ObjectivesOveruse of asthma relievers is associated with significant adverse consequences. This study aimed to better understand the population purchasing and using short-acting beta agonists (SABA) over the counter (OTC); and compare the demographic, clinical and behavioural characteristics of those who overuse SABA with those who do not.Design and settingReal-world cross-sectional observational study in community pharmacy.ParticipantsOf 412 participants ≥16 years requesting SABA OTC, 289 were SABA overusers (used SABA more than twice per week in the past 4 weeks).Main outcome measureReliever use, Global Initiative for Asthma-defined control, healthcare utilisation, patterns of preventer use.Results70.1% of participants were classified as SABA overusers, that is, reporting SABA use more than twice a week within the last 4 weeks, 73.6% reported not using a preventer daily and only 81.6% reported a doctor diagnosis of asthma. SABA overusers were more likely to have moderate-severe nasal symptoms (80.8% vs 63.0%, p<0.001) and a diagnosis of depression (11.1% vs 5.7%, p<0.001), when compared with SABA non-overusers. A higher proportion of SABA overusers had uncontrolled asthma (59.0% vs 15.4%, p<0.001), were more likely to use oral corticosteroids to manage worsening asthma symptoms (26.2% vs 13.5%, p<0.01) and visit the doctor for their asthma in the past 12 months (74.5% vs 62.5%, p<0.01), when compared to SABA non-overusers.ConclusionsThis study uncovers a hidden population of people who can only be identified in pharmacy with suboptimal asthma, coexisting rhinitis, poor preventer adherence and, in some cases, no asthma diagnosis.
Allergic rhinitis (AR) is increasingly becoming a patient self-managed disease. Just under 70% of patients purchasing pharmacotherapy self-select their treatment with no health-care professional intervention often resulting in poor choices, leading to suboptimal management and increased burden of AR on the individual and the community. However, no decision is made without external, influencing forces. This study aims to determine the key influences driving patients’ decision-making around AR management. To accomplish this aim, we utilised a social network theory framework to map the patient’s AR network and identify the strength of the influences within this network. Adults who reported having AR were interviewed and completed an AR network map and AR severity and quality of life questionnaires. Forty one people with AR completed the study. The AR networks of the participants had a range of 1–11 influences (alters), with an average number of 4 and a median of 5. The larger the impact of AR on their quality of life, the greater the number of alters within their network. The three most commonly identified alters were, general practitioners, pharmacists and the participants’ ‘own experience’. The strength of the influence of health-care professionals (HCPs) was varied. The proportion of HCPs within the AR network increased as the impact of AR on their quality of life increased. By mapping the AR network, this study demonstrated that there are multiple influences behind patient’s decisions regarding AR management but the role of the HCP cannot be dismissed.
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