BACKGROUND: Psoriasis is a common disease frequently studied in large databases. To date the validity of psoriasis information has not been established in The Health Improvement Network (THIN). OBJECTIVES: To investigate the validity of THIN for identifying patients with psoriasis and to determine if the database can be used to determine the natural history of the disease. METHODS: First, we conducted a cross-sectional study to determine if psoriasis prevalence in THIN is similar to expected. Second, we created a cohort of 4900 patients, aged 45-64 years, with a psoriasis diagnostic Read Code and surveyed their general practitioners (GPs) to confirm the diagnosis clinically. Third, we created models to determine if psoriasis descriptors (extent, severity, duration and dermatologist confirmation) could be accurately captured from database records. RESULTS: Psoriasis prevalence was 1·9%, and showed the characteristic age distribution expected. GP questionnaires were received for 4634 of 4900 cohort patients (95% response rate), and psoriasis diagnoses were confirmed in 90% of patients. Duration of disease in the database showed substantial agreement with physician query (κ = 0·69). GPs confirmed that the psoriasis diagnosis was corroborated by a dermatologist in 91% of patients whose database records contained a dermatology referral code associated with a psoriasis code. We achieved good discrimination between patients with and without extensive disease based on the number of psoriasis codes received per year (area under curve = 0·8). CONCLUSIONS: THIN is a valid data resource for studying psoriasis and can be used to identify characteristics of the disease such as duration and confirmation by a dermatologist.
BACKGROUND:Psoriasis is a common disease frequently studied in large databases. To date the validity of psoriasis information has not been established in The Health Improvement Network (THIN). OBJECTIVES: To investigate the validity of THIN for identifying patients with psoriasis and to determine if the database can be used to determine the natural history of the disease. METHODS: First, we conducted a cross-sectional study to determine if psoriasis prevalence in THIN is similar to expected. Second, we created a cohort of 4900 patients, aged 45-64 years, with a psoriasis diagnostic Read Code and surveyed their general practitioners (GPs) to confirm the diagnosis clinically. Third, we created models to determine if psoriasis descriptors (extent, severity, duration and dermatologist confirmation) could be accurately captured from database records. RESULTS:Psoriasis prevalence was 1·9%, and showed the characteristic age distribution expected. GP questionnaires were received for 4634 of 4900 cohort patients (95% response rate), and psoriasis diagnoses were confirmed in 90% of patients. Duration of disease in the database showed substantial agreement with physician query (κ = 0·69). GPs confirmed that the psoriasis diagnosis was corroborated by a dermatologist in 91% of patients whose database records contained a dermatology referral code associated with a psoriasis code. We achieved good discrimination between patients with and without extensive disease based on the number of psoriasis codes received per year (area under curve = 0·8). CONCLUSIONS: THIN is a valid data resource for studying psoriasis and can be used to identify characteristics of the disease such as duration and confirmation by a dermatologist.
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