Guide-linked quiz · Medium Level
AI-Drafted Replies to Patient Portal Messages Quiz
Tests what health system studies found on time savings and burnout, how automation bias affects draft review, and what safeguards and disclosure rules apply.
Question 1 of 8
What did the 2024 Stanford study by Garcia and colleagues find about AI-drafted inbox replies?
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- What did the 2024 Stanford study by Garcia and colleagues find about AI-drafted inbox replies?
- Drafts cut reply time in half
- Clinicians used drafts for nearly every message
- Task load and burnout scores fell, but there was no significant time savings
- The program was shut down for patient harm
- Why does the Ayers 2023 study not prove AI drafts beat physicians in real clinical inboxes?
- It compared answers to public questions on Reddit, not messages from patients in a health system
- It used only nurses as evaluators
- It measured only spelling errors
- It tested an image model
- The UC San Diego study by Tai-Seale and colleagues found which pattern?
- Shorter replies and faster sending
- No drop in reply time, longer time reading messages, and longer replies
- Complete elimination of nurse triage
- Drafts were sent automatically without review
- A physician leaves a fluent draft mostly unchanged even though it contains an error. What is this tendency called?
- Alert fatigue
- Retrieval failure
- Disparate impact
- Automation bias
- A draft tells a patient to double a blood pressure medication, missing yesterday's high potassium result. What risk does this show?
- Missing context, because the model sees only what the prompt includes
- A problem with the patient portal's font
- The model working too slowly
- A billing code mismatch
- Which safeguard sends high-risk messages away from AI drafting?
- Making replies longer
- Removing the start-blank option
- Excluding categories such as test results and possible emergencies from drafting and routing them to triage
- Sending drafts automatically after five minutes
- What does California's AB 3030 generally require?
- A ban on all AI in healthcare
- Disclosure of AI-generated patient communications unless a licensed provider reviewed them
- Federal FDA approval for every draft
- Patients to write their own replies
- Which monitoring practice best catches drafts that were sent without real review?
- Counting total portal logins
- Measuring server response time
- Tracking the number of patients enrolled
- Logging how much clinicians edit drafts and reviewing a sample of sent messages with minimal changes
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