Assessment of Patient Safety Culture among Healthcare Providers
Bibliographic record
Abstract
PURPOSE: Patient safety is an important element in ensuring quality of patient care and accreditation. This study aimed to assess the perception of patient safety culture among the healthcare providers; assess the areas of strength and improvement related to patient safety culture; and assess the relationship between patient safety culture and demographic variables of the sample. METHOD: Descriptive correlational design was employed in this study. Data was collected using the Hospital Survey on Patient Safety Culture (HSPSC). A stratified random sample of 158 healthcare providers from the Diwan of Royal Court Health Complex in Muscat participated in this study. RESULTS: The findings of this study indicated that most of the participants responded positively to the HSPSC items. The average percentage of positive responses was 56.4%. The major areas of strength were “teamwork within department,” “feedback and communication about errors,” and “organizational learning-continuous improvement” (83%, 77%, & 75%; respectively). The major areas of improvement were “frequency of events reported,” “teamwork across departments,” “non-punitive response to errors” and “overall perception of PS” (34%, 42%, 45% & 47%; respectively). Significant differences found were across “patient contact” characteristic [t (156) = 2.142, p = .034]; across “work specializations” [F (3, 154) = 2.84, p = .04]; and across “years of experience at the institution” [F (4, 153) = 4.86, p = .004]. CONCLUSION: A culture that is safe for healthcare providers to work is paramount to minimize adverse events and save patients’ lives. The findings of this study provide a foundation for further interventions to improve 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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".