<![CDATA[Background: The use of mobile health (mHealth) applications (apps) to support healthcare access, administration, and remote consultation has rapidly expanded in Indonesia. However, persistent challenges related to usability, reliability, clinical integration, and trust hinder sustained use of the proposed method. Existing research often adopts a single-perspective approach, which limits the understanding of how user experiences intersect with clinical practice and system-level factors. Objective: This study aims to explain how user-reported experiences, clinical workflow realities, and ecosystem-level constraints interact to shape sustainable mHealth design and implementation in Indonesia. Methods: This study used a qualitative socio-technical grounded theory design that integrated three complementary data sources: large-scale user reviews of four widely used Indonesian mHealth apps, general practitioner interviews, and digital health experts interviews. Based on prior quantitative analysis of user reviews, the review data were re-analyzed qualitatively and synthesized with interview transcripts through open coding, constant comparison, memoing, and socio-technical categorization. Results: mHealth apps were primarily used for administrative tasks, such as booking and payments. However, the perceptions of reliability, simplicity, and trust shaped sustained use. Users reported system instability, complex interfaces, and transactional failures. General practitioners noted misalignment with clinical workflows, workload demands, and organizational barriers. The experts highlighted broader systemic challenges, including fragmented regulation, poor interoperability, and uneven institutional readiness. Conclusion: Sustainable mHealth implementation in Indonesia depends on coordinated readiness across technical, clinical, organizational, and policy domains. This study offers evidence-based recommendations to guide more context-sensitive mHealth design and implementation. Keywords: mHealth Apps, Socio-Technical Analysis, User Reviews, Clinical Workflows, Recommendation]]>
