The 5 Best AI Medical Scribes for Orthopedics

Summary: The Best AI Scribe for Orthopedics in 2025

DeepScribe is the best overall AI medical scribe for orthopedics in 2025.

DeepScribe’s specialty-specific models allow it to capture high-complexity orthopedic encounters with extreme accuracy, allowing it to cover everything from chronic spine pain and rotator cuff pathology to

DeepScribe is trained on high-complexity orthopedic encounters, allowing it to —covering everything from chronic spine pain and rotator cuff pathology to advanced osteoarthritis and postoperative evaluations—while also capturing the clinical reasoning that defines quality orthopedic documentation.

For orthopedic practices, DeepScribe’s key differentiators are: 

Specialty-level understanding of orthopedics, including MSK anatomy, injury mechanisms, functional assessment, and imaging interpretation. 

Bi-directional EHR integration, including the ability to pull-forward prior patient records and contextualize them to the current visit. 

Coding intelligence across ICD-10, E/M, and HCC.

Deep customization, including macro organizational preferences as well as clinician-level personalization for visit types, phrasing, and formatting that improves autonomously with use.

DeepScribe automatically synthesizes imaging, surgical history, PT progress notes, and longitudinal MSK issues into the documentation, something generic models often fail to do reliably.

While other AI scribes may fit specific scenarios, orthopedic practices handling high encounter volumes, heavy imaging workloads, and complex surgical follow-ups will find Deepscribe offers the strongest blend of depth, accuracy, and customization.

Why Orthopedics Requires Specialty-Specific AI

Many AI scribes today are built to excel across high-volume, highly-templated specialties like primary care rather than layered, longitudinal specialties like orthopedics.

In orthopedics, clinicians must combine imaging results, physical exams, operative history, functional limitations, longitudinal MSK problems and more into a coherent note that supports diagnosis, procedure planning, and accurate coding.

A general-purpose AI can transcribe the conversation, but without true orthopedic training, it often misses the details that define surgical candidacy, progression of disease, or medical decision making..

More specifically, generic AI medical scribes present the following risks to orthopedic practices:

Misinterpreting Historical Imaging or Surgical Data

Generalist models may confuse past findings for present ones—for example, documenting a “current full-thickness tear” when the tear was surgically repaired years earlier—leading to inaccuracies that can compromise care planning and problem list integrity.

Revenue Leakage

Orthopedic documentation requires precise coding around laterality, chronicity, fracture classification, injury mechanism, imaging interpretation, and comorbid factors affecting MDM. General-purpose AI commonly misses these details, reducing E/M levels and missing ICD-10 specificity that influences reimbursement.

Misaligned Templates for Orthopedic Visits

Orthopedics follows predictable but specialized visit structures: new consults for joint pain, pre-op encounters, injection visits, fracture follow-ups, spine evaluations, and postoperative checks. Generic notes often lack orthopedic flow, leading to more edits and cognitive burden.

Gaps in MSK Terminology and Clinical Nuance

Orthopedic language includes:

• Specific physical exam maneuvers (e.g., Lachman, Neer, straight-leg raise)
• Fracture descriptors
• Joint grading systems
• Interpretation of radiology reports
• Functional scoring
• Surgical terminology

Generalist AI frequently oversimplifies or misinterprets these elements, resulting in clinically shallow notes.

How to Choose an AI Scribe for Orthopedics

Selecting an AI scribe for orthopedics requires more than evaluating transcription accuracy. Orthopedic visits are imaging-driven, detail-heavy, and often tied to surgical decision-making—meaning the right tool must understand MSK complexity, integrate deeply with your EHR, and reliably capture the nuances that determine diagnosis, treatment plans, and reimbursement.

Below are the core pillars and practical considerations orthopedic practices should use when selecting a platform.

Specialty Focus

Does the AI:

• Understand MSK anatomy and ortho-specific terminology?
• Correctly capture laterality and disease staging?
• Recognize operative vs. non-operative histories?
• Accurately document imaging findings referenced verbally?

If not, the tool risks producing shallow or misleading notes that undermine clinical decision making.

EHR Integration Depth

To what degree does the AI sync with the EHR system that you use? Can the AI medical scribe pull forward prior imaging reports, surgical notes, PT summaries, and problem list history before or during the encounter? Does it simply paste text or can it populate discrete fields dynamically for assessments, diagnoses, procedures, and orders?

The best AI scribes for orthopedics are those that integrate bi-directionally with your EHR — meaning they can pull information forward from the chart, and push information back into it.

Coding Intelligence

A true ortho-ready scribe should assist with:

• ICD-10 specificity
• E/M leveling based on MDM
• HCC capture for chronic comorbidities

Missed details mean missed revenue.

Customization

Orthopedic clinicians have personalized styles and structured templates for different visit types. A specialty-ready AI scribe should:

• Adapt to each clinician’s preferred note format
• Support structured templates for postop checks, fracture management, joint injections, and surgical planning
• Learn and evolve based on edits over time

When evaluating AI medical scribes for your orthopedic practice, start by identifying your top pain pionts and work backward from there. If after-hours charting is overwhelming, choose a tool with proven time-savings in orthopedic environments. If coding accuracy is the priority, favor tools with strong ICD-10 and E/M intelligence tailored to orthopedic workflows. Or, if synthesizing longitudinal history is the bottleneck, evaluate integration depth and context ingestion capabilities, as well as additional features like AI pre-charting.

