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AI medical summary verification checklist, by failure type

By Ahmed Jemaa, Co-Founder and CEO of Medrecords AI. Updated 2026-11-12.

Answer in brief: verify an AI summary in 5 stages: check the file, check every relied-on line, sample the rest, search for what is missing, and sweep for negatives, hedges, dates and sides. Tick what you have done below; the checklist shows which of the 10 failure types are still uncovered, and ends with a note you can paste into your file.

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.

How this checklist differs from a read-through

Most checklists list good habits. This one maps each check to the failure types it catches, so you can see the gap when you skip a step. Skipping the reverse spot check, for example, leaves omissions uncovered no matter how many citations you open, and skipping the cue sweep leaves every negation error open. Nothing you tick is saved or sent; it runs in your browser.

The checklist

Stage 1. The file, before you read the summary Name, date of birth and record number match on the first page of every source.Catches: wrong patient Duplicate pages are marked, and 2 visits with identical text and different fax dates are treated as 1.Catches: wrong date The list of records the file mentions but doesn't contain is reviewed: orders without results, referrals without notes.Catches: omission, invented fact

Stage 2. Every line you rely on Each relied-on line opened at its cited page, and the page says it.Catches: invented fact Each result traced to a result report, not an order or a later mention.Catches: invented fact The speaker kept: patient report, clinician finding, or another doctor's view as reported.Catches: attribution error Every dose that matters checked against the page image, with units and combination products read correctly.Catches: dose or unit error

Stage 3. A random sample of the other lines A random sample checked, sized with the sampling calculator, and any failure expanded to its whole section.Catches: invented fact, and shows how far to trust the rest Handwritten and poor-scan pages sampled separately from typed pages.Catches: wrong side or level, dose misreads

Stage 4. What the summary left out A reverse spot check: random source pages read, and their key facts found in the summary.Catches: omission Every page dated before the injury or event read in full.Catches: omission of prior history

Stage 5. Cue sweep on the source Negation cues searched, and each negative on a relied-on finding kept negative.Catches: lost negative Hedge cues searched, "rule out" kept apart from "ruled out", and no diagnosis dated before it appears without a hedge.Catches: hedge dropped Each key event carries its date of service or collection date, never a fax, print or signature date; addenda dated separately.Catches: wrong date Left, right, bilateral and spinal levels on relied-on findings match the page and the first visit.Catches: wrong side or level "Unchanged", "as above" and repeated paragraphs found, and conflicts between notes and forms flagged, not resolved silently.Catches: copy-forward echo

A verification note for your file

If a summary feeds a report you sign, record what you checked. It costs 2 minutes and answers the question you may get at deposition or peer review: how do you know the summary was right? Copy and fill in:

Verification of AI-assisted record summary
File: [case or claim number]   Source pages after duplicates removed: [n]
Tool and version or date run: [tool, date]
Relied-on lines checked against source pages: [n of n]   Failures: [n, with pages]
Random sample of other lines: [n]   Failures: [n]   Bound: [rate ruled out at 95%]
Reverse spot check: [n] random source pages read   Facts missing from summary: [n]
Pages before the date of injury read in full: [yes/no, page range]
Cue sweep (negation, hedge, date, side, dose): [done/not done]
Records referenced but not in the file: [list, or none]
Conflicts flagged (notes vs forms, sources vs sources): [list]
Checked by: [name], [date]

The note says what was checked, not that the summary is perfect. If your jurisdiction or client requires you to disclose AI use in a report, check its rules; this note is a record, not a disclosure.

How long the checklist takes

We don't have a published benchmark for verifying medical-legal summaries, so we won't give you a number. 2 data points frame it. A pilot study by Mendel and UMass Amherst reported that a trained clinician took 92 minutes on average to label 1 AI-generated summary of a medical note for errors (Clinical Trials Arena, via Yahoo Finance, 2024). That is roughly the cost of checking everything line by line. The checklist is built to avoid that cost by checking every relied-on line and sampling the rest. On a typical file, stage 2 and stage 4 take the most time; stages 1 and 5 are mostly searches.

Questions about the checklist

Do I need every check on every file?

For a summary behind a report you sign, yes. For a screening read to decide whether to take a case, stages 1, 2 and the pre-injury read in stage 4 cover the failures most likely to change the decision.

Does this checklist replace my own review of the records?

No. It checks a summary against its source. Your opinion still comes from your review of the records that matter, read in full.

Is my progress saved?

No. The ticks live in your browser tab and disappear when you close it. Nothing is sent anywhere.