The Best AI Medical Scribe for ModMed in 2026

Quick Answer: What's the Best AI Scribe for ModMed?

DeepScribe is the best AI medical scribe for ModMed in 2026. Its bi-directional integration with ModMed pulls patient context from the chart and pushes structured documentation back into discrete fields — without copy-paste or manual re-entry. It's purpose-built for the specialties ModMed serves, with AI models trained on gastroenterology, orthopedics, urology, ENT, dermatology, OBGYN, and more. For practices that chose ModMed precisely because it understands specialty workflows, DeepScribe extends that philosophy directly into the documentation layer.

Key takeaways:

• ModMed is a specialty-first EHR. The AI scribe you pair with it should be specialty-first as well — not a general-purpose tool that approximates specialty workflows.
• Integration depth matters. Scribes that only push text into a note field leave clinicians doing manual work. True bi-directional integration means the AI reads the chart and writes back to the right places automatically.
• DeepScribe holds a KLAS score of 98.8/100 — the highest in the ambient AI scribe category — and integrates directly with ModMed across its core specialties.
• For gastroenterology, orthopedics, and urology practices specifically, DeepScribe's specialty-trained models provide meaningful clinical accuracy advantages over generalist platforms.

Why ModMed Practices Have Higher AI Scribe Standards

ModMed was built for specialists. Unlike horizontal EHRs designed to serve any practice type, ModMed organizes its entire platform around specialty-specific workflows — specialty-coded templates, built-in procedure documentation, specialty-relevant billing logic, and a workflow that reflects how specialists actually practice.

That design philosophy means ModMed practices tend to have more refined documentation expectations than the average primary care office. When a gastroenterologist opens a procedure note in ModMed, it already has structure: fields for indication, bowel prep, instruments used, polyp characteristics, pathology disposition. When an orthopedic surgeon reviews a follow-up note, the layout reflects surgical history, functional assessment, and imaging correlation in a way that makes clinical sense.

This creates a problem for AI scribes that weren't built with specialty depth in mind. A generalist ambient tool can capture the conversation and generate a reasonable note — but "reasonable" in a GI or orthopedics practice means something different than it does in primary care. Generalist AI often flattens specialty nuance: it misses laterality, skips procedure detail, underspecifies ICD-10 codes, and produces notes that require significant rework before they meet the clinical and billing standards that ModMed practices expect.

The EHR integration layer is the other gap. Some AI scribes connect to ModMed in a limited way — enough to sync the note after the fact, but not enough to pull patient history before the visit or write structured data back into discrete fields. That means clinicians are still managing a two-system workflow: the AI generates a note, and the physician manually reconciles it with the ModMed record. That's a documentation burden reduction, but it's not elimination.

For ModMed practices evaluating AI scribes in 2026, the standard should be: specialty AI that matches the clinical depth of your EHR, with integration deep enough to replace the copy-paste layer entirely.

How AI Scribe Integration Works with ModMed — and Why Tiers Matter

Not all AI scribe integrations with ModMed are equivalent. There are effectively three tiers of connectivity, and the difference between them determines how much manual work the clinician still has to do after the AI generates a note.

Tier 1 — No integration: The AI scribe generates a note in its own interface. The clinician copies text into ModMed manually. This eliminates dictation time but introduces a copy-paste step that still consumes minutes per encounter. At scale, across a busy GI or orthopedic practice, this adds up.

Tier 2 — Push-only integration: The AI connects to ModMed and can push a completed note into the chart automatically. This removes the manual copy step, which is a real improvement. But the AI isn't reading the chart before the visit — it has no awareness of prior notes, recent labs, imaging results, or surgical history. Every note is generated without longitudinal context, which typically produces documentation that's less complete and requires more clinician editing.

Tier 3 — Bi-directional integration: The AI both reads from and writes to ModMed. Before the encounter, it pulls relevant chart data — prior diagnoses, procedure history, active medications, imaging, lab trends — and incorporates that context into the note it generates during the visit. After the encounter, it pushes structured documentation back into the correct discrete fields, not just a text block. This is the level of integration that eliminates dual-system workflow and produces notes that reflect the full clinical picture.

DeepScribe operates at Tier 3. For ModMed practices, this means AI pre-charting that synthesizes the relevant patient history before the visit begins, note generation during the encounter that incorporates that context, and post-encounter documentation that maps correctly to ModMed's specialty-specific templates and fields.

