Electronic Inhaler Monitoring for Chronic Airway Disease: Development and Application of a Multidimensional Efficacy Framework

Abstract

Inhaled therapy is the cornerstone of chronic airway disease therapy, but poor adherence to controller inhalers worsens clinical outcomes and increases cost. Monitoring of controller use is needed to improve adherence, and monitoring of reliever use can predict impending exacerbations. Both can be accurately achieved by electronic inhaler monitoring (EIM). However, evidence for EIM use in clinical practice is limited and varied, and knowledge gaps remain across different outcomes and health settings. We aimed to develop a framework to assess EIM systematically across all aspects of efficacy, apply this framework to the current literature, and identify gaps in efficacy to inform future development in the field. We adapted an existing framework for diagnostic tests, consisting of six levels of efficacy with ascending clinical relevance: technical, diagnostic accuracy, diagnostic thinking, therapeutic, patient outcome, and societal efficacy. Tailoring this framework to EIM, we incorporated expert feedback and applied it to the EIM efficacy literature. We found that EIM has good diagnostic accuracy, diagnostic thinking, and therapeutic efficacies, but evidence is lacking for specific aspects of technical, patient outcome, and societal efficacies. Further development of EIM requires improved reliability, usability, and data security for patients, and optimal integration with electronic medical records and overall patient care. Defining appropriate target patient groups and pairing EIM data with effective interventions, in conjunction with reducing costs through technological innovation and economies of scale, will enhance patient and societal outcome efficacies.

Keywords: Adherence; Asthma; COPD; Digital health; Dose count; Inhaler.