Abstract: The transition toward data-driven medicine represents a structural inflection point for health systems, redefining how quality, equity, and innovation are jointly pursued. Robotic-assisted surgery, when integrated within real-world data infrastructures and effective governance, should be understood not merely as a technological upgrade but as a policy instrument capable of transforming surgical delivery at scale. The diversification of robotic platforms following patent expiration has altered the economic and strategic calculus, enabling broader adoption beyond elite or private settings. Brazil’s decision to incorporate robotic-assisted radical prostatectomy into its Unified Health System (SUS) exemplifies how universal health systems can intentionally integrate advanced surgical technologies with equity objectives, industrial development, and national innovation strategies. This policy-oriented conceptual analysis synthesizes selected literature, policy frameworks, and health system experiences to examine the governance, implementation, and equity implications of data-driven surgery, with an emphasis on universal health systems and low- and middle-income countries. We argue that from a global health and policy perspective, data-driven surgery should be governed as a public asset, anchored in transparency, interoperability, and outcomes accountability, rather than as a market-driven luxury. Real-world data capture has enabled the systematic assessment of surgical performance, the personalization of care pathways, and the scaling of best practices across institutions. In principle, these developments offer a pathway toward more precise, efficient, and equitable surgical care. Health systems that fail to integrate robotics, artificial intelligence, and data governance risk widening inequities and forfeiting innovation sovereignty. Conversely, those that adopt a system-level, policy-led approach can transform surgical care into a lever for both population health and sustainable technological development. Challenges include digital infrastructure gaps, workforce readiness, regional disparities, and ethical concerns related to data governance and privacy. Keywords: data-driven medicine, Surgical public health, robotic-assisted surgery, universal health systems, artificial intelligence, health economic-industrial complex, real-world, innovation policy
Reis et al. (Thu,) studied this question.