Staged future-research agenda for transitioning LC assessment tools from developmental validation to safe clinical integration¶

Strategy · All strategies
Evidence · 4 claims (4 for) · 1 study (1 review), q3 · 0 of 1 report an effect size · 4 claims rest on one study

Description¶

The review's future research agenda lists five directions: prospective multicentre validation across heterogeneous pathology and surgeon experience levels; transparent, standardised annotation protocols to strengthen ground-truth reliability; evaluating "behavioural changes, learning curves, and patient outcomes, rather than relying solely on technical classification metrics"; shared benchmark datasets for reproducible external validation; and aligning tool design with intended use, distinguishing formative feedback, monitoring, and credentialing functions. For real-time AI deployment, the authors recommend alignment with the IDEAL and DECIDE-AI staged evaluation frameworks, preserving explicit human oversight.

Design Implications¶

Context¶

Requirements¶

• Progress depends on multicentre heterogeneous datasets and evidence of clinical impact rather than further technical refinement alone, per the review's conclusion.

Constraints¶

• The review currently supports no tool for integration into surgical credentialing or performance monitoring systems.

Target Learners¶

• surgical trainees
• practising surgeons

Target Learning Goals¶

• objective technical skill assessment
• safe integration of assessment tools into training and governance

Claims¶

• AI-based assessment systems show strong internal performance and early real-time deployment for critical view of safety detection, but lack external validation and clinical impact evidence [+W]
• Kinematic assessment systems for laparoscopic cholecystectomy are weakly validated, restricted to small datasets, and capture only a narrow component of operative competence [+W]
• Manual assessment tools have the largest body of validity evidence in laparoscopic cholecystectomy but show variable reliability and no links to patient outcomes [+W]
• No objective assessment tool for laparoscopic cholecystectomy demonstrates comprehensive validity across all Messick domains, so no gold standard exists [+W]

Related Strategies¶

• Standardize reporting of LLM versions, processing dates, input selection criteria, and data quality protocols in future MCQ benchmarking research

Examples¶

-

Key Sources¶

• Mainwaring Elizabeth M. A., Guidozzi Nadia, James Jonnie P., Pantling Jai, Menon Nainika, Salem Riadh, Markar Sheraz R. (2026). Objective technical skills assessment in laparoscopic cholecystectomy: a systematic review of manual, kinematic, and AI-based tools. Surgical Endoscopy. https://doi.org/10.1007/s00464-026-13309-z