Assessing the impact of implementing multiple adherence measures to antiretroviral therapy from dispensing data: a short report

• Published in: AIDS care Vol. 35; no. 7; pp. 970 - 975
• Main Authors: de Oliveira Costa, Juliana, Zhao, Yalin, Pearson, Sallie-Anne, Schaffer, Andrea L.
• Format: Journal Article
• Language: English
• Published: England Taylor & Francis 03.07.2023; Taylor & Francis Ltd
• Subjects: Adherence; Anti-Retroviral Agents - therapeutic use; Antiretroviral agents; Antiretroviral drugs; Antiretroviral therapy; Antiviral agents; Cohort analysis; Cohort Studies; Dispensing; Drug therapy; Estimates; highly active; HIV; HIV Infections - drug therapy; Humans; Medication Adherence; Patient compliance; Pharmaceutical Services; Pharmacies; Pharmacy; Pharmacy dispensing data; Retrospective Studies; Sensitivity analysis; Therapy; treatment adherence and compliance; highly active; Pharmacy dispensing data; treatment adherence and compliance; HIV; Antiretroviral therapy
• ISSN: 0954-0121; 1360-0451
• DOI: 10.1080/09540121.2022.2050179

Pharmacy dispensing data are useful for estimating adherence to therapy. Here, we implement multiple adherence measures to antiretroviral therapy (ART) and provide an online tool for visualising results. We conducted a cohort study for 2,042 people dispensed ART in Australia. We assessed adherence using the Proportion of Days Covered (PDC) within 360 days of follow-up as a continuous measure and dichotomised (PDC ≥80%). We defined a covered day as the 1) exposure to ≥3 antiretrovirals at the same time 2) exposure to any antiretroviral 3) lowest number of days covered per antiretroviral 4) average of days covered over all antiretrovirals 5) highest number of days covered per antiretroviral. For each method, we conducted sensitivity analyses. The median PDC ranged between 93.3%−98.3%. Between 67.0%−87.7% of individuals were classified as adherent, with higher values for measure 2 (85.5%−89.7%) and lower values for measure 3 (67.0%−70.9%). Censoring loss to follow-up had a higher impact on adherence estimates than considering a grace period. The variation in adherence estimates can be substantial, especially when dichotomising adherence. Researchers should consider operationalising multiple measures to estimate adherence bounds and identify a range of people at risk of non-adherence for targeted interventions.