Then, conduct demos using real orthopedic cases that apply to your practice, not generic wellness visits.

The Leading AI Scribes for Orthopedics in 2025

1. DeepScribe

Best For: Practices seeking the most advanced orthopedic-specific AI scribe.

DeepScribe leads the orthopedic category thanks to its specialty-trained models, deep customization, and bidirectional EHR integration with leading systems. It handles everything from routine knee pain consults to complex postoperative spine visits with accuracy and nuance. 

Orthopedic Specialty Models:
Trained on millions of patient visits, DeepScribe understands MSK exams, imaging-based reasoning, surgical history, and complex ortho workflows.

Deep Customization:
Each provider’s preferred structure, tone, and templates are learned automatically and refined over time.

Bidirectional EHR Integration:
DeepScribe can ingest imaging reports, operative notes, medications, and prior history to build richer, more accurate documentation — and write-back into the appropriate fields in the EHR.

Coding Intelligence:
DeepScribe proactively identifies ICD-10, HCC, and E/M documentation opportunities — critical for ortho practices managing high complexity and procedural volume.

For orthopedic groups balancing packed schedules, high imaging interpretation load, and surgical workflows, DeepScribe provides leading consistency and ROI.

2. Nuance DAX Copilot (Microsoft)

Best For: Orthopedic departments within large health systems standardized on Epic.

DAX Copilot remains widely adopted in enterprise environments, especially hospital-based orthopedics.

Strengths

• Deep Epic and Meditech integration
• Enterprise-grade stability and compliance
• Well suited for systems with centralized IT governance

Orthopedic Considerations

• Designed around standardized templates, limiting flexibility for specialty-specific customizations without IT escalation
• Some deployments introduce slower note finalization, which may create friction during high-volume clinic or post-op workflows

3. Suki

Best For: Clinicians who want a hybrid scribe + voice-controlled digital assistant.

Suki allows orthopedic providers to retrieve imaging reports, lab results, or operative history using voice commands—while also supporting clinical documentation.

Strengths

• EHR navigation via voice commands (“Pull up last MRI report”)
• Built-in ICD-10 and E/M assistance

Orthopedic Considerations

• More command-driven than ambient; may feel hands-on during visits
• Specialty templates and MSK nuance require manual customization to achieve ideal output

4. Abridge

Best For: Multi-specialty groups or primary care-driven systems that employ orthopedists part-time.

Abridge focuses on generating both clinical notes and simplified summaries for patients—helpful for teams emphasizing patient engagement.

Strengths

• “Linked Evidence” allows users to audit accuracy by tying audio to specific note sections
• Clean, modern UI

Orthopedic Considerations

• Generalist training means limited depth in MSK-specific terminology
• Templates are often standardized, requiring extra adjustment for ortho subspecialties (sports, spine, joints, trauma)

5. Commure

Best For: Practices prioritizing human-reviewed accuracy over instant note turnaround.

Commure (formerly augmented by the Augmedix acquisition) blends AI with human review to ensure note precision.

Strengths

• Human QA layer improves accuracy for atypical or complex encounters
• Supports many EHR environments, including legacy systems

Orthopedic Considerations

• Slower turnaround times are not ideal for surgeons who need charts closed immediately
• Human-in-the-loop model is more resource-intensive and lacks automated pre-chart synthesis

A Practical Roadmap to Pilot and Expansion

Phase 1: Pilot With Complexity That Represents Your Practice

Pilot with providers who manage high imaging workloads or complex surgical decision-making. Measure metrics like “Time to Chart Closure” and after-hours documentation reduction.

Phase 2: Template Optimization

Tune the system to your procedures and standard visit types—postops, fracture care templates, injection notes, pre-op evaluations, and chronic OA management.

Phase 3: Revenue Review

Compare coding patterns pre- and post-implementation. Look for improved capture of:

• Laterality
• Chronicity
• Comorbidity documentation
• Accurate MDM representation

Experience the Best AI Scribe for Orthopedics

If charting is encroaching on your personal time or your current notes fail to capture the depth of your imaging-heavy, procedure-driven orthopedic encounters, it’s time to explore specialty-specific AI.

DeepScribe’s AI medical scribe is built for orthopedics, where diagnostic complexity and procedural workflows demand more than transcription.

Request a demo to:

• Walk through your real orthopedic workflows
• See how DeepScribe handles your most complex cases
• Evaluate the impact of specialty-aware AI on your documentation and efficiency

FAQ

Do AI scribes work for orthopedic procedures and complex MSK cases?

Yes. Solutions like DeepScribe are trained on orthopedic workflows and capture details for complex evaluations—fractures, tendon injuries, spine pathology, joint degeneration, and postop assessments—with structured documentation that generic models cannot replicate.

How do AI scribes integrate with orthopedic EHR systems?

Leading tools use bidirectional integration. They pull forward imaging reports, surgical notes, and PT history, then write structured data back into the EHR to accurately reflect the patient’s MSK progression.

Can AI scribes capture ICD-10 and HCC codes relevant to orthopedics?

Yes. Specialty-oriented platforms identify comorbidities and ICD-10 specifics (laterality, chronicity, injury classification) that affect coding accuracy and reimbursement.

How long does AI scribe implementation take in orthopedic practices?

Usually 2–12 weeks. Vendors with specialty-trained models (like DeepScribe) achieve significantly faster adoption than generic tools requiring extensive manual setup.