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Medication non-adherence patterns and profiles for patients with incident myocardial infarction: Observations from a
Gregory Y H Lip1, Ash Genaidy2, Bobby Jones3
1Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, UK.
Insights
Many patients with cardiovascular conditions struggle with medication adherence, with over half eligible for interventions. Understanding non-adherence patterns is key to improving cardiovascular health outcomes.
Area of Science:
- Cardiology
- Pharmacology
- Health Services Research
Background:
- Cardiovascular disease patients require consistent medication adherence (≥50%) for long-term management.
- Adherence rates are often lower in specific patient populations.
- This study examined adherence in a large, diverse cohort across various demographics and socioeconomic statuses.
Purpose of the Study:
- To investigate medication adherence patterns in patients with cardiovascular conditions, particularly after myocardial infarction (MI).
- To identify characteristics associated with medication non-adherence.
- To inform the development of interventions for improving adherence.
Main Methods:
- Longitudinal analysis of group-based trajectory modeling was used to examine monthly adherence patterns for up to 12 months post-MI.
- Logistic regression modeling profiled non-adherent patterns based on comorbidities, demographics, and health plan factors.
- Four medication classes for MI were analyzed: beta-blockers, statins, ACE inhibitors, and anti-platelets.
Main Results:
- The study included 1,987,605 participants (MI cohort mean age 62; non-MI cohort mean age 45).
- Medication non-adherence was prevalent, affecting 74%–82% of the MI population.
- Four distinct non-adherence patterns were identified: fast decline, slow decline, occasional users, and early gap with later adherence.
Conclusions:
- Approximately 56% of MI patients exhibited consistent intermediate non-adherence across four key drug classes, indicating eligibility for targeted interventions.
- Identifying patient profiles with specific comorbidities (hypertension, diabetes, stroke) and Medicare enrollment can guide adherence improvement programs.
- These findings support the development of large-scale programs to enhance cardiovascular medication adherence.
Background:
Consistent adherence levels to multiple long-term medications for patients with cardiovascular conditions are typically advocated in the range of 50% or higher, although very likely to be much lower in some populations. We investigated this issue in a large cohort covering a broad age and geographical spectrum, with a wide range of socio-economic disability status.
Methods:
The patients were drawn from three different health plans with a varied mix of socio-economic/disability levels. Adherence patterns were examined on a monthly basis for up to 12 months past the index date for myocardial infarction (MI) using longitudinal analyses of group-based trajectory modelling. Each of the non-adherent patterns was profiled from comorbid history, demographic and health plan factors using main effect logistic regression modelling. Four medication classes were examined for MI: betablockers, statin, ACE inhibitors and anti-platelets.
Results:
The participant population for the MI/non-MI cohorts was 1,987,605 (MI cohort: mean age 62 years, 45.9% female; non-MI cohort: mean age 45 years, 55.3% females). Cohorts characterized by medication non-adherence dominated the majority of MI population with values ranging from 74% to 82%. There were four types of consistent non-adherence patterns as a function of time for each medication class: fast decline, slow decline, occasional users and early gap followed by increased adherence. The characteristics of non-adherence profiles eligible for improvement included patients with a prior history of hypertension, diabetes mellitus and stroke as co-morbidities, and Medicare plan.
Conclusions:
We found consistent patterns of intermediate non-adherence for each of four drug classes for MI cohorts in the order of 56% who are eligible for interventions aimed at improving cardiovascular medication adherence levels. These insights may help improve cardiovascular medication adherence using large medication non-adherence improvement programs.
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