Predicting NICU Admissions in Near-Term and Term Infants with Low Illness Acuity
By Malini Mahendra, M. Steurer-Muller, Samuel F. Hohmann, R. Keller, Anil Aswani, R. Adams Dudley. 2020
12 citations recorded by the source corpus.
Describe NICU admission rate variation among hospitals in infants with birthweight ≥2500 g and low illness acuity, and describe factors that predict NICU admission. Retrospective study from the Vizient Clinical Data Base/Resource Manager®. Support vector machine methodology was used to develop statistical models using (1) patient characteristics (2) only the indicator for the inborn hospital and (3) patient characteristics plus indicator for the inborn hospital. NICU admission rates of 427,449 infants from 154 hospitals ranged from 0 to 28.6%. C-statistics for the patient characteristics model: 0.64 (Confidence Interval (CI) 0.62–0.65), hospital only model: 0.81 (CI, 0.81–0.82), and patient characteristic plus hospital variable model: 0.84 (CI, 0.83–0.84). There is wide variation in NICU admission rates in infants with low acuity diagnoses. In all cohorts, birth hospital better predicted NICU admission than patient characteristics alone.
Subfields: Emergency Medicine, General Health Professions, Pulmonary and Respiratory Medicine
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Citations in the corpus
- FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference (2017, background): “These results can potentially be explained by the diverse set of reasons that individuals might be admitted into the NICU that are not accounted for in these data (Mahendra et al., 2020).”