Dimensions of Patient Safety Culture in Family Practice
Bibliographic record
Abstract
Safety culture has been shown to affect patient safety in healthcare. While the United States and United Kingdom have studied the dimensions that reflect patient safety culture in family practice settings, to date, this has not been done in Canada. Differences in the healthcare systems between these countries and Canada may affect the dimensions found to be relevant here. Thus, it is important to identify and compare the dimensions from the United States and the United Kingdom in a Canadian context. The objectives of this study were to explore the dimensions of patient safety culture that relate to family practice in Canada and to determine if differences and similarities exist between dimensions found in Canada and those found in previous studies undertaken in the United States and the United Kingdom. A qualitative study was undertaken applying thematic analysis using focus groups with family practice offices and supplementary key stakeholders. Analysis of the data indicated that most of the dimensions from the United States and United Kingdom are appropriate in our Canadian context. Exceptions included owner/managing partner/leadership support for patient safety, job satisfaction and overall perceptions of patient safety and quality. Two unique dimensions were identified in the Canadian context: disclosure and accepting responsibility for errors. Based on this early work, it is important to consider differences in care settings when understanding dimensions of patient safety culture. We suggest that additional research in family practice settings is critical to further understand the influence of context on patient safety culture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".