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Regional variation in prevalence of difficult-to-treat asthma and oral corticosteroid use for patients in Australia: heat map analysis

机译:Regional variation in prevalence of difficult-to-treat asthma and oral corticosteroid use for patients in Australia: heat map analysis

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Background In Australia, the regional prevalence of difficult-to-treat asthma is unknown. We aimed to describe regional variation in difficult-to-treat asthma prevalence and oral corticosteroid (OCS) use. Methods In this retrospective, observational, longitudinal study using data from March 2018-February 2019 in the NostraData longitudinal database, prescriptions dispensed for obstructive airway disease were processed through a high-level algorithm to identify patients with asthma. Difficult-to-treat asthma was defined by >= 2 high-dosage inhaled corticosteroids plus long-acting beta-agonist prescriptions over 6 months. Patients who additionally received OCS prescriptions sufficient to treat >= 2 exacerbations over 6 months were classified as having uncontrolled difficult-to-treat asthma. Patient-level data were analyzed across 340 geographic areas in Australia to determine regional prevalence of difficult-to-treat asthma, uncontrolled difficult-to-treat asthma, and OCS use. Results Of 1 851 129 people defined as having asthma, 440 800 (24) were classified as having difficult-to-treat disease. Of those difficult-to-treat asthma patients, 96 338 (22) were considered to have uncontrolled disease. Between 29 and 48 of patients had difficult-to-treat asthma in 49 geographic areas, most frequently located in Western Australia. Between 26 and 67 of patients had uncontrolled difficult-to-treat asthma in 29 geographic areas (mostly in Eastern Australia). Overall, a wide variability of asthma severity and control was observed among regions. Conclusions Despite global and national guidelines, regional differences in the prevalence of difficult-to-treat asthma and uncontrolled difficult-to-treat asthma and OCS use exist in Australia. Understanding these regional variations should inform policy and target management in the areas with the greatest unmet need.

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