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Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses
Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses
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Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses
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Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses
Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses

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Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses
Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses
Journal Article

Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses

2023
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Overview
Using a machine-learning model, we examined drivers of antibiotic prescribing for antibiotic-inappropriate acute respiratory illnesses in a large US claims data set. Antibiotics were prescribed in 11% of the 42 million visits in our sample. The model identified outpatient setting type, patient age mix, and state as top drivers of prescribing.