What to Look for in an AI Scribe for ModMed

Specialty-Specific AI Models

ModMed practices are not primary care. The AI scribe you deploy should have models trained specifically on the encounter types your clinicians see — GI procedures, orthopedic evaluations, urology clinic visits. Generic ambient AI models produce generic notes, and specialty clinicians spend time correcting them. Look for evidence that the vendor has trained models on your specialty, not just claims that their tool "supports" it.

Bi-Directional ModMed Integration

Confirm that the integration pulls patient data from the chart before the visit and pushes structured documentation back after — not just text into a note field. Ask specifically how the tool handles ModMed's specialty-coded templates: does it map to existing template structure, or does it produce freeform text that the clinician has to reformat?

Coding Intelligence for Specialty Encounters

ModMed practices generate complex coding scenarios. GI practices deal with multi-code colonoscopy encounters, add-on codes for polypectomy and EMR, and HCC conditions in chronic liver patients. Orthopedic practices need accurate E/M documentation with laterality, chronicity, and MDM complexity captured correctly. Urology practices navigate global periods, modifier usage, and longitudinal PSA documentation. The AI scribe should understand these coding contexts and surface the appropriate codes — not just transcribe the conversation and leave billing inference to the coder.

Customization by Clinician and Note Type

A gastroenterologist's IBD follow-up note looks different from their colonoscopy procedure note. An orthopedic surgeon's post-op note follows different structure than a new patient MSK evaluation. The AI scribe should support per-clinician customization by visit type, with the ability to tune output structure, phrasing, and field mapping without requiring IT intervention on every change. Look for systems that learn from clinician edits and apply those preferences forward automatically.

Deployment Support and Adoption Infrastructure

ModMed practices tend to be smaller specialty groups, not large health system IT departments. The vendor's implementation approach should match that reality — structured onboarding, hands-on template tuning, and a support model that doesn't require internal IT resources to maintain. Ask about go-live timelines, at-the-elbow support availability, and what ongoing governance looks like after deployment.

The Best AI Medical Scribes for ModMed, Ranked

1. DeepScribe

Best for: ModMed specialty practices — particularly gastroenterology, orthopedics, and urology — that need specialty-trained AI with deep EHR integration and per-clinician customization.

DeepScribe is the top-rated AI medical scribe for ModMed in 2026. Its KLAS score of 98.8/100 leads the category, and its direct ModMed integration operates bi-directionally — pulling patient history, prior procedure notes, lab trends, and imaging results before the encounter, and pushing structured documentation back into the correct ModMed template fields after.

The clinical alignment between DeepScribe and ModMed's core specialties is the primary differentiator. DeepScribe's AI models are trained on millions of specialty encounters, which means the tool understands the clinical vocabulary, documentation structure, and billing logic of gastroenterology, orthopedics, and urology without requiring clinicians to manually configure it from scratch.

For gastroenterology practices on ModMed: DeepScribe handles the full documentation scope of a GI practice — clinic visits and procedure notes alike. It captures IBD flare characterization, hepatology assessments with relevant lab context (LFTs, MELD, bilirubin trends), colonoscopy documentation with finding detail and pathology disposition, and complex multi-condition patients who carry both GI and systemic diagnoses. The coding layer flags HCC-eligible conditions like cirrhosis, chronic liver disease, and malabsorption, and supports the multi-code encounter structures that GI billing requires.

For orthopedics practices on ModMed: DeepScribe pulls surgical history, physical therapy progress, and imaging reports into the encounter context before the visit, so the generated note reflects the full MSK picture rather than the isolated conversation. Laterality, chronicity, functional limitation, and MDM complexity — all the elements that determine E/M level — are captured in the note automatically. The customization layer supports orthopedic note types (new patient evaluation, post-op visit, injection note, pre-surgical workup) with distinct templates that can be tuned to each surgeon's documentation style.

For urology practices on ModMed: DeepScribe integrates with both ModMed and UroChart, giving urology practices flexibility regardless of their specialty EHR setup. The AI models understand urology-specific workflows — BPH and LUTS documentation, PSA trending, cystoscopy and TURP procedure notes, post-prostatectomy follow-up, men's health visits — and the coding intelligence handles global periods, modifier usage, and the specificity requirements of urology ICD-10 coding.

