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Table 7 describes the predictive power of the frailty models to predict emergency readmission within 30 days (range of AUCs 0.57 0.63).
They are connected with the complexity of mechanical phenomena accompanying the drilling process and the absence of dependable methods of computer modeling providing the possibility to predict emergency situations and to exclude them in advance.
We determined interobserver variability in the classification of fetal heart rate (FHR) tracing with periodic deceleration as being reassuring or nonreassuring and in the ability to predict emergency cesarean delivery (ECD) or umbilical arterial pH < 7.00.
This study examines the use of phone referral information to predict Emergency Severity Index triage levels as a proxy to anticipate emergency department nursing resource allocation in a pediatric hospital.
The objectives of this study are to design an artificial neural network (ANN) and to test it retrospectively to determine if it may be used to predict emergency department (ED) volume.
Similar to the SEER subset study [ 5], prolonged LOS did not predict emergency readmission.
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SOPs are widely used in railway operations because they are explicit, finite instructions that provide detailed prescriptions to the operative staff on what to do in response to predicted emergency situations [46].
The same approach was used to identify factors predicting emergency readmissions.
Deprivation also predicted emergency readmission with 28 days, as did comorbidity and more advanced stage.
We further investigated factors predicting emergency readmission rates within 28 days of first admission and, specifically, whether LOS affected this.
The primary predictor variable was the score on the ERA Index, an instrument that predicts emergency room visits and hospitalization.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com