Artificial Intelligence Accurately Assists in Billing for Orthopaedic Lower Extremity Surgery: Performance of the Mistral-NeMo Language Model
Purpose To elucidate Mistral-NeMo's proficiency as a novel artificial intelligence assistant to verify coding accuracy and improve efficiency in manual medical coding practices in orthopaedic surgery. Methods This study tested Mistral-NeMo on 1000 operative notes labeled with the Current Procedural Terminology (CPT) codes from 177 providers. In total, there were 46 unique CPT codes; the most common were 29881 (knee arthroscopy with meniscectomy for both medial and lateral menisci), 29880 (knee arthroscopy with m…
Mistral-NeMo verified orthopaedic lower-extremity billing by correctly identifying 90% of true CPT codes and rejecting 99.8% of incorrect codes when provided with billing descriptions.
Mistral-NeMo failed to classify CPT codes accurately when billing descriptions were not provided, showing dependence on contextual information.
Performance depended on contextual information and was insignificant without billing descriptions, limiting use on operative notes alone.
Evidence
- Peer-reviewedArthroscopy2026-09-06
How should this claim be treated?
Truvace Impact Record TRV-2026-1003, v1: “Artificial Intelligence Accurately Assists in Billing for Orthopaedic Lower Extremity Surgery: Performance of the Mistral-NeMo Language Model.” Truvace, 2026-09-07. /record/TRV-2026-1003 (accessed at citation time). sha256 b2ef82ff6a5bb19b…
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