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Record W2155494252 · doi:10.12927/hcq.2013.19604

Patient Safety Culture Improvement Tool: Development and Guidelines for Use

2008· article· en· W2155494252 on OpenAlex

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.

Bibliographic record

VenueHealthcare Quarterly · 2008
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsSafety cultureOrganizational culturePatient safetyMaturity (psychological)WorkloadProcess managementReliability (semiconductor)Best practiceHealth careKnowledge managementProcess (computing)Capability Maturity ModelDimension (graph theory)Operations managementComputer scienceBusinessPsychologyEngineeringManagementPublic relationsPolitical science

Abstract

fetched live from OpenAlex

The Patient Safety Culture Improvement Tool (PSCIT) was developed to assist healthcare organizations in identifying practical actions to improve their culture. This article describes the development process of the PSCIT and provides a guide to using the PSCIT. The tool is based on a safety culture maturity model, which describes five stages of cultural evolution, from pathological to generative. The PSCIT consists of nine elements that cover five patient safety culture dimensions, namely, leadership, risk analysis, workload management, sharing and learning and resource management. Each element describes the systems in place at each level of maturity, enabling organizations to identify their current level of maturity and actions to move to the next level. The PSCIT should be used with caution as there is currently a lack of reliability and validity data.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
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 head0.186
GPT teacher head0.472
Teacher spread0.286 · 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