Validation of an EMR algorithm to measure the prevalence of ADHD in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN)

Abstract

Background: Building and validating electronic algorithms to identify patients with specific disease profiles using health data is becoming increasingly important to disease surveillance and population health management. The aim of this study was to develop and validate an algorithm to find patients with ADHD diagnoses within primary care electronic medical records (EMR); and then use the algorithm to describe the epidemiology of ADHD from 2008 to 2015 in a Canadian Primary care sample. Methods: This was a cross sectional time series that used data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN), a repository of primary care EMR data. A sample of electronic patient charts from one local clinic were manually reviewed to determine the positive predictive value (PPV) and negative predictive value (NPV) of an ADHD case-finding algorithm. In each study year a practice population was determined, and the algorithm was used to measure an observed prevalence of ADHD. The observed prevalence was adjusted for misclassification, as measured by the validity indices, to obtain an estimate of the true prevalence. Estimates were calculated by age group (4-17 year olds, 18 to 34 year olds, and 35 to 64 year olds) and gender, and compared over time. Results: The EMR algorithm had a PPV of 98.0% (95% CI [92.5, 99.5]) and an NPV of 95.0% (95% CI [92.9, 98.6]). After adjusting for misclassification, it was determined that the prevalence of patients with a clinical diagnosis of ADHD has risen in all age groups between 2008 and 2015, most notably in children and young adults (6.92, 95% CI [5.62, 8.39] to 8.57, 95% CI [7.32, 10.00]; 5.73, 95% CI [4.40, 7.23] to 7.33, 95% CI [6.04, 8.78], respectively). The well-established gender gap persisted in all age groups across time but was considerably smaller in older adults compared to children and young adults. Conclusion: Overall, the ADHD case-finding algorithm was found to be a valid tool to assess the epidemiology of ADHD in Canadian primary care practice. The increased prevalence of ADHD between 2008 and 2015 may reflect an improvement in the recognition and treatment of this disorder within primary care.

Validity of claims‐based algorithms to identify neurodevelopmental disorders in children

“…Few studies have reported on the accuracy of ADHD diagnoses in healthcare utilization data, with PPVs generally consistent with our estimate, accounting for the width of the confidence interval 16,25,27,28 . One study reported that inclusion of patients with ≥1 ADHD‐medication prescription without a documented diagnosis did not yield any additional confirmed cases 25 .…”

“…Excluding these 10 cases increased the PPV from 88% to 95%. Similar to these findings, a recent study by Morkem et al using a sample from one local clinic within the Canadian Primary Care Sentinel Surveillance Network reported a PPV of 95.9% (92.6%–98.0%) when requiring either 1 diagnostic code and ≥ 1 ADHD‐medication prescription or ≥ 2 encounters with a diagnostic code 27 . Thus, depending on the research question and the relative importance of high specificity versus sensitivity, using a more conservative definition (≥2 ADHD‐related encounters or 1 encounter and ≥ 1 prescription) might be the preferred approach.…”

“…There is limited data available on the validity of assessing NDDs using healthcare utilization databases. To the best of our knowledge, only claims‐based algorithms for ASD and ADHD have previously been validated 16,24–28 …”

A Review of Canadian Diagnosed ADHD Prevalence and Incidence Estimates Published in the Past Decade

“…A total of ten papers are included in the review [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ], all of which were published from 2012 to 2022 (see Table 1 ). Ten papers included prevalence estimates of ADHD in Canada [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. Out of these papers, one also examined the incidence of ADHD in Canada [ 15 ].…”

“…This group of studies based estimates on data collected from 1999 [ 11 , 20 ] to 2015/6 [ 12 , 17 , 20 ]. The range for data collection was similar for papers that focused on ADHD prevalence in children and/or adolescents (1999–2015/6) [ 11 , 15 , 17 , 18 , 20 ] and those that examined prevalence in adults (1999–2018) [ 13 , 14 , 15 , 16 , 19 ].…”