Medication Adherence in Chronic Disease Management

Medication adherence—the extent to which patients take medications as prescribed—is a cornerstone of effective chronic disease management. Non-adherence undermines therapeutic benefit, contributes to avoidable morbidity and mortality, and imposes substantial economic burdens on healthcare systems worldwide. Adherence comprises three phases: initiation (starting treatment), implementation (correct dosing and timing) and persistence (continuing therapy for the prescribed duration). Its determination is multifactorial, spanning patient-related factors (beliefs, health literacy, self-efficacy), therapy-related factors (regimen complexity, adverse effects), condition-related factors (symptom burden, comorbidities), healthcare system factors (access, clinician–patient communication) and socio-economic factors (education, income, social support). Measurement strategies vary from direct methods such as drug assays and electronic monitoring devices to indirect methods including pharmacy refill records and validated self-report scales. Multifaceted interventions—ranging from regimen simplification and fixed-dose combinations to digital reminders and personalised behavioural support—have been shown to improve adherence, yet sustained benefit often requires tailored approaches that account for individual patient contexts and barriers.

Research from Nature Portfolio

Large-scale registry analyses leveraging nationwide health and genomic data have quantified the impact of socio-demographic factors on adherence and persistence across multiple chronic medication classes. Findings indicate that indicators of social disadvantage—such as reliance on social assistance programmes and immigrant status—are strongly associated with lower long-term adherence, whereas genetic variants play a comparatively modest role. These insights highlight the need for targeted outreach and dispensing models that address economic and structural barriers to sustained therapy in vulnerable populations.

Medication Adherence in Chronic Disease Management publication trend

The graph below shows the total number of articles in medication adherence in chronic disease management across all publications each year (not limited to Nature Index journals).

Technical terms

Medication adherence: The extent to which patients follow prescribed medication regimens in terms of timing, dosage and frequency.

Initiation, implementation and persistence: Distinct phases of adherence referring to starting therapy, correctly taking medications, and maintaining treatment over time, respectively.

Reinforcement learning: A machine-learning approach in which algorithms iteratively adjust interventions based on individual behavioural responses to optimise outcomes.

Necessity-Concerns Framework: A theoretical model positing that patients’ adherence decisions are governed by their perceived personal need for treatment (necessity beliefs) weighed against concerns about potential adverse effects.

Self-efficacy: An individual’s confidence in their ability to perform behaviours necessary to achieve desired health outcomes, such as taking medications as prescribed.

Health locus of control: A psychological construct describing the degree to which individuals believe that control over their health lies internally (within themselves) or externally (with healthcare providers, fate or chance).

References

1. Medication Adherence Measures: An Overview. BioMed Research International (2015).
2. Socio-demographic and genetic risk factors for drug adherence and persistence across 5 common medication classes. Nature Communications (2024).
3. The impact of using reinforcement learning to personalize communication on medication adherence: findings from the REINFORCE trial. npj Digital Medicine (2024).
4. Factors Contributing to Medication Adherence in Patients with a Chronic Condition: A Scoping Review of Qualitative Research. Pharmaceutics (2021).
5. Understanding Patients’ Adherence-Related Beliefs about Medicines Prescribed for Long-Term Conditions: A Meta-Analytic Review of the Necessity-Concerns Framework. PLOS ONE (2013).