An interprofessional approach to improving paediatric medication safety
Bibliographic record
Abstract
BACKGROUND: Safe drug prescribing and administration are essential elements within undergraduate healthcare curricula, but medication errors, especially in paediatric practice, continue to compromise patient safety. In this area of clinical care, collective responsibility, team working and communication between health professionals have been identified as key elements in safe clinical practice. To date, there is limited research evidence as to how best to deliver teaching and learning of these competencies to practitioners of the future. METHODS: An interprofessional workshop to facilitate learning of knowledge, core competencies, communication and team working skills in paediatric drug prescribing and administration at undergraduate level was developed and evaluated. The practical, ward-based workshop was delivered to 4th year medical and 3rd year nursing students and evaluated using a pre and post workshop questionnaire with open-ended response questions. RESULTS: Following the workshop, students reported an increase in their knowledge and awareness of paediatric medication safety and the causes of medication errors (p < 0.001), with the greatest increase noted among medical students. Highly significant changes in students' attitudes to shared learning were observed, indicating that safe medication practice is learnt more effectively with students from other healthcare disciplines. Qualitative data revealed that students' participation in the workshop improved communication and teamworking skills, and led to greater awareness of the role of other healthcare professionals. CONCLUSION: This study has helped bridge the knowledge-skills gap, demonstrating how an interprofessional approach to drug prescribing and administration has the potential to improve quality and safety within healthcare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".