Resumo: | Background: Previous studies have demonstrated the feasibility of using an asthma app to support medication management and adherence but failed to compare with other measures currently used in clinical practice. However, in a clinical setting any additional adherence measurement must be evaluated in the context of both the patient and physician perspectives so that it can also help in improving the process of shared decision making. Thus, we aimed to compare different measures of adherence to asthma control inhalers in clinical practice, namely through an app, patient self-report and physician assessment. Methods: This study is a secondary analysis of three prospective multicentre observational studies with patients (≥13 years old) with persistent asthma recruited from 61 primary and secondary care centres in Portugal. Patients were invited to use the InspirerMundi app and register their inhaled medication. Adherence was measured by the app as the number of doses taken divided by the number of doses scheduled each day and was assessed at two time points: 1-week (1wk) and 1-month (1mo). At baseline, patients and physicians independently assessed adherence to asthma control inhalers during the previous week using a Visual Analogue Scale (VAS 0-100). Results: A total of 193 patients with asthma (72% female; Median [P25-P75] age 28[19-41] years old) were included in the analysis. Adherence measured by the app was lower (1wk: 31[0-71]%; 1mo: 18[0-48]%) than patient self-report (80[60-95]) and physician assessment (82[51-94]) (p<0.001). A negligible non-significant correlation was found between the app and subjective measurements (rho 0.118 to 0.156, p>0.05). There was a moderate correlation between patient self-report and physician assessment (rho=0.596, p<0.001). Conclusions: Adherence measured by the app was significantly lower than that reported by the patient or the physician, and similar to other objective methods reported in a recent meta-analysis. This low adherence may be due to the influence of adherence to the app itself and thus, this factor needs to be considered in future analysis.
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