» Articles » PMID: 35001867

Using Machine Learning to Examine Drivers of Inappropriate Outpatient Antibiotic Prescribing in Acute Respiratory Illnesses

Abstract

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.

Citing Articles

Treatment Failure and Adverse Events After Amoxicillin-Clavulanate vs Amoxicillin for Pediatric Acute Sinusitis.

Savage T, Kronman M, Sreedhara S, Lee S, Oduol T, Huybrechts K JAMA. 2023; 330(11):1064-1073.

PMID: 37721610 PMC: 10509725. DOI: 10.1001/jama.2023.15503.


Regional Variation in Outpatient Antibiotic Prescribing for Acute Respiratory Tract Infections in a Commercially Insured Population, United States, 2017.

Bizune D, Tsay S, Palms D, King L, Bartoces M, Link-Gelles R Open Forum Infect Dis. 2023; 10(2):ofac584.

PMID: 36776774 PMC: 9905267. DOI: 10.1093/ofid/ofac584.


Outpatient Antibiotic and Antiviral Utilization Patterns in Patients Tested for Respiratory Pathogens in the United States: A Real-World Database Study.

Tse J, Near A, Cheng M, Karichu J, Lee B, Chang S Antibiotics (Basel). 2022; 11(8).

PMID: 36009927 PMC: 9405217. DOI: 10.3390/antibiotics11081058.