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AIDS Care
Psychological and Socio-medical Aspects of AIDS/HIV
Volume 35, 2023 - Issue 7
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Research Article

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

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 970-975 | Received 28 Oct 2021, Accepted 01 Mar 2022, Published online: 17 Mar 2022

Figures & data

Box 1. Definitions for different methods to estimate adherence to multiple antiretrovirals.

Table 1. Descriptive statistics of the measures of adherence estimated from pharmacy dispensing claims (N = 2,042).

Table 2. Descriptive statistics of the measures of adherence estimated from pharmacy dispensing claims according to antiretroviral regimen in their first dispensing (N = 2,042).

Figure 1. Example of results provided in the three tabs of the web application to visualise patterns of medicine use and adherence estimates at the individual and populational level (Interactive tool available at https://adherencehiv.shinyapps.io/Application). A: Patterns of medicine use by patient ID: This tab enables identifying gaps in refills, changes in treatment and the results for adherence calculations for individual people based on each measure (Example for Patient ID 1). B: Cohort adherence results by different measures: This tab allows evaluating the impact of each measure and the implemented scenario on adherence estimates for the entire cohort. The tool also shows the absolute number of people identified as non-adherents to assist in selecting the appropriate measure (Example for base case scenario). C: Cohort adherence results by measure used and selected characteristics: This tab presents adherence results stratified by selected characteristics at index date according to each measure (Example for regimen type).

Figure 1. Example of results provided in the three tabs of the web application to visualise patterns of medicine use and adherence estimates at the individual and populational level (Interactive tool available at https://adherencehiv.shinyapps.io/Application). A: Patterns of medicine use by patient ID: This tab enables identifying gaps in refills, changes in treatment and the results for adherence calculations for individual people based on each measure (Example for Patient ID 1). B: Cohort adherence results by different measures: This tab allows evaluating the impact of each measure and the implemented scenario on adherence estimates for the entire cohort. The tool also shows the absolute number of people identified as non-adherents to assist in selecting the appropriate measure (Example for base case scenario). C: Cohort adherence results by measure used and selected characteristics: This tab presents adherence results stratified by selected characteristics at index date according to each measure (Example for regimen type).