Medication Refill Adherence and Its Predictors in Hypertensive Patients: Insights from E-Prescribing System in Malaysian Community Pharmacies

Technical Summary: Medication Refill Adherence and Its Predictors in Hypertensive Patients

Problem Statement
Non-adherence to antihypertensive medications (AHM) is a critical public health issue, linked to increased morbidity, mortality, and unnecessary healthcare expenditures. While global prevalence of non-adherence is estimated at approximately 45%, Malaysian studies indicate rates between 39.3% and 57%. Although electronic prescribing (e-prescribing) systems have been introduced in Malaysia (initially around 2016 and widely adopted post-2020) to improve accessibility and efficiency, their specific impact on patient medication adherence remains under-explored in the local context. There is a lack of comprehensive data regarding how patient demographics, medication-related factors, and healthcare system variables (including e-prescribing platform satisfaction) interact to influence refill behaviors and adherence levels among hypertensive patients in community pharmacy settings.

Methodology
The study employed a retrospective observational design conducted at a chain community pharmacy in Kelantan, Malaysia.

• Data Source: Dispensation data from January 1, 2023, to December 31, 2023, were extracted from the pharmacy's Point of Sales (PoS) system and matched with electronic prescriptions issued via the "Doc2us" platform.
• Study Population: The cohort consisted of 200 adult patients (aged ≥30) diagnosed with mild to moderate essential hypertension. Inclusion criteria required patients to have received four consecutive electronic prescriptions for the same medication with gaps of less than 30 days. Exclusion criteria included patients with terminal illnesses, neurological disabilities, or missing prescription data.
• Adherence Measurement: Medication adherence was quantified using the Proportion of Days Covered (PDC). Patients were categorized into two groups: adherent (PDC ≥ 80%) and non-adherent (PDC < 80%).
• Data Collection: Eligible participants were contacted via phone or text to participate in a survey. A structured questionnaire, validated through a pilot study, assessed patient-related factors (demographics, income, education, family history), medication-related factors (therapy type, cost perception), and system-related factors (clinic waiting times, e-prescribing satisfaction).
• Statistical Analysis: The study utilized univariate analysis and binary logistic regression (Simple and Multiple) to identify predictors of adherence. The Health Belief Model (HBM) was applied to interpret the relationship between perceived barriers and benefits.

Key Contributions

• Empirical Evidence on E-Prescribing in Malaysia: This study provides one of the first localized analyses of medication refill patterns specifically within the context of the Doc2us e-prescribing platform in community pharmacies.
• Identification of Primary Barriers: The research isolates "perceived financial burden" as the most significant predictor of non-adherence, surpassing technological usability or satisfaction metrics.
• Integration of HBM with Digital Health: The study applies the Health Belief Model to digital health contexts, demonstrating that in this specific demographic, perceived economic barriers outweigh the perceived benefits of system convenience.
• Granular Refill Data: By analyzing 2023 dispensation records, the study offers a detailed breakdown of adherence rates across different therapy types (monotherapy, Single Pill Combinations, and Free Combinations) and medication classes.

Results

• Adherence Rates: Of the 200 participants, 70% (140 patients) achieved good adherence (PDC ≥ 80%), while 30% (60 patients) were non-adherent (PDC < 80%).
• Therapy Patterns: Monotherapy was the most common regimen (86%), with amlodipine being the most frequent agent. Single Pill Combinations (SPC) showed better refill consistency than Free Combinations (FC), though sample sizes for subgroups were small.
• Predictors of Adherence:
  • Financial Burden: This was the only statistically significant independent predictor after adjusting for age, income, and medication sharing. Patients who perceived medication costs as a financial burden were 2.14 times more likely to be non-adherent (AOR = 2.14, 95% CI: 1.30–3.54, p = 0.023).
  • Satisfaction: While 66% of patients agreed the platform helped maintain adherence and 72.5% felt it reduced waiting times, statistical analysis revealed no significant direct association between user satisfaction scores and medication adherence levels (p = 0.399).
  • Demographics: Older adults and those in the M40 income group (RM5,000–RM10,000) showed higher adherence rates.
• Medication Classes: Calcium channel blockers demonstrated the highest refill adherence (71.8%), followed by angiotensin receptor blockers (69.5%) and diuretics (58.2%).

Significance and Claims
The paper claims that while e-prescribing systems offer technological advantages such as reduced waiting times and improved convenience, these benefits are insufficient to overcome economic barriers in the Malaysian context. The study concludes that the "perceived barriers" (financial strain) of the Health Belief Model outweigh the "perceived benefits" (usability of the e-prescribing system) in determining health behavior.

Consequently, the authors argue that digital health interventions cannot rely solely on technology adoption to improve outcomes. Instead, they propose a "comprehensive synergy" between behavioral and economic components. The significance of the findings lies in the recommendation that future adherence strategies must integrate financial support mechanisms (e.g., subsidized schemes, tiered pricing) and targeted counseling that addresses cost concerns alongside the deployment of digital tools. The study emphasizes that without addressing the economic root causes of non-adherence, the full potential of e-prescribing systems in chronic disease management remains unrealized.