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Record W2153148973 · doi:10.1371/journal.pmed.0030487

Impact of Extended-Duration Shifts on Medical Errors, Adverse Events, and Attentional Failures

2006· letter· en· W2153148973 on OpenAlexafffund
Laura K. Barger, Najib Ayas, Brian E. Cade, John Cronin, Bernard Rosner, Frank E. Speizer, Charles A. Czeisler

Bibliographic record

VenuePLoS Medicine · 2006
Typeletter
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsVancouver General HospitalVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
FundersNational Institute for Occupational Safety and HealthCanadian Institutes of Health ResearchCenters for Disease Control and PreventionUniversity of British ColumbiaAgency for Healthcare Research and QualityBritish Columbia Lung AssociationNational Heart, Lung, and Blood InstituteBrigham and Women's Hospital
KeywordsConfidence intervalOdds ratioOddsDuration (music)MedicineAdverse effectPopulationDemographyPsychologyEmergency medicinePediatricsInternal medicineLogistic regressionEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: A recent randomized controlled trial in critical-care units revealed that the elimination of extended-duration work shifts (> or =24 h) reduces the rates of significant medical errors and polysomnographically recorded attentional failures. This raised the concern that the extended-duration shifts commonly worked by interns may contribute to the risk of medical errors being made, and perhaps to the risk of adverse events more generally. Our current study assessed whether extended-duration shifts worked by interns are associated with significant medical errors, adverse events, and attentional failures in a diverse population of interns across the United States. METHODS AND FINDINGS: We conducted a Web-based survey, across the United States, in which 2,737 residents in their first postgraduate year (interns) completed 17,003 monthly reports. The association between the number of extended-duration shifts worked in the month and the reporting of significant medical errors, preventable adverse events, and attentional failures was assessed using a case-crossover analysis in which each intern acted as his/her own control. Compared to months in which no extended-duration shifts were worked, during months in which between one and four extended-duration shifts and five or more extended-duration shifts were worked, the odds ratios of reporting at least one fatigue-related significant medical error were 3.5 (95% confidence interval [CI], 3.3-3.7) and 7.5 (95% CI, 7.2-7.8), respectively. The respective odds ratios for fatigue-related preventable adverse events, 8.7 (95% CI, 3.4-22) and 7.0 (95% CI, 4.3-11), were also increased. Interns working five or more extended-duration shifts per month reported more attentional failures during lectures, rounds, and clinical activities, including surgery and reported 300% more fatigue-related preventable adverse events resulting in a fatality. CONCLUSIONS: In our survey, extended-duration work shifts were associated with an increased risk of significant medical errors, adverse events, and attentional failures in interns across the United States. These results have important public policy implications for postgraduate medical education.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.025
GPT teacher head0.323
Teacher spread0.298 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations528
Published2006
Admission routes2
Has abstractyes

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