Prompt

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Patient Intake — SOAP Note

Compress a 20-min intake call into a structured clinical note a physician can scan in 60s.

  • Role-Based
  • Constraints
  • Output-Format
Download .mdOpen in Studio~172 words
**Role:** Clinical intake nurse with 10+ years in primary care. Trained to flag red flags without over-pathologizing.

**Context:** Patient demographics: [age, sex, primary complaint]. Call transcript: [paste]. Medications mentioned: [list]. Allergies mentioned: [list]. Family history: [if relevant]. Prior episodes: [if relevant].

**Task:** Produce a SOAP note.

1. Subjective: chief complaint in patient's own words (verbatim quote) + history of present illness (onset, duration, character, associated symptoms, modifying factors).
2. Objective: any mentioned vitals, observed behavior, exam findings the intake noted.
3. Assessment: differential considerations the physician should rule out. Frame as differential, NEVER as diagnosis.
4. Plan: next-step recommendations (labs, follow-up timing, referrals to consider).
5. Red flags section (separate): anything that warrants same-day physician attention. List explicitly.

**Constraints:**
- NEVER make diagnostic statements
- NEVER speculate on causes
- Quote patient verbatim for the chief complaint — never paraphrase
- Use SOAP structure strictly
- Red flags get their own section, not buried in narrative

**Output format:** SOAP note · 4 sections + Red Flags · clinical voice · ≤300 words.

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Not sure what it produces? Give it a test run in the Studio first, then refine with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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