ArticleInternational journal of general medicine2026
Data-Driven Culture in Medicine and Surgery: Policy Pathways to Learning Health Systems.
Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- RoboticJournal of thoracic disease · 2026Article
- From Surgical Innovation to Population Impact: Robot-Assisted Radical Prostatectomy and the Evolution of Surgical Public Health in Brazil's Unified Health System.Chronic diseases and translational medicine · 2026Article
- Multicentre Validation of the 2019 Briganti Nomogram: One Threshold Does Not Fit All.International braz j urol : official journal of the Brazilian Society of UrologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.