Effectiveness of Digital Pharmaceutical Care Intervention on Medication Adherence in Hypertensive Patients: A Quasi-Experimental Study in Banjarmasin, South Kalimantan
Abstract
Hypertension remains a major public health challenge in Indonesia, where suboptimal adherence to antihypertensive therapy contributes to poor blood pressure control and avoidable cardiovascular risk. Pharmacist-led digital care offers a promising strategy to enhance medication adherence. This study aimed to evaluate the effectiveness of SatuObat, a Pharmacist-led digital care app, in improving medication adherence among hypertensive patients in community pharmacy practice. A quasi-experimental study with a non-equivalent control group pre-test and post-test design was conducted at community pharmacies in Banjarmasin, Indonesia. A total of 102 patients were recruited using consecutive sampling and assigned to either a control group (receiving usual care, n=52) or an intervention group (receiving usual care plus SatuObat app, n=50). The intervention comprised structured digital reminders, two-way chat with pharmacists, and tailored educational messages delivered through the app over 4 weeks. Medication adherence was measured using the validated Indonesian version of the MARS-5 questionnaire. Data were analyzed using the Wilcoxon signed-rank test and the Mann-Whitney U test. Adherence did not change significantly in the control group (p = 0.532), whereas the intervention group showed a significant increase in adherence scores (Δ = 7.20; p < 0.001). Post-intervention adherence was significantly higher in the intervention group than in the control group (p < 0.001). These findings indicate that integrating SatuObat into pharmacist-led care can substantially enhance medication adherence among hypertensive patients in community pharmacy settings and support the wider adoption of digital pharmaceutical care in low- and middle-income countries.
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Copyright (c) 2026 Yugo Susanto, Andi Hermansyah, Muhammad Ashar, Saybah Humairah, Devi Ristian Octavia, Long Chiau Ming, Muhammad Junaid Farrukh, Zaheer-Ud-Din Babar, Ronny Faslah, Abdul Rahem, Yuni Priyandani, Gusti Noorrizka Veronika Achmad

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