Nurse Level of Education, Quality of Care and Patient Safety in the Medical and Surgical Wards in Malaysian Private Hospitals: A Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Nursing knowledge and skills are required to sustain quality of care and patient safety. The numbers of nurses with Bachelor degrees in Malaysia are very limited. This study aims to predict the impact of nurse level of education on quality of care and patient safety in the medical and surgical wards in Malaysian private hospitals. METHODOLOGY: A cross-sectional survey by questionnaire was conducted. A total 652 nurses working in the medical and surgical wards in 12 private hospitals were participated in the study. Multistage stratified simple random sampling performed to invite nurses working in small size (less than 100 beds), medium size (100-199 beds) and large size (over than 200) hospitals to participate in the study. This allowed nurses from all shifts to participate in this study. RESULTS: Nurses with higher education were not significantly associated with both quality of care and patient safety. However, a total 355 (60.9%) of respondents participated in this study were working in teaching hospitals. Teaching hospitals offer training for all newly appointed staff. They also provide general orientation programs and training to outline the policies, procedures of the nurses' roles and responsibilities. This made the variances between the Bachelor and Diploma nurses not significantly associated with the outcomes of care. CONCLUSIONS: Nursing educational level was not associated with the outcomes of care in Malaysian private hospitals. However, training programs and the general nursing orientation programs for nurses in Malaysia can help to upgrade the Diploma-level nurses. Training programs can increase their self confidence, knowledge, critical thinking ability and improve their interpersonal skills. So, it can be concluded that better education and training for a medical and surgical wards' nurses is required for satisfying client expectations and sustaining the outcomes of patient care.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".