Identification of Early Onset Dementia in Population-Based Health Administrative Data: A Validation Study Using Primary Care Electronic Medical Records

Abstract

Background: Early onset dementia (EOD) occurs when symptoms of dementia begin between 45 to 64 years of age. Objective: We developed and validated health administrative data algorithms for EOD and compared demographic characteristics and presence of comorbid conditions amongst adults with EOD, late onset dementia (LOD) and adults with no dementia in Ontario, Canada. Methods: Patients aged 45 to 64 years identified as having EOD in their primary care electronic medical records had their records linked to provincial health administrative data. We compared several combinations of physician’s claims, hospitalizations, emergency department visits and prescriptions. Age-standardized incidence and prevalence rates of EOD were estimated from 1996 to 2016. Results: The prevalence of EOD for adults aged 45 to 64 years in our primary care reference cohort was 0.12%. An algorithm of ≥1 hospitalization or ≥3 physician claims at least 30 days apart in a two-year period or ≥1 dementia medication had a sensitivity of 72.9% (64.5–81.3), specificity of 99.7% (99.7–99.8), positive predictive value (PPV) of 23.7% (19.1–28.3), and negative predictive value of 100.0%. Multivariate logistic regression found adults with EOD had increased odds ratios for several health conditions compared to LOD and no dementia populations. From 1996 to 2016, the age-adjusted incidence rate increased slightly (0.055 to 0.061 per 100 population) and the age-adjusted prevalence rate increased three-fold (0.11 to 0.32 per 100 population). Conclusion: While we developed a health administrative data algorithm for EOD with a reasonable sensitivity, its low PPV limits its ability to be used for population surveillance.