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Quickload Database Update CD V3.8 Free Download (Final 2022)



 


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Comparing the Performance of Different Strategies for the Classification of Readmission in Children with Common Conditions. Electronic health records are increasingly being used for routine medical care to improve the quality of care and enhance the safety of care. The purposes of this study were to (1) describe and compare the performance of different classification models in the prediction of readmission in a pediatric population with 2 common conditions (cystic fibrosis [CF] and childhood asthma) and (2) determine the factors associated with readmission in a pediatric population with these 2 common conditions. Children with CF or asthma were identified using the electronic health record system of a large pediatric health care system (n = 64,921). The performance of different classification models for predicting readmission was compared, and a final model was created. Clinical and demographic factors associated with readmission were determined using a multivariate logistic regression model. The average length of stay for children with CF was 3.6 days (standard deviation [SD] = 2.8 days) in the index admission. Readmission within 30 days of discharge occurred in 2696 (4.1%) of the children, including 947 (15.0%) of those with CF and 1650 (6.7%) of those with asthma. The mean length of stay in the index admission was longer in the readmission group (3.7 days, SD = 2.8 days) than in the no readmission group (2.8 days, SD = 2.4 days), and readmissions were more likely to occur in older children (P

 

 

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Quickload Database Update CD V3.8 Free Download (Final 2022)
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