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International Perspectives on Modifications to the Surgical Safety Checklist

2023· article· en· W4379599308 on OpenAlexafffundabout
Nathan Turley, Meagan Elam, Mary Brindle

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsSnowball samplingChecklistMedicineNursingMedical educationQualitative researchFamily medicinePsychology

Abstract

fetched live from OpenAlex

Importance: Modification of the World Health Organization's Surgical Safety Checklist (SSC) is a critical component of its implementation. To facilitate the SSC's use, it is important to know how surgical teams modify their SSCs, their reasons for making modifications, and the opportunities and challenges teams face in SSC tailoring. Objective: To study SSC modifications in high-income hospital settings in 5 countries: Australia, Canada, New Zealand, the United States, and the United Kingdom. Design, Setting, and Participants: This qualitative study used semistructured interviews based on the survey used in the quantitative study. Each interviewee was asked a core set of questions and various follow-up questions based on their survey responses. Interviews were conducted from July 2019 to February 2020 in person and online using teleconferencing software. Surgeons, anesthesiologists, nurses, and hospital administrators from the 5 countries were recruited through a survey and snowball sampling. Main Outcomes and Measures: Interviewees' attitudes and perceptions on SSC modifications and their perceived impact on operating rooms. Results: A total of 51 surgical team members and hospital administrators from the 5 countries were interviewed (37 [75%] with >10 years of service; 28 [55%] women). There were 15 (29%) surgeons, 13 (26%) nurses, 15 (29%) anesthesiologists, and 8 (16%) health administrators. Five themes emerged concerning the awareness and involvement in SSC modifications; reasons for modifications; types of modifications; the outcomes of modifications; and perceived barriers to SSC modifications. Based on the interviews, some SSCs may go many years without being revisited or modified. SSCs are modified to ensure they address local issues and standards of practice and that they are fit for purpose. Modifications are also made following adverse events to reduce the risk of reoccurrence. Interviewees described adding, moving, and removing elements from their SSCs, which increased their sense of ownership in their SSC and participation in its performance. Some barriers to modification included leadership and the SSC's inclusion in hospitals' electronic medical record. Conclusions and Relevance: In this qualitative study of surgical team members and administrators, interviewees described addressing contemporary surgical issues through various SSC modifications. The process of SSC modification may improve team cohesion and buy-in in addition to providing opportunities for teams to improve patient safety.

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)0.044
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0090.022
Scholarly communication0.0110.010
Open science0.0020.009
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0060.001

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 head0.105
GPT teacher head0.453
Teacher spread0.348 · 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 designNot applicable
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

Citations13
Published2023
Admission routes3
Has abstractyes

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