Abstract
Asthma is a common chronic lung disease. National guidelines encourage a stepwise approach to pharmacotherapy, and as such, an individual’s current treatment step can be considered as a severity categorization proxy. BTS/SIGN steps can be estimated from electronic prescription records, however substantial data processing is required including extracting information from free-text drug descriptions and dose instructions. Almost 4.5 million asthma controller inhalers were prescribed for people in the Asthma Learning Health System (ALHS) Scottish cohort between 2009 and 2017. Asthma treatment regimens were identified and categorized by the combination of medications prescribed in the 120 days preceding prescribing events. 26% of prescriptions had no primary controller (inhaled corticosteroid) prescriptions in the previous 120 days and were thus assigned Step 0. 16% of prescriptions were assigned to BTS/SIGN Step 1, 7% to Step 2, 21% to Step 3, and 30% to Step 4. We developed a robust methodology enabling researchers to easily replicate BTS/SIGN asthma treatment step estimates, to both describe the severity of asthma in a population and to demonstrate changes over time. This can provide valuable insights into population and patient-specific trajectories, to improve understanding and management of symptoms.
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