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

Autor: Richard Birtwhistle, John A. Queenan, Rachael Morkem, Kenneth Handelman, David Barber
Rok vydání: 2019
Předmět:
Adult
Male
medicine.medical_specialty
Canada
Adolescent
Population
Attention deficit-hyperactivity disorder
Health Informatics
lcsh:Computer applications to medicine. Medical informatics
Health informatics
03 medical and health sciences
Young Adult
0302 clinical medicine
Epidemiology
Validation
medicine
Prevalence
Attention deficit hyperactivity disorder
Electronic Health Records
Humans
0501 psychology and cognitive sciences
Medical diagnosis
Young adult
education
Child
Disease surveillance
education.field_of_study
Primary Health Care
business.industry
Health Policy
Medical record
05 social sciences
Middle Aged
medicine.disease
030227 psychiatry
Computer Science Applications
Algorithm
Cross-Sectional Studies
Attention Deficit Disorder with Hyperactivity
Child
Preschool
lcsh:R858-859.7
Female
business
Sentinel Surveillance
Algorithms
050104 developmental & child psychology
Research Article
Zdroj: BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-8 (2020)
ISSN: 1472-6947
Popis: 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.
Databáze: OpenAIRE
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