Effectiveness Of Ai-Based Telemedicine In Improving Treatment Compliance Of Chronic Disease Patients In The Post-Pandemic Era: A Multicenter Study In Indonesia
DOI:
https://doi.org/10.46799/jhs.v6i3.2727Keywords:
Telemedicine;, Artificial Intelligence;, Medication Adherence;, Chronic Disease;, Post-Pandemic EraAbstract
Chronic diseases such as hypertension, diabetes, and chronic kidney failure are still major contributors to morbidity and mortality in Indonesia. However, long-term treatment compliance remains low, especially in areas with limited access to healthcare. This study aims to evaluate the effectiveness of an artificial intelligence (AI)-based telemedicine system in enhancing medication adherence among patients with chronic diseases in the post-pandemic era. The study design used a mixed method with a sequential explanatory approach, involving 300 patients from three representative areas (Jakarta, Yogyakarta, and East Sumba). Quantitative data collection was conducted using the Medication Adherence Rating Scale (MARS) instrument before and after the system was implemented for 3 months. Qualitative data were obtained through in-depth interviews with patients and medical personnel. The results showed a significant increase in adherence scores (p<0.001) from an average of 6.8 to 8.9 after the intervention. AI features, such as medication reminders, self-monitoring, and interactive chatbots, have been shown to improve adherence and foster positive habits. Regression analysis showed a positive correlation between the intensity of interaction with the application and increased adherence. In-depth interviews revealed that the system was perceived as a "digital companion" that helped patients adhere to their medication regimen. However, barriers related to digital literacy and connectivity in rural areas remained. This study provides evidence that integrating AI into telemedicine services can be a strategic solution to improve adherence to chronic disease medication in Indonesia. These findings offer recommendations for the development of a national digital health system that is inclusive, adaptive, and data-driven. This research also supports the transformation service digital health as part of the post-pandemic health reform agenda.
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