Digital transformation (DT) in healthcare has traditionally been conceptualized through models that privilege either technological or organizational perspectives. However, this study shows that DT cannot be understood as a linear or purely technical process but rather as a dynamic adjustment among policy frameworks, organizational capabilities, and technological change. To capture this complexity, we conducted a systematic and integrative review that combined bibliometric mapping and a grounded qualitative synthesis of literature published between 2010 and 2025, guided by three research questions: (RQ1) What are the key themes and trends in healthcare DT? (RQ2) What policy-level barriers and enablers shape its development? and (RQ3) What strategic challenges and benefits influence DT in healthcare institutions? Findings reveal that prevailing models—such as the HIMSS EMRAM and McKinsey 7S frameworks—offer valuable benchmarks but remain limited by static and technocentric assumptions. Building on these insights, this study proposes an integrated framework grounded in Social Systems Theory, which conceptualizes DT as an adaptive system characterized by iterative feedback, learning, and recalibration across policy, organizational, and technological domains. The framework contributes both a theoretical advancement toward an evolutionary understanding of DT and a practical roadmap for policymakers and healthcare managers aiming to build sustainable, interoperable, and human-centered health systems.
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Busco et al. (2026) studied this question.
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