The short answer
The best AI prompts for doctors are built to prevent hallucinations. Instead of asking an AI to simply “write a SOAP note,” a safer prompt provides the raw transcript and instructs the AI to *only* use the information provided, mark any gaps with [to complete], and flag ambiguous phrases rather than guessing. This “forced-extraction” method drastically reduces the risk of fabricated clinical details entering your notes.
Physician burnout remains stubbornly high, with up to 53% of doctors reporting at least one symptom. A primary driver is administrative burden, especially the hours spent on clinical documentation. While 81% of physicians now use AI professionally, many are using generic prompts that expose their notes to a significant, underappreciated risk: clinical hallucination.
ZEKAI is an independent AI-tools directory; we make recommendations based on our own research and testing. For physicians, the biggest leverage point in using AI safely is not just *which* tool you use, but *how* you prompt it. This guide provides 25 copy-paste prompts built on a “forced-extraction” framework designed to minimize errors and save you hours. For a broader look at the technology, see our guide to AI for doctors and healthcare professionals.
Why Generic Prompts Produce Hallucinated Clinical Notes
An AI hallucination is when a model generates fluent, confident-sounding information that is factually incorrect or was never mentioned in the source material. In a clinical context, this can mean inventing physical exam findings, fabricating patient history details, or misstating the plan of care.
This is not a rare or hypothetical problem.
Source: frontiersin.org
A 2025 study published in *Frontiers in Digital Health* found that clinical notes generated by an ambient AI scribe contained hallucinations in 31% of cases.
Other research published in *npj Digital Medicine* found baseline hallucination rates between 1-3%, but warned that even a low error rate becomes a large absolute number of mistakes when scaled across thousands of daily encounters. The risk is that a fabricated detail is signed into the chart, becoming part of the permanent medical record and contaminating future clinical decisions.
These errors happen because general-purpose AI models are designed to be “creative” and fill in gaps. A generic prompt like “Summarize this visit” encourages the AI to infer, guess, and generate a plausible-sounding narrative, even if it has to invent details to do so.
The “Forced-Extraction” Framework: Your Defense Against AI Errors
The safest way to prompt a large language model in a clinical setting is to constrain its creativity. The “forced-extraction” framework turns the AI from a creative writer into a disciplined transcription assistant.
The core principles are:
- Provide the full, raw text: Give the model the complete, de-identified transcript of the patient encounter.
- Explicitly forbid outside information: Instruct the model to *only* use information from the provided text.
- Mandate flagging for ambiguity: Command the model to flag any confusing, contradictory, or unclear statements rather than interpreting them.
- Require placeholders for missing information: Tell the model to insert a clear placeholder like
[to complete]or[clarify with patient]for any information that is expected but not present.
This approach forces the AI to surface gaps and uncertainties, putting the clinician back in control of all final medical judgments.
Generic vs. Forced-Extraction Prompting
| Prompt Type | Example Prompt | Output Risk |
|---|---|---|
| Generic | “Write a SOAP note for this patient visit.” | High risk of hallucinated findings, omissions, and incorrect interpretations as the AI tries to create a “complete” note. |
| Forced-Extraction | “From the transcript below, extract the information to create a SOAP note. Use ONLY the text provided. Do not infer or add any information not present in the transcript. If a section is missing information, write [to complete]. If any phrase is ambiguous, quote it and add [clinician to clarify].” | Low risk. The AI is constrained to extraction and formatting. Gaps and ambiguities are surfaced for physician review. |
Swipe the table sideways →
8 AI Prompts for Faster, Safer Clinical Documentation
These prompts are designed for use in HIPAA-compliant AI platforms. Do not paste protected health information (PHI) into general-purpose consumer chatbots. Use these with tools built for healthcare, like Freed AI or enterprise systems from vendors like Microsoft.
Act as a medical scribe. Based ONLY on the provided transcript below, generate a SOAP note.
RULES:
1. Use information exclusively from the transcript. Do not add or infer any details.
2. Structure the output into four sections: Subjective, Objective, Assessment, and Plan.
3. For any part of the SOAP note where information is not available in the transcript, you MUST write "[to complete]".
4. If any part of the transcript is ambiguous or contradictory, quote the exact phrase and add "[clinician to clarify]".
5. Format the output in clear, concise medical terminology.
[Paste de-identified transcript here]
Act as a referring physician's assistant. Using ONLY the information from the provided clinical note, draft a formal referral letter to [Specialist's Name/Specialty, e.g., Dr. Smith, Cardiology].
