Assessment of Patient Safety Competencies among Critical Care Nurses
Bibliographic record
Abstract
Background: Quality assurance programs have been implemented worldwide to address nursing errorsand improve patient safety. However, despite these efforts, threats to patient safety remain a majorconcern and contribute to the overall crude death rate. The World Health Organization (2018) reportedthat 42.7 million medical errors occurrences annually during hospitalizations. These errors are identifiedas the 14th leading cause of death and morbidity worldwide(Mohanty et al., 2018). Aim: This study aimsto assess levels patient safety competencies among critical care nurses. Research Question: What is thelevel of patient safety competencies among critical care nurses? Research design: Descriptive researchdesign was used to carry out this study. Setting: This study was conducted at all critical units ofAlexandria Main University Hospital. Subjects: All nurses (N=289) who are working in the previousmentioned units were recruited to collect the required data. Tools: One tool is used to collect thenecessary data Patient Safety Competency Self-Evaluation Questionnaire (PSCSE). Results: The highestpercentage of nurses (72.7% ) had high level of patient safety competencies. Conclusion: This studyhighlights that nurses exhibit a moderate to high level of patient safety competencies. By possessing thenecessary competencies, healthcare professionals can identify, prevent, and manage medical errors andadverse events, contributing to a culture of safety within the healthcare system. Recommendations: Basedon the findings of this study the policy makers and nurse leaders should fund training programs byallocating funding for the development and implementation of training programs that focus on patientsafety competencies. Mandate continuing education by requiring ongoing professional development inpatient safety as part of licensure renewal for nurses, ensuring continuous improvement in these criticalareas. Promote a safety culture by encouraging healthcare organizations to cultivate a culture of safety,where patient safety is core values supported by leadership and embedded in daily practices. Standardizecompetency assessments through establish standardized tools and methods for regularly assessing nurses'patient safety competencies, ensuring consistency and accountability
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".