Cargando…

Towards tailored and targeted adherence assessment to optimise asthma management

In this paper, we aim to emphasise the need for a more comprehensive and tailored approach to manage the broad nature of non-adherence, to personalise current asthma management. Although currently several methods are available to measure the extent of asthma patients’ adherence, the vast majority do...

Descripción completa

Detalles Bibliográficos
Autores principales: van Boven, Job FM, Trappenburg, Jaap CA, van der Molen, Thys, Chavannes, Niels H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4588030/
https://www.ncbi.nlm.nih.gov/pubmed/26181850
http://dx.doi.org/10.1038/npjpcrm.2015.46
Descripción
Sumario:In this paper, we aim to emphasise the need for a more comprehensive and tailored approach to manage the broad nature of non-adherence, to personalise current asthma management. Although currently several methods are available to measure the extent of asthma patients’ adherence, the vast majority do not incorporate confirmation of the actual inhalation, dose and inhalation technique. Moreover, most current measures lack detailed information on the individual consequences of non-adherence and on when and how to take action if non-adherence is identified. Notably, one has to realise there are several forms of non-adherence (erratic non-adherence, intelligent non-adherence and unwitting non-adherence), each requiring a different approach. To improve asthma management, more accurate methods are needed that integrate measures of non-adherence, asthma disease control and patient preferences. Integrating information from the latest inhaler devices and patient-reported outcomes using mobile monitoring- and feedback systems (‘mHealth’) is considered a promising strategy, but requires careful implementation. Key issues to be considered before large-scale implementation include patient preferences, large heterogeneity in patient and disease characteristics, economic consequences, and long-term persistence with new digital technologies.