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).
Clinical Snapshot
PICO Framework
| P — Population | Healthcare systems, surgical institutions, and policymakers evaluating robotic-assisted surgery (RAS) platforms across surgical specialties |
| I — Intervention | Proposed multidimensional Health Technology Assessment (HTA) frameworks incorporating organisational sustainability, digital interoperability, workforce implications, real-world evidence, and longitudinal healthcare value for robotic surgical platforms |
| C — Comparator | Conventional comparator-based HTA models focused on isolated perioperative and oncological outcomes (exemplified by the Italian AGENAS appraisal) |
| O — Outcomes | Adequacy and comprehensiveness of HTA frameworks in capturing the full value of robotic-assisted surgery; reimbursement alignment; implementation maturity; organisational and workforce impact; long-term healthcare system value |
Bottom Line
This EFISDS-TROGSS position paper makes a timely and conceptually important argument: that robotic-assisted surgery has outgrown the evaluative capacity of conventional HTA frameworks designed for discrete therapeutic interventions. The authors compellingly identify real tensions between the multidimensional value of robotic platforms — encompassing training ecosystems, digital infrastructure, telesurgery, and institutional transformation — and the narrow perioperative outcome metrics that dominate current national appraisals, including the Italian AGENAS evaluation used as a case study. However, clinicians and policymakers should engage with this paper as expert advocacy rather than synthesised evidence. The absence of a systematic review methodology, formal consensus process, quantitative data synthesis, and transparent conflict-of-interest disclosure substantially limits the evidentiary weight of its recommendations. The proposed multidimensional HTA framework is intellectually coherent but operationally underdeveloped. For Australian practice, the paper raises legitimate questions about MSAC methodology and AR-DRG alignment for robotic procedures, but local implementation would require adaptation through MSAC, RACS, and health economics expertise. Senior clinicians should treat this paper as a useful conceptual provocation and advocacy document, not as a practice-changing evidence synthesis.
Key Findings
P Value: Not reported
Effect Size: Not applicable — no quantitative effect sizes are reported; this is a qualitative policy position paper
Primary Outcome: The paper argues that conventional HTA frameworks are methodologically insufficient for evaluating robotic surgical platforms as integrated digital ecosystem technologies, and proposes a multidimensional assessment model encompassing procedural outcomes, organisational sustainability, digital interoperability, workforce implications, and longitudinal healthcare value
Nnt Or Sensitivity: Not applicable — no NNT, sensitivity/specificity, or hazard ratio data are presented; the paper does not conduct a primary or secondary quantitative analysis
Confidence Interval: Not reported — no quantitative data synthesis performed
Clinical Application
The conceptual framework proposed is aspirational and requires substantial operationalisation before practical implementation. Adoption of multidimensional HTA approaches would necessitate new data collection infrastructure, revised DRG coding structures, longitudinal outcome registries, and cross-sector collaboration between surgical societies, health economists, payers, and digital health regulators. Feasibility in resource-constrained health systems is not addressed. In Australia, robotic-assisted surgery is evaluated through the Medical Services Advisory Committee (MSAC) process, which assesses safety, clinical effectiveness, and cost-effectiveness prior to Medicare Benefits Schedule (MBS) listing. Several robotic procedures (e.g., robotic prostatectomy, robotic colorectal resection) have been assessed by MSAC with mixed reimbursement outcomes. The paper's critique of comparator-based HTA models is directly relevant to MSAC methodology. The Therapeutic Goods Administration (TGA) regulates robotic surgical devices as Class IIb or Class III medical devices, but TGA approval does not guarantee MBS reimbursement. The RACGP and relevant surgical colleges (RACS) have not yet published unified positions on robotic surgery HTA reform. The paper's arguments regarding DRG misalignment are pertinent to the Australian Refined Diagnosis Related Groups (AR-DRG) system, where robotic procedures are not consistently differentiated from laparoscopic equivalents, creating reimbursement disincentives for public hospitals. Australian public hospital access to robotic surgery remains inequitable, with most platforms concentrated in metropolitan private and tertiary public centres. Surgical departments, hospital administrators, health technology assessment bodies, and health policymakers considering the adoption, reimbursement, or evaluation of robotic-assisted surgical platforms across digestive surgery and other surgical specialties
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.
References
- 1.Marano, L., Oviedo, R. J., Nappo, G., Prete, F. P., Pascotto, B., Abou-Mrad, A., & Vashist, Y. (2026). 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). Journal of Robotic Surgery. Advance online publication. https://doi.org/10.1007/s11701-025-02456-7
Related Research
Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Ventral hernia repair in emergency settings. A machine learning model to predict post-operative complications.
3 Aug 2026
Journal of pediatric surgery
Interpretable deep learning model for pediatric strangulated small bowel obstruction on CT: A multicenter study
3 Aug 2026
European journal of radiology
A CT-based deep learning model to differentiate between benign and malignant adrenal lesions
3 Aug 2026
This content is for educational purposes for healthcare professionals only and does not constitute clinical advice. Clinical decisions should be based on individual patient assessment, current guidelines, and appropriate specialist consultation. Editorial Standards · Privacy Policy · Terms of Service