ReviewJournal of robotic surgery2026
Rethinking health technology assessment in robotic surgery: an EFISDS-TROGSS position paper. Official position paper of the European Federation - International Society for Digestive Surgery (EFISDS) and The Robotic Global Surgical Society (TROGSS).
Review in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Staying minimally invasive: robotic versus laparoscopic colorectal cancer surgery in a propensity-weighted Italian multicentre cohort.Journal of robotic surgery · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Robotic-assisted surgery (RAS) has evolved from a procedural innovation into an increasingly integrated component of contemporary digital surgical ecosystems. Nevertheless, most current Health Technology Assessment (HTA) frameworks continue to evaluate robotic systems primarily through comparator-based models focused on isolated perioperative and oncological outcomes. In this EFISDS-TROGSS position paper, we critically examine the methodological limitations of conventional HTA paradigms when applied to robotic surgical platforms, using the recent Italian AGENAS appraisal as a representative case study. While the AGENAS document represents one of the most comprehensive national evaluations of RAS performed to date, its heterogeneous recommendations across procedures highlight unresolved tensions regarding perioperative benefit, real-world implementation, learning curves, organizational impact, and long-term healthcare value. We argue that RAS should increasingly be interpreted not simply as a surgical device, but as a platform technology interacting with simulation-based training, digital infrastructure, surgical data science, artificial intelligence, telecommunication systems, and institutional organization. Rather than a surgical device alone, RAS should be interpreted and regarded as a combination of technological advances and approaches that integrate various degrees of artificial intelligence autonomy, image navigation, telesurgery, and other benefits to empower the surgical team. Conventional HTA models, originally developed for relatively discrete therapeutic interventions, may incompletely capture the multidimensional interaction between robotic technologies and modern healthcare systems. Particular attention is dedicated to real-world evidence, implementation maturity, reimbursement limitations, and the growing mismatch between current Diagnosis-Related Group (DRG) structures and technologically integrated surgical care. Finally, we propose more flexible and multidimensional assessment frameworks integrating procedural outcomes with organizational sustainability, digital interoperability, workforce implications, and longitudinal healthcare value.
Indexed as
Identifiers
42319537What OpenQuestion holds
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.