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Background <p>Digital surgery technologies, including robotic systems, artificial intelligence (AI) algorithms, augmented reality platforms, and advanced data analytics, are rapidly transforming surgical practice. While these technologies hold tremendous potential to improve patient outcomes, they introduce unique regulatory challenges that current frameworks are not fully equipped to address.</p> Methods <p>This white paper from the SAGES Surgical Data Science Committee characterizes the regulatory challenges specific to digital surgery technologies and proposes general regulatory principles designed to balance patient safety with efficient delivery of beneficial innovations.</p> Results <p>We identify key regulatory gaps across three categories of digital surgery technologies, including enhanced instrumentation and robotics, advanced visualization systems, and AI data analytics and capture. Unlike diagnostic tools, these technologies guide real-time, irreversible actions where errors can cause immediate and permanent patient harm. Critical challenges include the lack of clinically meaningful performance metrics, ambiguous liability across hardware and software stakeholders, performance drift in adaptive algorithms, algorithmic bias, data governance concerns, and insufficient cybersecurity standards for intraoperative systems. To address these gaps, we propose a three-tier risk-stratified classification framework aligned with existing FDA pathways, guidance on predetermined change control plans for adaptive technologies, recommendations for performance metrics that balance technical and clinical evaluation, established evaluation frameworks such as IDEAL and stage-specific reporting guidelines to structure development and assessment, a defined role for professional societies and collaborative communities in shaping clinically relevant standards, and evidence requirements reflecting the procedural context of these tools.</p> Conclusions <p>Regulation of digital surgery must balance innovation with safety, recognizing that both excessive and insufficient oversight can harm patients. Traditional metrics and trial designs are insufficient, as evaluation must be anchored in clinically meaningful outcomes, ongoing surveillance, and real-world validation. The framework presented provides a foundation for achieving this balance through risk-proportionate, evidence-based regulatory approaches.</p>

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Regulating digital surgery to balance safety and innovation: a SAGES white paper

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月19日

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  • Natalie M. Guzman,
  • Jayson S. Marwaha,
  • Deborah S. Keller,
  • Liane S. Feldman,
  • Daniel A. Hashimoto,
  • Amin Madani,
  • Dana A. Telem

摘要

Background

Digital surgery technologies, including robotic systems, artificial intelligence (AI) algorithms, augmented reality platforms, and advanced data analytics, are rapidly transforming surgical practice. While these technologies hold tremendous potential to improve patient outcomes, they introduce unique regulatory challenges that current frameworks are not fully equipped to address.

Methods

This white paper from the SAGES Surgical Data Science Committee characterizes the regulatory challenges specific to digital surgery technologies and proposes general regulatory principles designed to balance patient safety with efficient delivery of beneficial innovations.

Results

We identify key regulatory gaps across three categories of digital surgery technologies, including enhanced instrumentation and robotics, advanced visualization systems, and AI data analytics and capture. Unlike diagnostic tools, these technologies guide real-time, irreversible actions where errors can cause immediate and permanent patient harm. Critical challenges include the lack of clinically meaningful performance metrics, ambiguous liability across hardware and software stakeholders, performance drift in adaptive algorithms, algorithmic bias, data governance concerns, and insufficient cybersecurity standards for intraoperative systems. To address these gaps, we propose a three-tier risk-stratified classification framework aligned with existing FDA pathways, guidance on predetermined change control plans for adaptive technologies, recommendations for performance metrics that balance technical and clinical evaluation, established evaluation frameworks such as IDEAL and stage-specific reporting guidelines to structure development and assessment, a defined role for professional societies and collaborative communities in shaping clinically relevant standards, and evidence requirements reflecting the procedural context of these tools.

Conclusions

Regulation of digital surgery must balance innovation with safety, recognizing that both excessive and insufficient oversight can harm patients. Traditional metrics and trial designs are insufficient, as evaluation must be anchored in clinically meaningful outcomes, ongoing surveillance, and real-world validation. The framework presented provides a foundation for achieving this balance through risk-proportionate, evidence-based regulatory approaches.