FemTech refers to the application of digital solutions to address health concerns that affect women, such as menstruation, fertility, pregnancy, menopause, etc. It is emerging as a potential way to close persistent gender gaps in health care. While there has been an increase in both technical sophistication and market demand for FemTech products, adoption of FemTech solutions has remained inconsistent. Prior research identified a number of barriers to FemTech adoption; however, each barrier was generally studied in isolation from other barriers and therefore limits our understanding of the systemic inter-relationships between barriers. This study aims to provide insight to the systemic inter-relationships by analysing barriers to FemTech adoption within four categories of barriers: technological (usability, interoperability, data security); socio-cultural (stigma, gender norms, health literacy); economic (cost, funding limitations, insurance coverage); and regulatory and policy (compliance, data governance). Using Interpretive Structural Modeling (ISM) the study developed a hierarchical representation of the relationships between the barriers identified, and using MICMAC analysis classified the barriers based on their drive and dependency power. Results show that regulatory and policy constraints combined with gendered economic constraints are key drivers that shape technological and social cultural barriers to FemTech adoption. Therefore, this study will contribute to a system level of understanding of digital health and information systems and provide insights for policymakers, healthcare managers, and FemTech developers that can lead to more inclusive and sustainable adoption of FemTech solutions.