Quality outcomes across DeepScribe deployments include a 95.9% major defect-free rate on audited notes, 85% clinician adoption, a 16% increase in diagnoses captured per visit, 22% improvement in ICD-10 code specificity, and a 45% increase in SDOH capture.

Customization is managed through DeepScribe's Customization Studio, which supports governance at the organization, service line, and individual clinician level. Clinicians don't need to manually configure preferences from scratch — the system learns from edits and applies adjustments forward. For practices with multiple specialties under one group (a common ModMed scenario), this governance structure lets administrators standardize baseline documentation while preserving individual clinician preferences.

2. Nuance DAX (Microsoft)

Best for: Large health systems with ModMed deployed at scale, existing Microsoft infrastructure, and dedicated IT resources for enterprise implementation.

Nuance DAX is a credible ambient AI platform with strong enterprise reliability and brand recognition. For ModMed practices, DAX provides ambient capture and reasonable note generation across clinical encounters. Its primary strength is scale — large organizations that have already invested in the Microsoft/Nuance ecosystem can extend DAX to ModMed environments without adopting a new vendor relationship.

The limitations are most visible in specialty depth and customization flexibility. DAX's models are broadly trained across specialties rather than purpose-built for the clinical nuance of GI, orthopedics, or urology. Clinicians in these specialties often report needing to do more note editing than with purpose-built alternatives, and the customization layer — while present — is less granular than what ModMed specialty practices typically require. Implementation is also weighted toward large enterprise deployments; smaller specialty groups may find the rollout process heavier than necessary for their size.

3. Abridge

Best for: Multi-specialty health systems where Epic is the primary EHR and ModMed is deployed for a subset of specialists.

Abridge has built a strong reputation for real-time note generation and clean, readable output. Its integration is strongest in Epic environments, where it has invested most of its EHR connectivity development. For ModMed-specific deployments, the integration tends toward push-only rather than bi-directional, which limits the pre-charting and discrete field mapping capabilities that ModMed specialty workflows benefit from most.

Abridge's "Linked Evidence" feature — which connects specific note elements back to the source audio — is a useful transparency and audit tool. On the specialty side, its models are more generalist in orientation than DeepScribe's, which can produce notes in GI or orthopedics that require more clinician editing to meet specialty documentation standards.

4. Suki

Best for: Individual practitioners or small practices looking for fast deployment and a hybrid voice-command plus ambient workflow.

Suki combines voice-command interaction with ambient ambient listening, giving clinicians more explicit control over how notes are structured and what gets captured. For ModMed practices that prefer a more hands-on documentation approach — particularly in lower-complexity visit types — Suki provides an accessible on-ramp with minimal implementation overhead.

The trade-off is that Suki's specialty depth is less developed than DeepScribe's, and the command-driven elements of the workflow add interaction overhead in high-volume environments. For a urology or orthopedics practice seeing 25+ patients per day, the efficiency ceiling is lower than with a fully ambient system. Customization is available but requires more active clinician configuration rather than learning from behavior over time.

5. Commure

Best for: Practices where clinical accuracy is the top priority and a slightly slower turnaround time is acceptable.

Commure (incorporating the Augmedix model) blends AI-generated drafts with a human review layer, which provides a meaningful accuracy backstop for atypical or diagnostically complex encounters. For ModMed practices with unusual case complexity or a lower tolerance for AI error, this hybrid approach offers a different risk profile than fully automated systems.

The practical limitation is speed. The human-in-the-loop model introduces latency between encounter and finalized note, which disrupts same-day chart closure in high-volume practice environments. Specialty depth is still maturing, and the ModMed integration capabilities are less developed than those of the top-ranked options.

Implementation Roadmap for ModMed Practices

Phase 1: Pilot With Your Most Complex Encounter Types

Identify two to three clinicians who represent the highest documentation complexity in your practice — your IBD specialist, your joint replacement surgeon, your high-volume urologist. Piloting with high-complexity users rather than the easiest cases gives you a real signal about whether the AI can handle your actual workload. Run the pilot for four to six weeks and measure time-to-chart-closure, after-hours documentation time, and note editing volume per encounter.