RULES:
1. Extract the following from the note: Patient's presenting problem, pertinent history, key examination findings, relevant test results, my assessment, and the specific question for the consultant.
2. Do not add any information not explicitly present in the note.
3. If any required information for the letter is missing from the note, insert a placeholder like "[Insert relevant test result]".
4. The tone should be professional and concise.
[Paste de-identified clinical note here]
Generate a hospital discharge summary based ONLY on the following admission H&P, progress notes, and consultant reports.
RULES:
1. Structure the summary with these sections: Date of Admission, Date of Discharge, Admitting Diagnosis, Hospital Course, Condition at Discharge, Discharge Medications, Follow-up Appointments, and Pending Studies.
2. Extract all information directly from the provided texts. Do not infer or invent details.
3. If information for a section is missing (e.g., a pending lab result), state "[Pending results to be forwarded]".
4. Consolidate the hospital course into a brief, chronological narrative.
[Paste de-identified notes here]
Convert the "Plan" section of the following clinical note into a clear, simple After-Visit Summary for the patient. Use the 5th-grade reading level.
RULES:
1. Use only the information from the "Plan" section.
2. Organize the instructions with clear headings (e.g., "New Medications," "Activity," "Follow-Up").
3. Translate medical jargon into plain language (e.g., "take twice daily" instead of "BID").
4. Explicitly list symptoms that should prompt a call to the office or a visit to the ER.
[Paste "Plan" section of note here]
Draft a Letter of Medical Necessity for [Procedure/Medication] for a patient with [Diagnosis]. Use ONLY the information provided in the clinical notes below.
RULES:
1. Structure the letter to include: Patient history, diagnosis with ICD-10 code, the proposed treatment plan, and the clinical rationale.
2. Specifically extract and list treatments that have been tried and failed.
3. Directly quote phrases from the notes that support the medical necessity of the proposed treatment.
4. If supporting literature is mentioned in the notes, list the citations. Do not search for new literature.
5. If a critical piece of information is missing, use the placeholder "[Awaiting results of...]" or "[Clinician to add detail on...]".
[Paste relevant de-identified clinical notes here]
Act as a clinical analyst. Summarize the following de-identified patient chart into a one-page brief for a new physician.
RULES:
1. Create sections for: Active Problems, Chronic Conditions, Major Surgeries/Hospitalizations, Current Medications, and Allergies.
2. Extract information ONLY from the provided chart documents.
3. Present the information as bullet points under each heading.
4. Note any significant gaps in the record, such as a missing allergy status, with "[Record Incomplete]".
[Paste de-identified chart documents here]
Generate a SOAP note for a telehealth visit based ONLY on the transcript below.
RULES:
1. Follow all standard forced-extraction rules (use only transcript data, mark gaps with "[to complete]").
2. In the Objective section, explicitly state "Patient seen via video telehealth."
3. Document only the visual observations possible via video (e.g., "general appearance," "respiratory effort") and patient-reported findings (e.g., "patient reports temperature of...").
4. Explicitly state "Physical exam limited by virtual modality" and list any parts of a standard exam that were deferred (e.g., "Auscultation of lungs deferred.").
[Paste de-identified telehealth transcript here]
Act as a behavioral health scribe. From the session transcript below, generate a [BIRP/DAP] note.
RULES:
1. Use information exclusively from the transcript. Do not infer client thoughts or feelings not explicitly stated.
2. Structure the output into the correct sections (Behavior, Intervention, Response, Plan OR Data, Assessment, Plan).
3. If the client's statement is ambiguous, quote it directly in the Data/Behavior section rather than interpreting it.
4. The Intervention section must only describe the therapist's actions as documented in the transcript.
[Paste de-identified session transcript here]
5 AI Prompts for Patient Communication
These prompts help translate complex medical information into language patients can understand and act on.
Explain the medical condition [Condition Name, e.g., Type 2 Diabetes] to a newly diagnosed adult patient in simple, clear language (around a 6th-grade reading level).
