Matthew Engelhard, MD, PhD (left) and Elliot Hill (right). Credit: Duke Health/ Shawn Rocco.
New research shows routine medical records could help a new AI tool flag the risk of ADHD early, when support matters most.
Attention-deficit/hyperactivity disorder (ADHD) affects millions of children, yet many go years without a diagnosis, missing the chance for early support that can change long-term outcomes even when early signs are present.
In a new study, Duke Health researchers found that artificial intelligence tools can analyse routine electronic health records to accurately estimate a child’s risk of developing ADHD years before a typical diagnosis.
By reviewing patterns in everyday medical data, the approach could help flag children who may benefit from earlier evaluation and follow-up.
The research highlights how powerful insights can come from information already collected during regular healthcare visits to help support early decision-making by primary care providers.
Lead author Elliot Hill, a data scientist in the Department of Biostatistics & Bioinformatics at Duke University School of Medicine, said: “We have this incredibly rich source of information sitting in electronic health records.
“The idea was to see whether patterns hidden in that data could help us predict which children might later be diagnosed with ADHD, well before that diagnosis usually happens.”
Specialised AI model
To arrive at the findings, researchers analysed electronic health records from more than 140,000 children, with and without ADHD.
They trained a specialised AI model to look at medical history from birth through early childhood.
The model learned to recognise combinations of developmental, behavioural, and clinical events that often appeared years before an ADHD diagnosis was made.
The model was highly accurate at estimating future ADHD risk in children aged five and older, with consistent performance across patient characteristics like sex, race, ethnicity, and insurance status.
Importantly, the tool does not make a diagnosis; it identifies children who may benefit from closer attention by their paediatric primary care provider or an earlier referral for ADHD assessment by a specialist.
Study senior author Matthew Engelhard, MD, PhD, in Duke’s Department of Biostatistics & Bioinformatics, advised: “This is not an AI doctor; it’s a tool to help clinicians focus their time and resources, so kids who need help don’t fall through the cracks or wait years for answers.”
The researchers note that earlier identification for screening could lead to earlier diagnosis and therefore earlier support, which is linked to better academic, social, and health outcomes for children with ADHD.
They also emphasise the need for further studies before such tools are used in clinical settings.
Study author, Naomi Davis, PhD, associate professor in the Department of Psychiatry and Behavioral Sciences, said: “Children with ADHD can really struggle when their needs aren’t understood and adequate supports are not in place.
“Connecting families with timely, evidence-based interventions is essential for helping them achieve their goals and laying a foundation for future success.”
Hill and Engelhard have also researched the use of AI models in predicting potential risks and causes for mental illness in adolescents.
The study is published in Nature Mental Health.
