Heterogeneity in Asthma Medication Adherence Measurement Medication nonadherence is strongly associated with poor asthma control and outcomes. Many studies use an aggregate measure of adherence, such as the percentage of prescribed doses that were taken, however this conceals variation between patientsu0027 medicationtaking routines. Electronic monitoring devices, which precisely record the date and time of a dose being actuated from an inhaler, provide the means to objectively and remotely monitor adherence behavior patterns. This secondary analysis of a New Zealand audiovisual medication reminder intervention study visually explored the relationships, variation, and heterogeneity between multiple measures of adherence, in 211 children aged 615 years old who presented to an emergency department with an asthma attack. Our findings highlight the weakness of statistical relationships between measures of adherence, and the irregularity in patient medicationtaking behavior. This demonstrates that a single aggregate adherence measure fails to detect asthma patients for whom their daytoday medication taking (implementation) is inconsistent with their longitudinal medication taking (persistence).

Pitfalls of medication adherence approximation through EHR and pharmacy records: Definitions, data and computation Abstract   Background and purpose  Patientsxe2x80x99 adherence to medication is a complex, multidimensional phenomenon. Dispensation data and electronic health records are used to approximate medicationtaking through refill adherence. Indepth discussions on the adverse effects of data quality and computational differences are rare. The purpose of this article is to evaluate the impact of common pitfalls when computing medication adherence using electronic health records.    Procedures  We point out common pitfalls associated with the data and operationalization of adherence measures. We provide operational definitions of refill adherence and conduct experiments to determine the effect of the pitfalls on adherence estimations. We performed statistical significance testing on the impact of common pitfalls using a baseline scenario as reference.    Findings  Slight changes in definition can significantly skew refill adherence estimates. Pickup patterns cause significant disagreement between measures and the commonly used proportion of days covered. Common data related issues had a small but statistically significant (pxe2x80xaf    Conclusion  Datarelated issues encountered in realworld administrative databases, which affect various operational definitions of refill adherence differently, can significantly skew refill adherence values, leading to false conclusions about adherence, particularly when estimating adherence for individuals.