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Record W2130324498 · doi:10.1258/shorts.2010.010007

The World Health Organization's ‘Surgical Safety Checklist’: should evidence-based initiatives be enforced in hospital policy?

2010· article· en· W2130324498 on OpenAlexaboutno aff
Niroshan Sivathasan, Krzysztof Rakowski, Bernard F. Robertson, Lavnya Vijayarajan

Bibliographic record

VenueJRSM Short Reports · 2010
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsnot available
Fundersnot available
KeywordsChecklistMedicineQuarter (Canadian coin)Government (linguistics)Patient safetyHealth careMedical emergencyFamily medicineNursingMedical educationPsychologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the awareness and voluntary usage of the World Health Organization's Surgical Safety Checklist (WHO SSC), just prior to its mandatory implementation. DESIGN: Questionnaire-based, prospective, telephone survey. SETTING: Patients are exposed to systematic risks and principles of surgical safety are inconsistently applied even in sophisticated settings. The evidence-based WHO SSC addresses shortfalls to promote patient safety. It was formally introduced in the United Kingdom in January 2009 and became a mandatory preoperative requirement in all hospitals from February 2010. PARTICIPANTS: Two hundred and thirty-eight hospitals, both private and government-run, in the UK. MAIN OUTCOME MEASURES: Appreciation among senior theatre personnel as to the existence, implementation and usage of the WHO SSC concept. RESULTS: Almost all had heard of the SSC, but in only two-thirds of hospitals was its use mandatory. Where the SSC was not compulsory, 80% were using it informally or sporadically. One-quarter of senior theatre personnel in hospitals without compulsory use indicated they did not know or that their department did not plan on using the checklist in the next six months, despite the deadline for implementation. CONCLUSIONS: If the SSC is to optimize safety, then greater education and awareness is required.

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 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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.438
Teacher spread0.371 · 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 teacher head, not a consensus.

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

Citations32
Published2010
Admission routes1
Has abstractyes

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