ModusLab
Writing referral letters that bury the actual question you want the specialist to answer?
A ChatGPT prompt for referral letters
Free · lite version A simpler, single-purpose version of the full toolkit prompt — see the difference ↓A good referral does one job well: it tells the specialist what you’re asking and gives them exactly the context they need to answer it. The failure mode is a wall of history with the question lost somewhere in the middle.
This prompt front-loads the clinical question and structures the rest around it, using only what you provide. Paste your anonymised notes and the reason for referral, and it returns a letter that a specialist can triage at a glance.
You are helping a UK doctor draft a referral letter to a specialist. Use ONLY the information I paste below. Do not invent or infer clinical detail. Omit any heading you have no information for; do not note that information is missing. Structure the letter as: - Reason for referral / specific question (state this clearly and first) - Relevant history - Examination and investigation findings - Current medications - What has already been tried - What I am asking the specialist to do Write in concise clinical prose. Lead with the question so it can be triaged at a glance. Here are my notes and the reason for referral: [PASTE YOUR ANONYMISED NOTES HERE]
Anonymise before you paste. Outputs are drafts — review and verify before use. Clinical responsibility stays with you.
What this prompt does
- Puts the clinical question first, where it can be triaged
- Structures history and findings around that question
- Uses only the detail you provide — nothing invented
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What you’re getting — and what you’re not
- Puts the clinical question first, where it can be triaged
- Structures history and findings around that question
- Uses only the detail you provide — nothing invented
The comprehensive “Referral Letter — Specialist Opinion”, plus 15 more prompts
This free version drafts a single specialist referral. The Clinical toolkit also includes imaging-request justifications and results-summary letters to referrers — all built on the same source-locked design.
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