ScribeMDPro

Cardiology

A scribe that speaks the language of cardiology

NYHA class, guideline-directed medical therapy, imaging review — ScribeMDPro drafts cardiology notes the way you would.

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Cardiology documentation lives in a tight vocabulary — NYHA functional class, murmur grading, ejection fraction, GDMT dose targets, and study-by-study imaging review. A general-purpose transcription tool will mangle these terms; a scribe that produces something reviewable has to understand them. ScribeMDPro's clinical model was trained on cardiology visits — it recognizes functional class descriptions in patient-friendly language and converts them to NYHA classification, it knows which medications belong in the GDMT bundle for HFrEF, and it structures imaging review into readable, chronological summaries. That specificity is why cardiology practices reach for a purpose-built tool rather than a generic dictation product.

Documentation challenges we solve

  • Functional class assessment is described conversationally but needs to be classified precisely (NYHA I–IV) in the note
  • GDMT titration decisions require documentation of dose, target, and rationale for each medication class
  • Imaging review (echo, stress, coronary CT) is dense and benefits from consistent narrative structure
  • Anticoagulation and antiplatelet decisions must be documented with explicit risk/benefit rationale

What clinicians gain

  • Extracts NYHA/CCS classification from natural functional class discussion
  • Structures GDMT plan by class (beta blocker, ACE/ARB/ARNI, MRA, SGLT2) with dose and target
  • Imaging review section formatted study-by-study with key findings and comparison to prior
  • Anticoagulation reasoning captured with CHA2DS2-VASc / HAS-BLED context when discussed

How it works

  1. Step 1
    Start ambient capture

    Open ScribeMDPro before the cardiology encounter and start recording — the patient never has to talk to a device.

  2. Step 2
    Focus on the patient

    Conduct your normal history and exam. Discuss functional status, exam, and imaging as you normally would; the AI restructures into cardiology-standard sections.

  3. Step 3
    Auto-drafted note

    A structured SOAP note appears seconds after the visit ends, formatted for your specialty.

  4. Step 4
    Review, sign, export

    Edit inline, copy to your EMR, download as PDF, or push through supported integrations.

Example SOAP output

S: 68yo M with HFrEF (EF 30%), NYHA II. Reports improved exertional dyspnea since carvedilol uptitration. No orthopnea, PND. Adherent.
O: BP 118/72, HR 62. JVP 6cm, no S3, trace LE edema. Recent echo: EF 32%, mild MR.
A/P: 1) HFrEF — Continue carvedilol 25mg BID (at target). Continue sacubitril/valsartan 97/103 BID, spironolactone 25mg daily, dapagliflozin 10mg daily. Full GDMT. Repeat echo 6 months. 2) Volume status — euvolemic, continue current diuretic. RTC 3 months.

Illustrative only. Clinicians retain final responsibility for the record.

Frequently asked questions

Can it capture echocardiogram review discussion?

Yes. Imaging review is structured study-by-study with EF, chamber sizes, valvular findings, and comparison to prior when mentioned.

Does it understand GDMT terminology?

The model was trained on cardiology notes and recognizes GDMT drug classes, dose targets, and titration language.

What about EP visits (arrhythmia, devices)?

EP-specific vocabulary (device interrogation, ablation planning, CHA2DS2-VASc, HAS-BLED) is supported natively.

Can it handle procedural notes (cath, TEE)?

Procedural note templates are available. The ambient recording captures pre-procedure discussion and consent.

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