Novel technology and analysis techniques for monitoring COPD treatment adherence using the Inhaler Compliance Aid

Abstract

Background Assessing adherence to treatment regimens is a perennial problem in the management of chronic illnesses. Non-adherence can include over- or under-dosing, incorrect timing of doses or failure to correctly operate a medical device. The problem is particularly prevalent in the case of inhaled medications, where improper inhaler technique routinely leads to under-dosing. The recently-developed INCA (Inhaler Compliance Aid) device records precise timing of inhaler use and, uniquely, can identify with >90% sensitivity errors in inhalation technique. The INCA output therefore consists of both time-series (dose timing) and failure-event data, and thus demands novel analysis techniques combining time-series and survival/frailty models. Methods The current project encompasses three strands: An observational study of established, theory-informed psychosocial predictors of adherence in COPD patients (e.g. depression, beliefs about medicine and illness, etc.). Observational data will be acquired from COPD patients using salmeterol/fluticasone dry powder inhalers fitted with the INCA device. Development of novel statistical measures and techniques for the analysis of adherence data, combining time-series and frailty analyses. Establishment of an international consortium to apply for H2020 (Health) funding. Expected Results Determination of patterns and predictors of adherence, derivation of novel statistical techniques to exploit the rich structure of INCA data, and development of accompanying specialist tools such as Stata and R software modules. Discussion The INCA device presents excellent opportunities to develop adherence research and novel analysis to fully exploit complex data. The current work programme also provides an opportunity for international collaboration within the H2020 (Health) framework. Funding: Irish Research Council