The IDEAL framework for surgical robotics: development, comparative evaluation and long-term monitoring.
Hani J MarcusPedro T RamirezDanyal Zaman KhanHugo Layard HorsfallJohn G HanrahanSimon C WilliamsDavid J BeardRani BhatKenneth CatchpoleAndrew CookKatrina HutchisonJanet MartinTom MelvinDanail StoyanovMaroeska M RoversNicholas Tobias Johannes RaisonProkar DasguptaDavid NoonanDeborah StockenGeorgia SturtAnne VanhoestenbergheBaptiste VaseyPeter McCullochnull nullPublished in: Nature medicine (2024)
The next generation of surgical robotics is poised to disrupt healthcare systems worldwide, requiring new frameworks for evaluation. However, evaluation during a surgical robot's development is challenging due to their complex evolving nature, potential for wider system disruption and integration with complementary technologies like artificial intelligence. Comparative clinical studies require attention to intervention context, learning curves and standardized outcomes. Long-term monitoring needs to transition toward collaborative, transparent and inclusive consortiums for real-world data collection. Here, the Idea, Development, Exploration, Assessment and Long-term monitoring (IDEAL) Robotics Colloquium proposes recommendations for evaluation during development, comparative study and clinical monitoring of surgical robots-providing practical recommendations for developers, clinicians, patients and healthcare systems. Multiple perspectives are considered, including economics, surgical training, human factors, ethics, patient perspectives and sustainability. Further work is needed on standardized metrics, health economic assessment models and global applicability of recommendations.
Keyphrases
- healthcare
- artificial intelligence
- big data
- machine learning
- endothelial cells
- end stage renal disease
- chronic kidney disease
- ejection fraction
- type diabetes
- metabolic syndrome
- case report
- social media
- insulin resistance
- prognostic factors
- weight loss
- data analysis
- induced pluripotent stem cells
- patient reported
- glycemic control