Early Hearing Detection and Intervention programs in the United States rely on timely, accurate reporting so infants who are deaf or hard of hearing can be screened by one month, diagnosed by three months, and connected to early intervention services by six months. Across the U.S., there is an opportunity to enhance the reporting process for audiologists to state Early Hearing Detection and Intervention programs. Replacing manual data entry with more efficient and timely systems helps protect the early intervention window and ensures no child misses out on connections to care.

In response, a collaboration formed to reimagine pediatric audiology reporting. In partnership with The Task Force for Global Health’s Public Health Informatics Institute (PHII), the California Polytechnic State University Digital Transformation Hub (DxHub), powered by Amazon Web Services, collaborated with Mass Eye and Ear, Boston Children’s Hospital, the Massachusetts Universal Newborn Hearing Screening (UNHS) Program, and funded by the Centers for Disease Control and Prevention to design an innovative solution that leverages generative artificial intelligence.

The tool provides transparent reasoning for every classification. Audiologists can trace decisions step-by-step with a human-in-the-loop design that ensures that automation supports clinical judgment rather than replacing it.

The result is a scalable, automated system that reduces administrative burden, improves diagnostic consistency, and accelerates reporting to public health agencies. By automating classification while preserving clinical standards, the system helps ensure that infants and children who are deaf or hard of hearing are connected to services more quickly, and audiologists can spend less time on duplicative data entry. 

“This system can streamline how audiologists work and strengthen their reporting to state health departments, helping save time and improving connections to care,” says Lura Daussat, Business Unit Director of Practice Support for PHII.

Public health programs receive more complete, standardized data, which supports earlier intervention and better developmental outcomes for the infant. More timely and accurate data helps identify at-risk infants sooner, reduces the number of infants lost to follow-up, and ensures prompt referral to early intervention services. Because hearing is essential for language, cognitive, and social development in the first months of life, early intervention supports stronger language acquisition, reduces communication delays, and improves long-term educational outcomes. This project was supported by cooperative agreement number NU38PW000002, funded by the Centers for Disease Control and Prevention.  

Now being piloted with Mass Eye and Ear, Boston Children’s Hospital, and the Massachusetts UNHS Program, the solution is now available to other organizations looking to modernize their reporting.