Routine health data describe adherence and persistence patterns for oral diabetes medication for a virtual cohort in the Khayelitsha sub-district of Cape Town, South Africa

Abstract

Type 2 diabetes mellitus (T2DM) is managed with combined lifestyle modifications and antidiabetic drugs, but people on treatment often fail to reach glycaemic control. Adherence is important for achieving optimal glycaemic control, and management of diabetes with drugs is a lifelong process, so understanding adherence through analysis of longitudinal medications data is important. Using retrospective routine health data and metformin dispensing records as a proxy for medication use, we describe longitudinal persistence and adherence to oral diabetes medication in a virtual cohort of 10541 people with diabetes (PLWD) in Khayelitsha subdistrict, Cape Town. Adherence was measured in 120-day sliding windows over two years and used to estimate metformin adherence trajectories. Multinomial logistic regression identified factors influencing these trajectories. Analysis of pharmacy dispensing records showed varying medication refill patterns: while some PLWD refilled prescriptions consistently, others had treatment gaps with periods of non-persistence and multiple treatment episodes–from one to five per individual across two years. There was a general trend of decreasing adherence over time across all sliding windows in the two-year period, with only 25% of the study population achieved medication adherence (> = 80% adherence) after two years. Four adherence trajectories; ‘low adherence gradual decline (A), ‘high adherence rapid decline’ (B), ‘low adherence gradual increase (C) and ‘adherent’ (D) were identified. Only trajectory D represented participants who were adherent at treatment start and remained adherent after two years. Taking HIV antiretroviral treatment before or concurrently with diabetes treatment and taking metformin in combination with sulphonylurea and/or insulin were associated with the long-term adherence (trajectory D). Routine data shows real life medication implementation patterns which might not be seen under controlled study conditions. This study illustrates the utility of these data in describing longitudinal adherence patterns at both an individual and population level.