MétaCan
Menu
Back to cohort
Record W4409319873 · doi:10.1186/s13037-025-00432-4

Wrong-site, wrong-procedure, and retained foreign object events in out-of-hospital settings: analysis of closed medico-legal complaints in Canada (2012–2021)

2025· article· en· W4409319873 on OpenAlex
Omar Hajjaj, Joanna Zaslow, Reem El Sherif, Diane L Héroux, Richard Mimeault, Jacqueline H. Fortier, Gary Garber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePatient Safety in Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicHemostasis and retained surgical items
Canadian institutionsCanadian Medical Protective AssociationUniversity of TorontoUniversity of OttawaCARE CanadaQueen's University
Fundersnot available
KeywordsMedicineSurgeryGeneral surgery

Abstract

fetched live from OpenAlex

BACKGROUND: Surgical sentinel events (SSEs) are serious safety incidents associated with significant patient harm and medico-legal consequences for healthcare teams and institutions. SSEs include wrong-site surgeries, wrong procedures, and unintentional retention of foreign objects. SSEs occur in hospitals and out-of-hospital operating spaces (physician offices or ambulatory surgical centres). It is unclear how the resource constraints and workflow differences of an out-of-hospital setting contribute to SSEs. METHODS: We conducted a retrospective review and descriptive content analysis of all out-of-hospital SSEs reported to the Canadian Medical Protective Association (CMPA) between 2012 and 2021. Medico-legal files, medical records, and peer expert opinions were analyzed to identify the contributing factors to out-of-hospital wrong-site, wrong-procedure, and retained-object SSEs. RESULTS: A total of 276 medico-legal complaints involved a wrong-site, wrong-procedure or retained-object SSE, of which 24 (24/276; 9%) occurred out of hospital. Only twenty of these out-of-hospital complaints were included in the qualitative content analysis. We identified five main contributing factor categories to out-of-hospital SSEs. These categories included (1) incomplete preoperative verification, (2) inadequate intraoperative surgical counts, (3) insufficient review of patient medical records, (4) surgery performed without the necessary resources, and (5) administrative errors or office disorganization. Half of the complaints were assigned more than one contributing factor. The majority of out-of-hospital SSEs (19/20; 95%) resulted in an unfavourable outcome for the operating physician and most (18/20; 90%) required additional healthcare resources to resolve or mitigate the consequences of the SSE. CONCLUSIONS: Recognizing the contributing factors to an out-of-hospital SSE enables targeted improvements in facility protocols to support patient safety. Some factors identified in this dataset overlap with hospital-based contributing factors previously identified in literature (incomplete preoperative verification and inadequate surgical counts), whereas other novel factors are associated with the practice environment of an out-of-hospital setting (resource constraints, office disorganization). Addressing the identified contributing factors may mitigate the risk of SSEs in all facilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.242
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it