2026 Early Hearing Detection & Intervention Conference
March 15-17, 2026 • Jacksonville, FL
3/10/2025 | 3:10 PM - 3:40 PM | EHDI program considerations for leveraging Artificial Intelligence(AI)/Machine Learning(ML) initiatives to improve timeliness and reduce lost documentation | 315/316
EHDI program considerations for leveraging Artificial Intelligence(AI)/Machine Learning(ML) initiatives to improve timeliness and reduce lost documentation
Early Hearing Detection and Intervention (EHDI) programs rely on reporting from audiology providers to track and ensure that deaf or hard-of-hearing infants are identified and connected to early intervention services. However, in many jurisdictions there is often under-reporting of diagnostic audiology reports because pediatric audiologists have to manually enter their reports into jurisdictionally hosted EHDI information systems (EHDI-IS). Jurisdictions are seeking innovative solutions to streamline the process and solve this issue. The Centers for Disease Control and Prevention (CDC) EHDI program, the Public Health Informatics Institute (PHII), Amazon Web Services (AWS), private audiologists, and state EHDI programs are collaborating on a proof-of-concept (POC) using machine learning (ML) to streamline the data submission process to the EHDI-IS system for audiologists. This initiative aims to reduce the reporting burden on audiologists and reduce the infant data lost to documentation.
This presentation will cover what is needed for Artificial Intelligence (AI)/ML project success, including recommendations on project management and planning. Presenters will also share what is needed for data sharing agreements when establishing governance in AI/ML projects. Participants will receive recommendations on the types of partners to engage and how to establish buy-in for the use of AI/ML. The presentation will conclude with details on the initial results of the POC work and details on the refinement needed to categorize narrative audiology text into the EHDI-IS reporting categories. Participants will leave the session with considerations for leveraging AI/ML initiatives to streamline the documentation process aimed at improving timeliness and reducing lost documentation. Presenters will share insights into project planning, how to leverage AI/ML to improve timeliness of reporting, and how to join forces with the private sector on solution development.
- The participant will be able to identify strategies to improve the timeliness of pediatric diagnostic reporting of infants that fail their infant hearing screen.
- The participant will gain knowledge of the importance of project management and planning in AI/ML projects
- The participant will be able to identify ML solutions that can enhance data quality by identifying infant records lost to documentation.
Presentation:
3545975_18107LuraDaussat.pdf
Handouts:
3545975_18107LuraDaussat.pdf
Transcripts:
CART transcripts are NOT YET available, but will be posted shortly after the conference
Presenters/Authors
Lura Daussat
(Primary Presenter,Author), Public Health Informatics Institute , ldaussat@taskforce.org;
Lura Daussat serves as the director of the practice support business unit; before moving into this role, she was a senior informatics analyst for PHII. While at PHII she has worked on projects related to child and adolescent mental health and audiology reporting. Previously, Lura spent 12 years at OZ Systems, where she partnered with state public health programs that included newborn hearing screening. In addition, Lura authored two implementation guides for HL7 on exchanging data from devices to public health for newborn hearing screening and critical congenital heart disease.
Lura holds an MPH from Tulane University School of Public Health and Tropical Medicine and a BS in biology from the University of North Texas. She served three years as a Peace Corps Volunteer in Ghana between her undergraduate and graduate programs, and is currently a doctoral candidate in Georgia State University’s DrPH program.
ASHA DISCLOSURE:
Financial -
No relevant financial relationship exists.
Nonfinancial -
No relevant nonfinancial relationship exists.
AAA DISCLOSURE:
Financial -
No relevant financial relationship exists.
Nonfinancial -
No relevant nonfinancial relationship exists.
Caitlin Loretan
(), Centers for Disease Control and Prevention, cloretan@cdc.gov;
Caitlin Loretan, MPH is a Health Scientist on the CDC EHDI Team. Caitlin is a Health/Data Scientist with a background in epidemiology. As a member of the CDC EHDI Team, Caitlin is working on projects related to advancing data modernization efforts. Prior to joining the CDC EHDI Team, Caitlin worked as an Epidemiologist in the Office on Smoking and Health (CDC), where she focused her time on the National Youth Tobacco Survey and tobacco surveillance research.
ASHA DISCLOSURE:
Financial -
No relevant financial relationship exists.
Nonfinancial -
No relevant nonfinancial relationship exists.
AAA DISCLOSURE:
Financial -
No relevant financial relationship exists.
Nonfinancial -
No relevant nonfinancial relationship exists.
Tonny Bogere
(Co-Presenter,Author,Co-Author), Public Health Informatics Institute, tbogere@taskforce.org;
Tonny Bogere is a senior informatics analyst in the Public Health Informatics Institute’s Practice Support Unit. He previously managed informatics roles and assignments as a government contractor informatics specialist at the Centers for Disease Control and Prevention (CDC) – Division of Heart Disease and Stroke Prevention.Tonny completed a competency-based Public Health Informatics Fellowship Program at the CDC in Atlanta, where he provided informatics technical assistance to public health programs at the Global Immunization Division, Polio Eradication Branch. Tonny also spent nine years at the CDC Uganda country office, where he engaged in providing informatics expertise to identify user needs, design, implement, and maintain health data collection, analytics, and reporting platforms, including decision support systems for the Division of Global HIV and TB – PEPFAR programs.
In 2012, Tonny completed his Master of Science in Public Health Informatics at the University of Sheffield in the United Kingdom. During his spare time, he enjoys spending time with family and friends, traveling and playing soccer and lawn tennis.
ASHA DISCLOSURE:
Financial -
No relevant financial relationship exists.
Nonfinancial -
No relevant nonfinancial relationship exists.
AAA DISCLOSURE:
Financial -
No relevant financial relationship exists.
Nonfinancial -
No relevant nonfinancial relationship exists.