Objective: To assess suitability and comparability of the most common methods of treatment adherence and persistence assessment, as applied to the same pharmacy dataset. Methods: Data on drugs prescribed for cardiovascular primary prevention to participants in the Aragon Workers’ Health Study (AWHS) were collected from a regional electronic drug prescription database. Several different approaches were used to measure treatment adherence (with the medication possession ratio [MPR]) and proportion of days covered [PDC]) and persistence in new users by therapeutic subgroup. Defined daily dose (DDD) was used as a proxy of the number of days’ supply, or substituted with surrogate daily dose values. Results: Higher mean adherence values and proportions of adherent patients were obtained using MPR versus PDC, with additional differences depending on the approach used. The proportion of adherent patients was lowest for oral antidiabetics (14.4%–30.6%) and highest for antihypertensives (70.2%–82.1%). The use of surrogate daily dose values increased adherence for antidiabetics and statins and decreased adherence for antihypertensives. After a 1 year follow-up, treatment persistence was observed for 21.1%, 58.7%, and 29.5% of antidiabetic, antihypertensive and statin users, respectively. Conclusions: Our findings indicate that use of multiple measures of treatment adherence and persistence provides a more complete overview of medication use patterns, and certain limitations associated with DDD for some drug groups can be overcome with replacement by surrogate doses. The PDC indicator seems to provide a more accurate reflection of patient behavior and treatment continuity than the MPR. Any comparison of adherence/persistence should always consider the method used, variables analyzed, and corresponding data collection process.

Medication adherence is a priority for health systems worldwide and is widely recognised as a key component of quality of care for disease management. Adherence-related indicators were rarely explicitly included in national health policy agendas. One barrier is the lack of standardised adherence terminology and of routine measures of adherence in clinical practice. This paper discusses the possibility of developing adherence-related performance indicators highlighting the value of measuring persistence as a robust indicator of quality of care. To standardise adherence and persistence-related terminology allowing for benchmarking of adherence strategies, the European Ascertaining Barriers for Compliance (ABC) project proposed a Taxonomy of Adherence in 2012 consisting of three components: initiation, implementation, discontinuation. Persistence, which immediately precedes discontinuation, is a key element of taxonomy, which could capture adherence chronology allowing the examination of patterns of medication-taking behaviour. Advances in eHealth and Information Communication Technology (ICT) could play a major role in providing necessary structures to develop persistence indicators. We propose measuring persistence as an informative and pragmatic measure of medication-taking behaviour. Our view is to develop quality and performance indicators of persistence, which requires investing in ICT solutions enabling healthcare providers to review complete information on patients’ medication-taking patterns, as well as clinical and health outcomes.

It is essential to understand the impact of social inequalities on the risk of COVID-19 infection in order to mitigate the social consequences of the pandemic. With this aim, the objective of our study was to analyze the effect of socioeconomic inequalities, both at the individual and area of residence levels, on the probability of COVID-19 confirmed infection, and its variations across three pandemic waves. We conducted a retrospective cohort study and included data from all individuals tested for COVID-19 during the three waves of the pandemic, from March to December 2020 (357,989 individuals) in Aragón (Spain). We studied the effect of inequalities on the risk of having a COVID-19 confirmed diagnosis after being tested using multilevel analyses with two levels of aggregation: individuals and basic healthcare area of residence (deprivation level and type of zone). Inequalities in the risk of COVID-19 confirmed infection were observed at both the individual and area level. There was a predominance of low-paid employees living in deprived areas. Workers with low salaries, unemployed and people on minimum integration income or who no longer receive the unemployment allowance, had a higher probability of COVID-19 infection than workers with salaries ≥ €18,000 per year. Inequalities were greater in women and in the second wave. The deprivation level of areas of residence influenced the risk of COVID-19 infection, especially in the second wave. It is necessary to develop individual and area coordinated measures by areas in the control, diagnosis and treatment of the epidemic, in order to avoid an increase in the already existing inequalities.

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