It was reported that during a laparoscopic low anterior resection, while performing rectal dissection, there were jaw-related issues: difficulty closing the jaw, inability to close, and inability to open the jaw inside the abdominal cavity. The handle and cartridge were replaced to resolve the issue. There was no patient injury.
MAUDE Signal Explorer
Surgical Staplers · A Human Factors Lens
An independent demo by Kennedy DeSousa
Post-market surveillance, read like a human factors engineer
What 199,000+ adverse-event reports say about surgical staplers
HFE teams mostly look forward — formative studies, validation, design controls. But the FDA's MAUDE database is a backward-looking goldmine: real use errors, in real ORs, in the reporters' own words. This page mines the public openFDA device-event API for surgical staplers (product codes GAG & GDW) and shows how post-market signals can seed formative-study hypotheses.
199,444
Total reports in MAUDE
158,242
Malfunctions
38,972
Injuries
1,384
Deaths
Live from openFDA · dataset last updated 2026-11-04
Reports per year — and the hidden-database story
For years, stapler manufacturers could route adverse events through FDA's “Alternative Summary Reporting” program — tens of thousands of malfunction reports that never appeared in public MAUDE. After investigative reporting surfaced the practice, FDA ended ASR in mid-2019 and the hidden reports flooded into the public record. The lesson for anyone reading this data: the shape of a reporting curve reflects policy as much as risk.
A use-error lens on the narratives
Event narratives often encode perception, cognition, or action failures — the raw material of use-related risk analysis. These phrase counts are a deliberately simple heuristic for surfacing candidate reports to read, not a validated classifier:
Failed to fire
1,062
reports mentioning “failed to fire”
Boundary caseOften entangled with loading, positioning, or tissue-thickness selection — but a jammed mechanism with perfect technique is a device failure. Run the perfect-device test before claiming it.
Difficult to remove
998
reports mentioning “difficult to remove”
ActionPost-fire release problems often involve technique interaction with the release design
Misfire
863
reports mentioning “misfire”
ActionFrequently involves firing sequence or reload handling — execution of a known procedure
Inadvertent action
499
reports mentioning “inadvertently”
ActionMarker for unintended activation or release — classic slip during execution
Labeled 'user error'
179
reports mentioning “user error”
Reporter-attributedHow reporters themselves attribute the event — attribution, not analysis; treat as a pointer, not a classification
Wrong size
24
reports mentioning “wrong size”
PerceptionCartridge/tissue mismatch — the user didn't detect or judge the tissue thickness the design asked them to assess
Which analysis owns this cause?
A signal only becomes a use-relatedrisk when the initiating event is a human perceiving, deciding, or acting while the device performs to specification. Device deviates from spec → that's a failure mode for the FMEA family. Two tests sort every narrative:
1 · The perfect-device test
Would this scenario still occur with a flawlessly functioning device? Yes → use-related analysis. No— it requires a malfunction → failure-mode analysis. A “failed to fire” narrative can land either way, which is why it's tagged a boundary case above.
2 · The initiating-event test
When a chain involves both a failure and a user, ask what starts it. The failure itself belongs to the failure-mode analyses — but the user-response task the failure creates (respond, recover, replace) is use-related risk in its own right.
The latest reports, in the reporters' own words
The most recent stapler narratives in MAUDE, with use-error phrases highlighted. Reading raw narratives is where the method earns its keep — counts point you somewhere; the words tell you why.
It was reported during a total gastrectomy, during esophagojejunostomy, only the esophageal mucosa slipped in and bleeding occurred. To resolve the issue, manual suturing was performed.
It was reported that during a da Vinci-assisted Esophagectomy surgical procedure, the SureForm 45 Stapler instrument jaws would not open after the 4th staple. The procedure was completed. No known impact or patient consequence was reported.\\Intuitive Surgical, Inc. (ISI) followed up with the initial reporter and obtained the following additional information: The customer was not able to open the jaws during the procedure. The customer was able to use another instrument to spread open the jaws. There were no jaws clamped onto the tissue when the issue occurred. There were no adverse effects as a result of the jaws not being able to open.
According to the reporter, during the pyloric gastrectomy while cutting off duodenal section, stapler did not fire. A new reload was used. There was no patient injury.
According to the reporter, during the procedure, when setting up, the connection was not recognized, and after several attempts it was recognized, but it was then marked as used already. The reload was replaced to resolve the issue. There was no patient injury. PL10: Medtronic's initial evaluation found that the cartridge was observed to not be seated properly during visual inspection.
Why this matters for HFE teams
1 · Signal
Trend breaks and phrase clusters point to where users struggle — before your own study budget is spent.
2 · Hypothesis
Each recurring narrative pattern (“wrong size,” “failed to fire”) becomes a candidate use error for task analysis and PCA classification.
3 · Study design
Formative scenarios and IFU probes get grounded in documented field failures instead of conference-room guesses.
4 · Risk file
Confirmed patterns flow into the use-related risk analysis — recalibrating severity and likelihood on existing rows, seeding new ones, and tracing each use-error chain to the hazards the top-level risk file owns.
Limitations — read before drawing conclusions
- MAUDE has no denominator. Report counts can't be turned into rates — procedure volumes aren't in the data, so more reports ≠ more dangerous.
- Reporting is biased and incomplete. Underreporting is well documented; media attention, litigation, and policy changes (see the ASR story above) all move the curve.
- Keyword matching is a heuristic. Phrase counts surface candidates for human reading. A validated use-error classification needs trained reviewers and a coding scheme (e.g., PCA taxonomy) with reliability checks.
- Duplicates and follow-ups exist. The same event can generate multiple MDRs; no deduplication is attempted here.
- Narratives are secondhand. Most are written by manufacturers from user communications, with their own framing incentives.