AI for Writing Medical Referral Letters

A strong referral letter answers the specialist's first question: what do you want me to do? Useful content includes: the specific clinical question and the urgency; relevant history; current medications and allergies; key exam findings; investigations with values and timing; treatments already tried and how the patient responded; practical needs, such as an interpreter or mobility support; and what the patient has been told. With AI, a safe workflow runs in steps.

Choose the right tool. Use one your organization has approved, ideally built into the EHR or covered by a business associate agreement. Consumer chatbots usually do not offer HIPAA protections by default; If the tool is not approved for identifiable data, de-identify the input. HIPAA's Safe Harbor method lists 18 identifiers to remove, including names, addresses smaller than a state, all date elements except the year, phone numbers, email addresses and medical record numbers. Use placeholders such as [PATIENT] and relative timing such as 'three months ago'; Tell the model its role, the recipient's specialty and the purpose of the letter; Paste the facts in labeled sections. Instruct the model to use only what you provided and to mark gaps as [MISSING] instead of guessing; Specify the format and length, with the question first; review every sentence. Check numbers, drug names, doses, laterality and dates, and delete anything the model added; and Put the identifiers back in inside the EHR, then sign. Two misconceptions are common. The first is that removing the name is enough. A rare condition combined with exact dates and a town can still identify someone. The second is that the AI 'knows' the patient. It only knows what you paste in, so missing facts produce a confident but incomplete letter. Longer is not better, either: specialists triaging many referrals want the question and the key data up front.