Prevalence and Incidence Trends of Attention Deficit/Hyperactivity Disorder in Children and Youth Aged 1–24 Years in Ontario, Canada: A Validation Study of Health Administrative Data Algorithms

Author:

Butt Debra A.12ORCID,Jaakkimainen Liisa234,Tu Karen256

Affiliation:

1. Department of Family and Community Medicine, Scarborough General Hospital, Scarborough Health Network, ON, Canada

2. Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto, ON, Canada

3. ICES, Toronto, ON, Canada

4. Sunnybrook Academic Family Health Team, Toronto, ON, Canada

5. Research and Innovation and Department of Family and Community Medicine, North York General Hospital, Toronto, ON, Canada

6. Toronto Western Family Health Team, University Health Network, Toronto, ON, Canada

Abstract

Objective To estimate prevalence and incidence rates over time in children and youth with attention deficit/hyperactivity disorder from the validation of population-based administrative data algorithms using family physicians’ electronic medical records as a reference standard. Methods A retrospective cohort study was conducted in Ontario, Canada to identify attention deficit/hyperactivity disorder among children and youth aged 1–24 years in health administrative data derived from case-finding algorithms using family physicians’ electronic medical records. Multiple administrative data algorithms identifying attention deficit/hyperactivity disorder cases were developed and tested from physician-diagnosis of attention deficit/hyperactivity disorder in the electronic medical record to determine their diagnostic accuracy. We calculated algorithm performance using sensitivity, specificity, and predictive values. The most optimal algorithm was used to estimate prevalence and incidence rates of attention deficit/hyperactivity disorder from 2014 to 2021 in Ontario. Results The optimal performing algorithm was “2 physician visits for attention deficit/hyperactivity disorder in 1 year or 1 attention deficit/hyperactivity disorder-specific prescription” with sensitivity: 83.2% (95% confidence interval [CI], 81.8% to 84.5%), specificity: 98.6% (95% CI, 98.5% to 98.7%), positive predictive value: 78.6% (95% CI, 77.1% to 80.0%) and negative predictive value: 98.9% (95% CI, 98.8% to 99.0%). From 2014, prevalence rates for attention deficit/hyperactivity disorder increased from 5.29 to 7.48 per 100 population in 2021 ( N = 281,785). Males had higher prevalence rates (7.49 to 9.59 per 100 population, 1.3-fold increase) than females (2.96–5.26 per 100 population, 1.8-fold increase) from 2014 to 2021. Incidence rates increased from 2014 (0.53 per 100 population) until 2018, decreased in 2020 then rose steeply in 2021 (0.89 per 100 population, N = 34,013). Males also had higher incidence rates than females from 2014 to 2020 with females surpassing males in 2021 (0.70–0.81 per 100 male population,1.2-fold increase versus 0.36–0.97 per 100 female population, 2.7-fold increase). Conclusions Attention deficit/hyperactivity disorder is increasing in prevalence. We developed an administrative data algorithm that can reliably identify children and youth with attention deficit/hyperactivity disorder with good diagnostic accuracy.

Funder

Centre for ADHD Awareness Canada

Canadian ADHD Resource Alliance

Publisher

SAGE Publications

Subject

Psychiatry and Mental health

Reference47 articles.

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