RULES:
1. Use an analogy to explain the core mechanism of the disease.
2. Focus on what the patient can control.
3. Keep the tone reassuring but direct.
4. Include a section on why the recommended lifestyle changes and medications are important.
5. Limit the explanation to 250 words.
Draft a response to a patient portal message asking: "[Insert patient question, e.g., 'Can I take ibuprofen with my new blood pressure medicine?']".
RULES:
1. The response must be for informational purposes only.
2. It MUST include a disclaimer to call the office or seek urgent care for worsening symptoms.
3. Provide a direct answer to the question based on standard medical knowledge.
4. Keep the message concise (under 100 words) and friendly.
5. Do not provide any new diagnosis or treatment.
Translate the following test results into a plain-language summary for a patient.
RULES:
1. For each result, explain what was measured and what the result means (e.g., "Your 'bad cholesterol' or LDL is slightly high.").
2. Do not use numerical values unless you provide a simple reference range (e.g., "Your result was 110, and the goal is under 100.").
3. State the next step clearly (e.g., "Because of this result, we will continue your current medication and recheck in 6 months.").
4. Use a reassuring and non-alarming tone.
[Paste de-identified test results here]
Create a patient instruction sheet for the following medication: [Medication Name, Dose, Frequency].
RULES:
1. Use large, clear font with headings.
2. Include these sections: "What this medicine is for," "How to take it," "Common side effects," and "When to call the doctor."
3. Use simple icons or visuals if possible (e.g., a sun for morning, a moon for night).
4. Write instructions in plain language (e.g., "Take 1 pill in the morning with food.").
Generate a list of 5 frequently asked questions (FAQs) a patient newly diagnosed with [Condition Name] might have. Provide a simple, concise answer for each.
RULES:
1. The questions should cover diet, activity, medication, and prognosis.
2. Answers should be 2-3 sentences long and at a 6th-grade reading level.
3. Include a disclaimer that these are general answers and the patient should discuss specific questions with their doctor.
4 AI Prompts for Evidence & Literature Review
Use these prompts with AI search engines designed for clinical evidence, like OpenEvidence, or in general models to summarize provided text.
Summarize the following research abstract into a 3-bullet-point summary using the PICO framework.
RULES:
1. Bullet 1 (Population/Intervention): Who was studied and what was done?
2. Bullet 2 (Comparison/Outcome): What was the result compared to, and what was the main finding?
3. Bullet 3 (Conclusion): What is the key takeaway for clinical practice?
[Paste abstract text here]
Based ONLY on the two abstracts provided below, create a table comparing Treatment A and Treatment B for [Condition].
RULES:
1. The table should have three columns: Feature, Treatment A, and Treatment B.
2. Rows should include: Efficacy, Major Side Effects, and Dosing Frequency.
3. Extract information verbatim from the abstracts. Do not synthesize or infer conclusions not explicitly stated.
4. If information for a cell is not in the abstracts, write "Not mentioned.
What are the current [Year] [Organization, e.g., American Heart Association] guidelines for the management of [Condition, e.g., hypertension] in a patient with [Co-morbidity, e.g., chronic kidney disease]? Provide a summary of the key recommendations and a link to the source document.
Create a 10-slide presentation outline for a journal club discussion of the following research paper.
RULES:
1. Slide 1: Title, Authors, Journal.
2. Slide 2: Background & Clinical Question.
3. Slide 3: Study Design & Methods (PICO).
4. Slides 4-5: Key Results (include main tables/figures).
5. Slide 6: Study Strengths.
6. Slide 7: Study Limitations & Biases.
7. Slide 8: Discussion & Clinical Implications.
8. Slide 9: Do these findings change my practice?
9. Slide 10: Questions for Discussion.
[Paste full text or abstract of paper here]
4 AI Prompts for Coding & Billing
These prompts can help streamline administrative tasks, but all AI-suggested codes must be verified by a certified coder before submission.
Act as a medical coding assistant. Based ONLY on the clinical note below, suggest potential ICD-10 and CPT codes.
RULES:
1. List ICD-10 codes for each diagnosis mentioned in the "Assessment."
2. List CPT codes for all procedures and services performed during the visit (e.g., office visit level, tests performed, counseling time).
