Effect of Ambient Listening Technology on E&M Codes in Orthopaedic Surgery
Authors:
- Jonathan AriasJAJonathan Arias
- Ed O'BEirneEOEd O'BEirne
- Luke S. Spencer GardnerLGLuke S. Spencer Gardner
- Paul A. RizkPRPaul A. Rizk
- Keith T. AzizKAKeith T. Aziz
- Courtney E. ShermanCSCourtney E. Sherman
- Bryan D. SpringerBSBryan D. Springer
- 31 August 2026
- journal article
- Published by Wolters Kluwer Health in Journal of the American Academy of Orthopaedic Surgeons
Abstract
Background: Accurate Evaluation and Management (E/M) coding depends on the precise documentation of medical decision making. Advances in artificial intelligence have introduced ambient listening technology as a novel documentation tool. Despite its rapid adoption, the effect of ambient listening technology on E/M code selection, coding accuracy, and downstream financial implications remains poorly defined. This study aimed to evaluate the effect of ambient listening technology on E/M code selection, coding concordance, and associated revenue implications within an orthopaedic surgery practice. Methods: A comparative cross-sectional analysis was done of all outpatient E/M services at a single academic medical center. Providers were required to have a minimum of 20 encounters documented using ambient listening technology and traditional dictation for the same encounter type. The final analytic cohort included 7,236 encounters. A randomized subset of 200 encounters (100 ambient listening and 100 traditional) underwent blinded, independent audit by an experienced orthopaedic coding auditor. Outcomes included concordance between provider-selected and auditor-determined E/M levels, weighted coding discrepancies, accuracy rates, and modeled revenue effect. Results: Encounters documented with ambient listening technology were associated with higher E/M levels than those documented with traditional dictation, as assessed by both auditors (3.24 vs 2.96) and providers (3.11 vs 2.82). Overall coding accuracy was 68% for ambient listening and 74% for dictation, while focused review of higher-level ambient listening encounters demonstrated 81.3% accuracy. Revenue modeling projected a potential annual increase of $232,313 if dictation-based encounters achieved E/M distributions observed with ambient listening. Conclusion: Ambient listening–generated documentation meaningfully influences E/M code determination in orthopaedic outpatient practice, supporting higher and more appropriate E/M level selection compared with dictation. Although distinct error patterns persist, ambient listening was associated with reduced undercoding and measurable financial impact. These findings position ambient listening technology as a clinically and financially consequential documentation modality, warranting thoughtful implementation and continued coding oversight.Keywords
This publication has 14 references indexed in Scilit:
- The Influence of Artificial Intelligence Scribes on Clinician Experience and Efficiency among Pediatric Subspecialists: A Rapid, Randomized Quality Improvement TrialApplied Clinical Informatics, 2025
- Ambient Artificial Intelligence Scribes: Learnings after 1 Year and over 2.5 Million UsesNEJM Catalyst, 2025
- Artificial Intelligence in Surgical Coding: Evaluating Large Language Models for Current Procedural Terminology Accuracy in Hand SurgeryJournal of Hand Surgery Global Online, 2025
- Artificial Intelligence to Predict Billing Code Levels of Emergency Department EncountersAnnals of Emergency Medicine, 2024
- Impact of an Artificial Intelligence-Based Solution on Clinicians’ Clinical Documentation Experience: Initial Findings Using Ambient Listening TechnologyJournal of General Internal Medicine, 2024
- Current Applications of Artificial Intelligence in Billing Practices and Clinical Plastic SurgeryPlastic and Reconstructive Surgery - Global Open, 2024
- The impact of nuance DAX ambient listening AI documentation: a cohort studyJournal of the American Medical Informatics Association, 2024
- Association of Evaluation and Management Payment Policy Changes With Medicare Payment to Physicians by SpecialtyJAMA, 2023
- New Billing Rules for Outpatient Office Visit CodesChest, 2020
- How physicians document outpatient visit notes in an electronic health recordInternational Journal of Medical Informatics, 2013