Identifying Children and Youth With Autism Spectrum Disorder in Electronic Medical Records: Examining Health System Utilization and Comorbidities.
Jennifer D Brooks, Susan E Bronskill, Longdi Fu and 7 others
PMID 33098262WHAT IT FOUND
Children and youth with autism in Ontario family medicine records used significantly more health services than peers without autism.
They were more likely to visit psychiatrists, neurologists, and geneticists, undergo surgeries, and be hospitalized for psychiatric reasons.
Key findings
01A keyword search of the Cumulative Patient Profile in electronic medical records identified autism with high accuracy, while physician billing codes alone missed many cases.
02Children and youth with autism had a significantly higher prevalence of asthma, mood disorders, and schizophrenia compared to those without autism.
03Individuals with autism were approximately five times more likely to visit a psychiatrist and over three times more likely to visit a neurologist than those without autism.
STILL TO COME
How it was doneWhat they found
Read the rest of this summary
You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.
What it does not show
The identification algorithm missed 18% of ASD cases in the validation set, likely excluding milder presentations or those diagnosed by non-physician professionals. The study relied on physician billing codes, so it could not capture services provided by psychologists, social workers, or therapists (PT/OT/SLP) that are not billed through this specific administrative pathway. The sample was drawn from family medicine practices, which tend to be more rural and higher socioeconomic status than the general Ontario population, and excluded children who only see pediatricians. Comorbidity analysis was restricted to conditions with validated administrative algorithms, so other common issues like epilepsy or gastrointestinal disorders were not examined.
Declared interests
Funded by the Ontario Brain Institute. ICES is an independent nonprofit research institute funded by an annual grant from the Ontario Ministry of Health and Long-Term Care.
The easy way to misread this
Do not interpret the high utilization rates as evidence that this specific EMR algorithm is the best way to diagnose autism in your practice. The algorithm had 82% sensitivity, meaning it missed nearly one in five cases, and it relied entirely on physician records, ignoring diagnoses made by other professionals.