Medical Scribe Dictation

---

name: medical-scribe-dictation

description: Convert physician verbal dictation into structured SOAP notes. Trigger.

license: MIT

skill-author: AIPOCH

---

# Medical Scribe Dictation

Convert unstructured physician dictation into professionally formatted SOAP (Subjective, Objective, Assessment, Plan) notes with medical terminology normalization and clinical quality assurance.

When to Use

Key Features

See `## Features` above for related details.

Dependencies

Example Usage

See `## Usage` above for related details.

cd "20260318/scientific-skills/Academic Writing/medical-scribe-dictation"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.

2. Edit the in-file `CONFIG` block or documented parameters if the script uses fixed settings.

3. Run `python scripts/main.py` with the validated inputs.

4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See `## Workflow` above for related details.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py -h
python scripts/main.py --help

Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.

2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.

3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.

4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.

5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Features

Usage

Processing Pre-Transcribed Text

python scripts/main.py --input "patient presents with..." --output-format soap

Processing Audio File (requires whisper/faster-whisper)

python scripts/main.py --audio consultation.wav --output note.md

Python API

from scripts.main import MedicalScribe

scribe = MedicalScribe(specialty="internal_medicine")
soap_note = scribe.process_dictation(transcription_text)
print(soap_note.to_markdown())

Parameters

| Parameter | Type | Default | Description |

|-----------|------|---------|-------------|

| `input` | string | - | Raw transcribed text or path to text file |

| `audio` | string | - | Path to audio file (wav/mp3/m4a) |

| `specialty` | string | "general" | Medical specialty for context hints |

| `output-format` | string | "soap" | Output format: soap, ehr, narrative |

| `language` | string | "auto" | Language code (en/zh/es/...) |

| `confidence-threshold` | float | 0.85 | Minimum confidence for auto-acceptance |

SOAP Output Structure

# Clinical Note - [Date]

## Subjective
Chief Complaint:
History of Present Illness:
Review of Systems:
Past Medical History:
Medications:
Allergies:
Social History:
Family History:

## Objective
Vital Signs:
Physical Examination:
Diagnostic Studies:

## Assessment
Primary Diagnosis:
Differential Diagnoses:
Clinical Reasoning:

## Plan
Diagnostic:
Therapeutic:
Patient Education:
Follow-up:

Technical Architecture

Components

1. **Transcription Module** (optional): Whisper-based STT with medical vocabulary fine-tuning

2. **Segmentation Engine**: NLP-based section identification and content classification

3. **Terminology Processor**: Medical NER (Named Entity Recognition) and normalization

4. **SOAP Assembler**: Structured output generation with specialty-specific formatting

5. **Quality Validator**: Completeness checks and clinical red-flag detection

Technical Difficulty

**High** - Requires medical domain expertise, complex NLP pipelines, and clinical validation.

Known Limitations

References

See `references/` for:

Safety Notes

⚠️ **Clinical Validation Required**: All generated notes must be reviewed by the attending physician before entering the medical record.

⚠️ **No Diagnostic Authority**: This tool structures clinical information but does not provide diagnostic suggestions.

Risk Assessment

| Risk Indicator | Assessment | Level |

|----------------|------------|-------|

| Code Execution | Python/R scripts executed locally | Medium |

| Network Access | No external API calls | Low |

| File System Access | Read input files, write output files | Medium |

| Instruction Tampering | Standard prompt guidelines | Low |

| Data Exposure | Output files saved to workspace | Low |

Security Checklist

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

Test Cases

1. **Basic Functionality**: Standard input → Expected output

2. **Edge Case**: Invalid input → Graceful error handling

3. **Performance**: Large dataset → Acceptable processing time

Lifecycle Status

- Performance optimization

- Additional feature support

Output Requirements

Every final response should make these items explicit when they are relevant:

Error Handling

Input Validation

This skill accepts requests that match the documented purpose of `medical-scribe-dictation` and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

> `medical-scribe-dictation` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template

Use the following fixed structure for non-trivial requests:

1. Objective

2. Inputs Received

3. Assumptions

4. Workflow

5. Deliverable

6. Risks and Limits

7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.