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BackgroundAtopic dermatitis is known to be common among children, but there are few studies examining the epidemiology across the life course. In particular, there is a paucity of data on atopic dermatitis among older adults.ObjectiveTo evaluate participant characteristics, patterns of disease activity and severity, and calendar trends in older adult atopic dermatitis in comparison to other age groups in a large population-based cohort.MethodsThis was a cohort study of 9,154,936 individuals aged 0-99 years registered in The Health Improvement Network, a database comprised of electronic health records from general practices in the United Kingdom between 1994 and 2013. Atopic dermatitis was defined by a previously validated algorithm using a combination of at least one recorded atopic dermatitis diagnostic code in primary care and two atopic dermatitis therapies recorded on separate days. Cross-sectional analyses of disease prevalence were conducted at each age. Logistic mixed effect regression models were used to identify predictors of prevalent disease over time among children (0-17 years), adults (18-74 years), and older adults (75-99 years).ResultsPhysician-diagnosed atopic dermatitis was identified in 894,454 individuals with the following proportions in each age group: 18.3% of children, 7.7% of adults, and 11.6% of older adults. Additionally, atopic dermatitis prevalence increased across the 2-decade period (beta from linear regression test for trend in the change in proportion per year = 0.005, p = 0.044). In older adults, atopic dermatitis was 27% less common among females (adjusted OR 0.73, 95% CI 0.70-0.76) and was more likely to be active (59.7%, 95% CI 59.5-59.9%) and of higher severity (mean annual percentage with moderate and severe disease: 31.8% and 3.0%, respectively) than in other age groups.ConclusionIn a large population-based cohort, the prevalence of physician-diagnosed atopic dermatitis has increased throughout adulthood and was most common amo

BackgroundAtopic dermatitis is known to be common among children, but there are few studies examining the epidemiology across the life course. In particular, there is a paucity of data on atopic dermatitis among older adults.ObjectiveTo evaluate participant characteristics, patterns of disease activity and severity, and calendar trends in older adult atopic dermatitis in comparison to other age groups in a large population-based cohort.MethodsThis was a cohort study of 9,154,936 individuals aged 0-99 years registered in The Health Improvement Network, a database comprised of electronic health records from general practices in the United Kingdom between 1994 and 2013. Atopic dermatitis was defined by a previously validated algorithm using a combination of at least one recorded atopic dermatitis diagnostic code in primary care and two atopic dermatitis therapies recorded on separate days. Cross-sectional analyses of disease prevalence were conducted at each age. Logistic mixed effect regression models were used to identify predictors of prevalent disease over time among children (0-17 years), adults (18-74 years), and older adults (75-99 years).ResultsPhysician-diagnosed atopic dermatitis was identified in 894,454 individuals with the following proportions in each age group: 18.3% of children, 7.7% of adults, and 11.6% of older adults. Additionally, atopic dermatitis prevalence increased across the 2-decade period (beta from linear regression test for trend in the change in proportion per year = 0.005, p = 0.044). In older adults, atopic dermatitis was 27% less common among females (adjusted OR 0.73, 95% CI 0.70-0.76) and was more likely to be active (59.7%, 95% CI 59.5-59.9%) and of higher severity (mean annual percentage with moderate and severe disease: 31.8% and 3.0%, respectively) than in other age groups.ConclusionIn a large population-based cohort, the prevalence of physician-diagnosed atopic dermatitis has increased throughout adulthood and was most common amo

Electronic health records hold great promise for clinical and epidemiologic research. Undertaking atopic eczema (AE) research using such data is challenging because of its episodic and heterogeneous nature. We sought to develop and validate a diagnostic algorithm that identifies AE cases based on codes used for electronic records used in the UK Health Improvement Network. We found that at least one of five diagnosis codes plus two treatment codes for any skin-directed therapy were likely to accurately identify patients with AE. To validate this algorithm, a questionnaire was sent to the physicians of 200 randomly selected children and adults. The primary outcome, positive predictive value for a physician-confirmed diagnosis of AE, was 86% (95% confidence interval = 80-91). Additional criteria increased the PPV up to 95% but would miss up to 89% of individuals with physician-confirmed AE. The first and last entered diagnosis codes for individuals showed good agreement with the physician-confirmed age at onset and last disease activity; the mean difference was 0.8 years (95% confidence interval = -0.3 to 1.9) and -1.3 years (95% confidence interval = -2.5 to -0.1), respectively. A combination of diagnostic and prescription codes can be used to reliably estimate the diagnosis and duration of AE from The Health Improvement Network primary care electronic health records in the UK.

Electronic health records hold great promise for clinical and epidemiologic research. Undertaking atopic eczema (AE) research using such data is challenging because of its episodic and heterogeneous nature. We sought to develop and validate a diagnostic algorithm that identifies AE cases based on codes used for electronic records used in the UK Health Improvement Network. We found that at least one of five diagnosis codes plus two treatment codes for any skin-directed therapy were likely to accurately identify patients with AE. To validate this algorithm, a questionnaire was sent to the physicians of 200 randomly selected children and adults. The primary outcome, positive predictive value for a physician-confirmed diagnosis of AE, was 86% (95% confidence interval = 80-91). Additional criteria increased the PPV up to 95% but would miss up to 89% of individuals with physician-confirmed AE. The first and last entered diagnosis codes for individuals showed good agreement with the physician-confirmed age at onset and last disease activity; the mean difference was 0.8 years (95% confidence interval = -0.3 to 1.9) and -1.3 years (95% confidence interval = -2.5 to -0.1), respectively. A combination of diagnostic and prescription codes can be used to reliably estimate the diagnosis and duration of AE from The Health Improvement Network primary care electronic health records in the UK.