How to change nurses’ behavior leading to medication administration errors using a survey approach in United Christian Hospital
Bibliographic record
Abstract
Background: Medication administrations errors (MAEs) occur frequently in the world. Preventive measures have been extensively studied, but there is very limited literature considering nurses’ behavior leading to medication administration errors in hospitals. Objectives: This study aimed to change nurses’ behavior so as to reduce MAE rate. The objective of this study was to study the phenomenon of nurses’ behavior during medication administration and to infer these behaviors that might cause MAE. The secondary outcome aimed to evaluate the effectiveness of existing preventive measures. Methods: A convenience sampling design was employed to recruit around 1600 qualified nurses to participate in 6 identical surveying forums where a self-reported questionnaire was filled by participants under guidance led by the first author between August 2013 and September 2013. Results : There is a significant decreasing trend of MAE from the peak at 0.61 to the current 0.22 per 1,000 occupied patient bed days after the surveying forums were organized. A variety of inappropriate behaviours of medication administration was identified. Most of them were found significantly associated with MAE. Length of time nurses have been working was thought to be an important factor to lead to MAE due to complacency and poor supervision. Other possible factors such as knowledge deficits, poor communication and poor speak-up culture were associated with MAE. Conclusion: Risk of MAEs is inherent in medication administration, and if not properly managed, incidents will happen. Incidents will jeopardize nurses’ work performance, influence the patient safety and sustainability of the relationship between nurses and patients. In this study, various risks of nurses’ behaviour in medication administration have been revealed. The surveying forum might be a good way for nurses to self-evaluate their behavior and to perform proper ways of medication administration. Although there are different preventive measures implemented, information is not reached at nurses. The nursing implications were recommended to uphold safety of nursing behavior from personal to corporate level.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".