3. For each suggested code, provide the official description.
4. You MUST include the disclaimer: "These are suggestions only and must be verified by a certified coder based on the complete medical record and payer rules."
[Paste de-identified clinical note here]
Based on the 2023 E/M guidelines, create a summary of the Medical Decision Making (MDM) from the provided clinical note to support a [e.g., 99214] level of service.
RULES:
1. Extract and list the number and complexity of problems addressed.
2. Extract and list the amount and/or complexity of data reviewed and analyzed.
3. Extract and describe the risk of complications and/or morbidity or mortality of patient management.
4. Present this information in a structured format corresponding to the MDM table.
5. Do not add any information not present in the note.
[Paste de-identified clinical note here]
Create a script with key talking points for a peer-to-peer review to appeal a denial for [Procedure/Medication]. Use ONLY the information from the provided clinical notes.
RULES:
1. Start with a one-sentence summary: "I am calling to discuss the denial for [Patient Initials], who has a diagnosis of [Diagnosis] and for whom we have prescribed [Service]."
2. Create bullet points for: Clinical presentation, treatments tried and failed, and evidence-based rationale for the requested service.
3. Directly quote key findings from the notes.
4. End with a clear ask: "I am requesting you overturn this denial based on medical necessity."
[Paste relevant de-identified notes here]
Act as a Clinical Documentation Improvement specialist. Review the following clinical note and identify any diagnoses that lack the specificity required for accurate ICD-10 coding.
RULES:
1. For each non-specific diagnosis (e.g., "heart failure," "diabetes"), suggest what additional details might be needed (e.g., "Is the heart failure acute, chronic, or acute-on-chronic? Systolic or diastolic?", "Is the diabetes with or without complications?").
2. Present the findings as a list of queries for the physician.
3. Do not suggest codes, only opportunities to improve documentation specificity.
[Paste de-identified clinical note here]
4 AI Prompts for Practice Administration
AI can also assist with the business side of running a practice.
Create a 30-minute staff meeting agenda for a primary care practice.
The agenda should include the following topics:
- Review of last month's patient wait times.
- Update on the transition to the new patient portal.
- Open floor for staff feedback (10 minutes).
Assign a time limit to each agenda item.
Review the following patient feedback comments and identify the top 3 positive themes and top 3 areas for improvement.
RULES:
1. Categorize each piece of feedback (e.g., "wait time," "staff friendliness," "physician communication").
2. Count the number of comments in each category.
3. Summarize the most frequently mentioned positive and negative themes in bullet points.
4. Directly quote 1-2 representative comments for each theme.
[Paste anonymized patient feedback comments here]
Create a first-week onboarding checklist for a new Medical Assistant in our practice.
RULES:
1. Divide the checklist by day (Day 1, Day 2, etc.).
2. Include tasks for HR paperwork, system logins (EHR, portal), clinical workflow training (rooming patients, taking vitals), and introductions to key staff members.
3. For each task, include a checkbox and a space for the trainer's initials.
Draft a professional email to [Recipient, e.g., the entire clinical staff] about [Subject, e.g., an upcoming change to the on-call schedule].
The key points to include are:
- The new schedule will start on [Date].
- The reason for the change is [Reason].
- The updated schedule is attached.
Keep the tone professional and the message under 150 words.
What You Must NEVER Paste Into a Generic AI
It is critical to distinguish between secure, HIPAA-compliant AI platforms designed for healthcare and general-purpose AI tools like the public version of ChatGPT.
- Protected Health Information (PHI): Never paste any of the 18 HIPAA identifiers into a non-compliant AI. This includes names, dates, addresses, social security numbers, medical record numbers, and any other information that could be used to identify a patient.
- HIPAA and Business Associate Agreements (BAA): A compliant AI vendor will sign a BAA with your practice. This is a legal contract that obligates the vendor to protect PHI according to HIPAA rules. Without a BAA, you are liable for any data breach.
- De-identification is Hard: Truly de-identifying clinical text is difficult. A patient’s rare diagnosis combined with their city could be enough to re-identify them. The safest assumption is to treat all clinical data as PHI and only use it in BAA-covered platforms.
