Staff attitudes about event reporting and patient safety culture in hospital transfusion services
Bibliographic record
Abstract
BACKGROUND: Little is known about how transfusion service staff view issues pertaining to event reporting and patient safety. The goal of this study was to assess transfusion service staff attitudes about these issues. STUDY DESIGN AND METHODS: A survey was developed and administered to 945 transfusion service staff from 43 hospital transfusion services in the United States and 10 in Canada. The overall response rate was 73 percent (693 responses), with a mean of 15 respondents per site. RESULTS: While events resulting in patient harm are reported (91%) as well as mistakes not corrected that could cause harm (79%), less than one-third of respondents report deviations from procedures with no apparent potential to harm (31%) and mistakes that staff catch and correct on their own (27%). Staff indicated that the main reasons mistakes happen are interruptions (51%) and staff in other departments not knowing or understanding proper procedures (49%). Staff had overall positive attitudes about event reporting, but a significant minority were afraid of punitive consequences. Most were positive about their supervisor's safety actions and believed that their transfusion service tries to identify causes of mistakes. Only 31 percent, however, agreed that nursing staff would work with the transfusion service to reduce mistakes. CONCLUSION: Overall, the transfusion services had very positive attitudes about event reporting and safety culture. Transfusion services do well recording events that result in patient harm or have the potential for harm, but there is a need to increase reporting of deviations from procedures and mistakes that staff catch and correct on their own. In addition, there are a few areas of safety culture that warrant improvement, particularly the transfusion service's work relationship with nursing staff. The study provides useful descriptive information about how staff view event reporting and safety-related issues and identifies strengths and areas for improvement.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".