Novel Approaches for Visualizing and Analyzing Dose-Timing Data from Electronic Drug Monitors, or “How the ‘Broken Window’ Theory Pertains to ART Adherence”

Abstract

Adherence to antiretroviral medications is usually expressed in terms of the proportion of doses taken. However, the timing of doses taken may also be an important dimension to overall adherence. Little is known about whether patients who mistime doses are also more likely to skip doses. Using data from the completed Adherence for Life randomized controlled trial, we created visual and statistical models to capture and analyze dose timing data collected longitudinally with electronic drug monitors (EDM). From scatter plots depicting dose time versus calendar date, we identified dominant patterns of dose taking and calculated key features [slope of line over calendar date; residual mean standard error (RMSE)]. Each was assessed for its ability to categorize subjects with ‘sub-optimal’ (<95 % of doses taken) using area under the receiver operating characteristic (AROC) curve analysis. Sixty eight subjects contributed EDM data, with ~300 to 400 observations/subject. While regression line slopes did not predict ‘sub-optimal’ adherence (AROC 0.51, 95 % CI 0.26–0.75), the variability in dose timing (RMSE) was strongly predictive (AROC 0.79, 95 % CI 0.62–0.97). Compared with the lowest quartile of RMSE (minimal dose time variability), each successive quartile roughly doubled the odds of ‘sub-optimal’ adherence (OR 2.1, 95 % CI 1.3–3.4). Patterns of dose timing and mistiming are strongly related to overall adherence behavior. Notably, individuals who skip doses are more likely to mistime doses, with the degree of risk positively correlated with the extent of dose timing variability.