Tools like Freed AI are built specifically for this purpose, offering a BAA and a secure environment for clinical documentation. In contrast, enterprise platforms like Biofourmis focus on different AI applications like remote patient monitoring under health system-level agreements.
Freed AI
Best for solo clinicians who need a simple, self-serve ambient scribe with transparent pricing.
Best for solo clinicians who need a simple, self-serve ambient scribe with transparent pricing.
Freed AI is an AI medical scribe that works as a Chrome extension. As of September 2026, its pricing starts at $39/month for 40 notes, with an unlimited “Core” plan at $79/month. It offers a BAA and is designed for HIPAA compliance. Its strength is simplicity and speed for individual or small practice clinicians. It is not ideal for large health systems needing deep EHR integration, which is the domain of tools like Nuance Dragon Copilot.
- Price from
- From $39/mo (as of Sep 2026)
- Free tier
- 7-day trial, no permanent free tier
The Final Step: How to Verify Every AI-Generated Output
AI is a powerful assistant, not a replacement for clinical judgment. Every single piece of AI-generated output that enters a medical record must be reviewed and signed by a licensed clinician.
Your Verification Checklist:
- Read the Entire Note: Do not just skim the Assessment and Plan. Read the full HPI and Exam.
- Check for Hallucinations: Does the note mention a finding you didn’t observe or a historical detail the patient didn’t report? Delete it.
- Check for Omissions: Did the AI leave out a key pertinent negative or a significant detail from the plan? Add it.
- Verify Key Details: Double-check all medication dosages, frequencies, and follow-up intervals.
- Sign Your Name: Your signature attests that you have reviewed the note and take full responsibility for its content.
Adopting this workflow transforms AI from a potential liability into a powerful tool for reducing your administrative workload and reclaiming time for patient care. To learn more about how AI is reshaping medical practice, visit our AI for doctors and healthcare professionals hub.
Where to go next
Three routes, picked for what you just read.
What are the best AI prompts for writing SOAP notes?
The best prompts use a “forced-extraction” framework. Instead of a vague command, you provide the visit transcript and instruct the AI to *only* use the provided text, mark any missing information with [to complete], and flag any ambiguous phrases for clinician review. This minimizes the risk of hallucinations.
Can I use ChatGPT for medical documentation?
No, you should not use the public version of ChatGPT for medical documentation. It is not HIPAA-compliant, and pasting patient information into it is a data breach. Only use AI tools from vendors who will sign a Business Associate Agreement (BAA) and provide a secure, compliant platform.
What are “AI hallucinations” in medicine?
An AI hallucination is when the model generates information that is factually incorrect but presents it as if it were true. In a medical note, this could be a fabricated physical exam finding, an invented symptom, or an incorrect medication dose. These occur in up to 31% of AI-generated notes, making physician verification essential.
Do I still need to review AI-generated notes?
Yes, absolutely. The clinician is always legally and ethically responsible for the content of the medical record. Every AI-generated note must be thoroughly reviewed for accuracy, omissions, and hallucinations before you sign it. Think of the AI as a scribe, not as an autonomous author.
How can AI prompts reduce physician burnout?
Physician burnout is strongly linked to administrative tasks, particularly documentation. Well-designed AI prompts can automate the drafting of notes, letters, and summaries, saving hours of clerical work. This allows physicians to finish their charts faster, reduce “pajama time” spent on the EHR, and focus more on direct patient care.
Are there AI prompts for medical billing and coding?
Yes, you can use AI to suggest potential ICD-10 and CPT codes based on a clinical note. However, these suggestions must be verified by a certified coder. The AI can also help draft letters of medical necessity or summarize the medical decision-making to justify a specific E/M level.
Can AI help with patient communication?
Yes. You can use AI prompts to translate complex medical terminology into plain language for patient instructions, explain a new diagnosis using simple analogies, or draft responses to common patient portal questions. This can improve patient understanding and adherence while saving you time.
What is the difference between a generic AI and a medical AI?
A generic AI (like public ChatGPT) is trained on broad internet data. A specialized medical AI (like OpenEvidence or the models within Freed AI) is trained on a curated dataset of medical literature, clinical notes, and biomedical data. This domain-specific training generally leads to higher accuracy and lower risk for clinical tasks.
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