Healthcare5.0 · 132 ratings

Patient Intake — SOAP Note

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

Role-BasedConstraintsOutput-Format

Prompt

**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 this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer 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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