Phase 2: Template and Integration Tuning

Once you've validated accuracy and workflow fit, move into customization. Map the AI's output to your specific ModMed templates — procedure note fields, follow-up structure, pre-op documentation format. Configure clinician-level preferences for note structure and phrasing. Confirm that discrete field mapping from the AI pushes correctly into the ModMed fields your billers and coders rely on. This phase typically takes two to four weeks and sets up the infrastructure for clean, scalable deployment.

Phase 3: Revenue and Coding Review

At the 60–90 day mark post-deployment, pull a comparative coding analysis. Compare E/M level distribution, ICD-10 specificity, HCC capture rate, and any changes in chart closure timing from before implementation. For GI practices, look specifically at comorbidity capture in complex liver and IBD patients. For orthopedics, examine MDM documentation quality and its relationship to supported E/M levels. For urology, review procedure code accuracy and global period handling. These metrics tell you whether the AI is generating documentation quality benefits, not just documentation speed benefits.

See DeepScribe in Your ModMed Environment

If you're evaluating AI scribes for a ModMed deployment, the best starting point is a structured demo that walks through your actual workflows — your note types, your procedure documentation, your coding scenarios.

Request a demo at deepscribe.ai/contact to see how DeepScribe works within your ModMed environment and what clinical and revenue impact you can expect in your specialty.

Frequently Asked Questions

What is the best AI medical scribe for ModMed?

DeepScribe is the best AI medical scribe for ModMed in 2026. It integrates bi-directionally with ModMed — pulling patient history before the visit and pushing structured documentation back into discrete fields after — and its AI models are purpose-built for the specialties ModMed serves, including gastroenterology, orthopedics, and urology, among others.

Does DeepScribe integrate with ModMed?

Yes. DeepScribe has a direct integration with ModMed that supports bi-directional data flow. The AI pulls chart context (prior notes, lab trends, imaging, surgical history) before the encounter to inform note generation, and it writes structured documentation back into the correct ModMed fields after the visit — including specialty-specific template elements.

Can AI scribes handle ModMed's specialty-specific templates?

The best ones can. AI scribes with bi-directional ModMed integration and specialty-trained models can map generated documentation to ModMed's specialty templates rather than producing freeform text that clinicians have to reformat manually. DeepScribe supports this mapping for ModMed's core specialties, with customization options at the note-type and clinician level.

How does an AI scribe help with coding in a ModMed specialty practice?

Specialty practices on ModMed deal with complex coding scenarios — multi-code GI procedure encounters, orthopedic E/M with MDM complexity, urology global periods and modifiers. An AI scribe with built-in coding intelligence surfaces appropriate ICD-10, CPT, E/M, and HCC codes based on the documented encounter, reducing the gap between clinical documentation and billing accuracy. DeepScribe's coding layer captures these automatically, including HCC-eligible conditions that are commonly underdocumented in specialty visits.

How long does it take to implement an AI scribe in a ModMed practice?

Most practices complete a structured pilot in four to six weeks, followed by template tuning and full deployment over an additional two to four weeks. Total time from kickoff to full deployment typically runs eight to twelve weeks depending on the number of providers, complexity of ModMed template customization, and depth of EHR integration required.

Do AI scribes work for GI procedures like colonoscopy and EGD?

Yes, with the right platform. Purpose-built AI scribes like DeepScribe are trained to document GI procedures — capturing indication, prep quality, instrument details, findings (polyp size, location, morphology), interventions (polypectomy, EMR, biopsy), and pathology disposition — in a structured format that supports both clinical continuity and accurate billing. Generalist AI tools typically produce less complete procedure documentation and require more post-procedure editing.

Which AI scribe works best for an orthopedic practice on ModMed?

DeepScribe is the top choice for orthopedic practices on ModMed. Its models capture the specificity orthopedics requires — laterality, chronicity, functional limitation, imaging correlation, surgical history — and its bi-directional ModMed integration means prior operative notes and imaging reports inform each new encounter automatically. The customization layer supports orthopedic-specific note types (post-op, injection, new patient MSK evaluation) with distinct templates per visit type.

Is an AI scribe worth it for a smaller specialty practice on ModMed?

Yes, and smaller practices often see the impact more quickly than large health systems. A four-physician GI or urology group can realistically recover one to two hours of documentation time per clinician per day, reduce after-hours charting significantly, and improve coding accuracy without adding administrative headcount. The ROI case for smaller specialty practices is straightforward when the implementation is matched to the practice's actual workflow rather than a generic enterprise deployment model.

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