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Medical Records Summary AI

Glossary: terms for AI summary errors and checks

By Ahmed Jemaa, Co-Founder and CEO of Medrecords AI. Updated .

In brief: 18 terms used on this site, defined for a physician checking an AI summary of a record file. Each definition says what the term means in practice and where it comes up.

Limits: We can't vouch for any tool's error rate on your files: the studies we cite measured other tasks and other models, and vendor features are as each vendor's site stated on the capture date.

Error types

Hallucination
A statement in an AI output that the source doesn't support: an invented finding, date, dose or event. In record summaries the riskiest kind is plausible, such as the result of a test that was ordered but never resulted. See failure modes.
Omission
A fact in the source that matters to the question but is missing from the summary. The most common error in the studies on the evidence page, and the 1 a read-through can't find.
Negation error
A negated finding stated as present, or the reverse: "denies numbness" summarized as "numbness". 30% of hallucinated sentences in the 2025 npj Digital Medicine study were negations.
Hedge
A word that marks clinical uncertainty: rule out, possible, probable, cannot exclude, suspicious for. A dropped hedge turns a differential into a diagnosis. Not to be confused with "ruled out", which means excluded.
Attribution error
A summary that changes who said something: the patient's report stated as a clinical finding, or a patient's account of another doctor's advice stated as that doctor's recommendation.
Copy-forward
EHR text carried from an earlier note into a later 1. A summary that trusts the later note can report a stale plan, exam or work status as current. In a 2022 study, 50.1% of note text at 1 health system was duplicated from earlier text.
Co-mingled records
Pages from another patient inside a record production, often with a similar name or the same facility and date. Any summarizer that reads them as your patient's adds their diagnoses to the history.
Laterality
Which side of the body a finding is on. Laterality errors (right for left) come from OCR, stray lines in a note or co-mingled pages.

Dates

Date of service
The date an encounter happened. The date to use for a visit in a summary, as opposed to fax, print, dictation or signature dates. See the 12 date types.
Addendum
Text added to a note after it was first written, with its own date. What an addendum says wasn't known at the original visit.

Citations and checks

Page citation
A pointer from a summary line to the source page it came from. It proves a page exists, not that the page supports the line. See citation checks.
Citation granularity
How precisely a citation points: to a whole document, to a page, or to a highlighted sentence. Finer granularity makes each check faster.
Upper bound
The highest error rate a random sample rules out at a stated confidence. 0 failures in 59 random lines gives a 95% upper bound of 5.0%. Try the sampling calculator.
Reverse spot check
Sampling the source instead of the summary: read random source pages and confirm their key facts appear in the summary. The sampling method that can find omissions.
Deduplication
Finding and setting aside repeated pages before a summary is built, so 3 copies of 1 visit don't read as 3 visits.
OCR
Optical character recognition: turning a scanned image into text. OCR errors on doses, sides and dates enter a summary before any language model sees the page.

Privacy terms

PHI
Protected health information under HIPAA. Real record files contain it; the synthetic test file on this site doesn't.
BAA
Business Associate Agreement: the HIPAA contract a vendor signs before it handles PHI for you. Sign it before uploading any real record to a summary tool.

Questions about these terms

Is a hallucination the same as an error?

No. A hallucination is 1 kind of error, where the output says something the source doesn't. Omissions, wrong dates and lost negatives are errors too, and some come from the file rather than the model.

What does "faithful" mean for a summary?

That every statement is supported by the source. A faithful summary can still be wrong about the patient if the source itself is wrong, duplicated or from another patient.