Artificial Intelligence Diagnostic Decision Support to Reduce Antimicrobial Prescriptions in Young Children With Colds

Description

Ear infections are common in young children with cold symptoms, but they can be difficult to diagnose due to small ear canals, child movement, and limited viewing time. In this study, investigators will take photos of the eardrums of children 6-24 months of age with upper respiratory symptoms. The photos will be reviewed by imaging software enhanced with artificial intelligence (AI app) to determine whether the AI app changes how ear infections are diagnosed and treated. The AI app has undergone rigorous study and was found to be highly accurate; but how using this technology affects the diagnosis and treatment by clinicians has not been studied. This research may help improve diagnostic accuracy for ear infections and ensure antibiotics are prescribed only for those children who have definite ear infections.

Interventions

• Standard Clinical Ear Exam (Diagnostic test)
  The clinician will examine the child's ear with a standard otoscope and give a clinical diagnosis and decision to treat with antibiotics.
• AI app ear exam and diagnosis (Diagnostic test)
  Using a standard otoscope with a cell phone mounted to it, research personnel will record a video image of the tympanic membrane and send it to the cloud for analysis using AI enhanced classification software to render a diagnosis and treatment recommendation

Eligibility criteria

Conditions

Locations

• Children's Community Pediatrics Brentwood — Pittsburgh, Pennsylvania, United States
• Children's Community Pediatrics Castle Shannon — Pittsburgh, Pennsylvania, United States