The median odds ratio for mortality between two neonates treated in a randomly chosen low-performing versus high-performing hospital was 1.62 in the null model (without explanatory variables). Hospital volume only explained 15.1% of interhospital variation in mortality rates after adjustment for case-mix. Other hospital characteristics were of minor relevance. A funnel plot of the standardized mortality ratio against the number of admissions showed that 41% of small-volume hospitals performed better than expected.
  
  
  CONCLUSIONS
  A selective referral strategy based solely on hospital volume will fall short of the task of optimal allocation of neonatal care by means of centralization.
authors.affiliation: 1 Bavarian Institute for Quality Assurance of Medical Care in Hospitals, Munich, Germany esser@baq-bayern.de.
authors.forename: Melanie
authors.initials: M
authors.lastname: Esser
authors.affiliation: 1 Bavarian Institute for Quality Assurance of Medical Care in Hospitals, Munich, Germany.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Lack
authors.affiliation: 2 Institute of Social Paediatrics and Adolescent Medicine, Division of Epidemiology, Ludwig-Maximilians-University of Munich, Germany.
authors.forename: Christina
authors.initials: C
authors.lastname: Riedel
authors.affiliation: 3 Institute of Medical Informatics, Biometrics and Epidemiology, Ludwig-Maximilians-University of Munich, Germany.
authors.forename: Ulrich
authors.initials: U
authors.lastname: Mansmann
authors.affiliation: 2 Institute of Social Paediatrics and Adolescent Medicine, Division of Epidemiology, Ludwig-Maximilians-University of Munich, Germany.
authors.forename: Ruediger
authors.initials: R
authors.lastname: von Kries
mesh_terms: D001509:Bed Occupancy / Q000706:statistics & numerical data*; D005260:Female; D005858:Germany; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006760:Hospitalization; D006761:Hospitals / Q000706:statistics & numerical data*; D006784:Hospitals, Teaching / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D007231:Infant, Newborn; D019102:Infant, Very Low Birth Weight; D007363:Intensive Care Units, Neonatal / Q000706:statistics & numerical data*; D008297:Male; D016017:Odds Ratio; D012307:Risk Factors