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Digital Health in Low-Resource Settings: Comprehensive Challenges and Opportunities With a Focus on Stroke Care
João Brainer Clares de Andrade1,2,3, Thales Pardini Fagundes4, Eric Katsuyama5
1Hospital Israelita Albert Einstein, Academic Research Organization, São Paulo, Brazil (J.B.C.d.A., G.S.S.).
Abstract:
The global transition to digital health offers a critical opportunity to transform health care delivery, particularly in low- and middle-income countries. Stroke care exemplifies the need for timely, coordinated, and longitudinal management across health systems. Although substantial progress has been achieved, low- and middle-income countries continue to encounter persistent challenges, including infrastructural deficiencies, digital inequity, fragmented governance structures, and limitations within the health care workforce. Nonetheless, scalable digital health interventions, such as telestroke networks, mobile health platforms, artificial intelligence-supported diagnostics, and telerehabilitation programs, have demonstrated efficacy and impact across diverse contexts. The central challenge has, thus, shifted from technological development to the systemic integration of these solutions within existing health infrastructures. Crucially, low- and middle-income countries must not be perceived solely as passive recipients of technology but as active agents of innovation, developing efficient, adaptive, and culturally attuned models prioritizing community engagement and a holistic conception of health. To realize the transformative potential of digital health, it is imperative to invest not only in technological infrastructure but also in promoting digital literacy, establishing robust ethical and regulatory frameworks, fostering cross-sectoral partnerships, and creating inclusive innovation ecosystems. Only through such a comprehensive, human-centered approach can digital health effectively serve as a catalyst for more equitable, resilient, and sustainable health systems, particularly for populations residing in resource-constrained settings.
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