Abstract
BackgroundThe proportion of days covered (PDC) is used to estimate medication adherence by looking at the proportion of days in which a person has access to the medication, over a given period of interest. This study aimed to adapt the PDC algorithm to allow for plausible assumptions about prescription refill behaviour when applied to data from online pharmacy suppliers.MethodsThree PDC algorithms, the conventional approach (PDC1) and two alternative approaches (PDC2 and PDC3), were used to estimate adherence in a real-world dataset from an online pharmacy. Each algorithm has different denominators and increasing levels of complexity. PDC1, the conventional approach, is the total number of days between first dispensation and a defined end date. PDC2 counts the days until the end of supply date. PDC3 removes from the denominator specifically defined large gaps between refills, which could indicate legitimate reasons for treatment discontinuation. The distribution of the three PDCs across four different follow-up lengths was compared.ResultsThe dataset included people taking ACE inhibitors (n = 65,905), statins (n = 100,362), and/or thyroid hormones (n = 30,637). The proportion of people taking ACE inhibitors with PDC ≥ 0.8 was 50–74% for PDC1, 81–91% for PDC2, and 86–100% for PDC3 with values depending on drug and length of follow-up. Similar ranges were identified in people taking statins and thyroid hormones.ConclusionThese algorithms enable researchers and healthcare providers to assess pharmacy services and individual levels of adherence in real-world databases, particularly in settings where people may switch between different suppliers of medicines, meaning an individual supplier’s data may show temporary but legitimate gaps in access to medication. Accurately identifying problems with adherence provides the foundation for opportunities to improve experience, adherence and outcomes and to reduce medicines wastage. Research with people taking medications and prescribers is required to validate the algorithms’ assumptions.
Highlights
The proportion of days covered (PDC) is used to estimate medication adherence by looking at the proportion of days in which a person has access to the medication, over a given period of interest
The resulting P2U database consisted of 65,905 people in the United Kingdom (UK) with prescriptions for angiotensin-converting enzyme (ACE) inhibitors, 100,362 for statins and 30,637 for thyroid hormones with prescriptions dispatched in the target timeframe
In all three drug classes, there are substantially more individuals with a low PDC1 than there are with low PDC2 or PDC3
Summary
The proportion of days covered (PDC) is used to estimate medication adherence by looking at the proportion of days in which a person has access to the medication, over a given period of interest. Adherence is understood as involving several distinct, quantifiable behaviours: initiation is when the person takes the first dose of prescribed medication (this may be the same or different to the prescription date); implementation is the degree to which the person’s intake of medication corresponds to the prescription, from initiation until the last dose taken; discontinuation is the term given to the time at which the person has taken their last dose and no further doses are taken and persistence is the duration of time between the first and last dose taken (from implementation to discontinuation) [6] This relatively new taxonomy of adherence (the ABC taxonomy) can help researchers and healthcare professionals to better understand, interpret and support medicine-related behaviour. It provides a rationale for refining measures of adherence, for example by specifying which type of adherence behaviour (e.g. implementation or persistence) is being measured
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