PS-054 Storage and use of concentrated intravenous potassium solutions in a hospital complex
Bibliographic record
Abstract
Background Intravenous concentrated potassium solution (ICPS) has been identified as a high-alert drug by organisations in Australia, Canada, United States of America and the United Kingdom. Despite that, there are reports of accidental death from the incorrect administration of ICPS. Purpose To evaluate the storage and use of ICPS in a hospital complex. To identify the factors that can influence the use of ICPS versus pre-diluted solutions. Material and methods Descriptive study. An audit was conducted of all hospital complex medical kits (place in clinical management units (CMUs) where drugs are stored); location and identification of vials, CMU accreditation by Health Quality Andalusian Agency and knowledge of ICPS use by personnel. Also, consumption of intravenous concentrated potassium salts was calculated and was compared with the consumption of pre-diluted solutions by the CMUs. A medical kit was considered appropriate when ICPS lockers were separated, identified and had a safety alert. Results 78 kits from 30 CMUs were tested. 64 (82%) kits were in correctly identified ICPS lockers and 39 (51.3%) were in ICPS lockers adequately separated from the rest. 20 (25.6%) kits were labelled with safety alerts warning about the use of ICPS: 11 of them were posters and 9 red boxes. 35 (44.9%) kits belonged to an accredited CMU and 23 (29.5%) had received safety clinical sessions. Only 12 (15.4%) were appropriate medical kits: 9 (75%) belonged to an accredited CMU. The total ratio mEq potassium concentrated/potassium pre-diluted was 9.68. The total ratio mEq potassium concentrated/potassium pre-diluted in a CMU with certified quality management was 9.26. The total ratio mEq potassium concentrated/potassium pre-diluted in a CMU trained in prevention of treatment errors was 6.74. Conclusion The percentage of suitable kits was very low and consumption of pre-diluted solutions was much lower than ICPS. CMUs with an accredited quality management and/or whose staff had been trained in prevention of treatment errors had better concentrated potassium storage conditions and had a slightly higher use of pre-diluted potassium solutions than non-accredited CMUs. References and/or acknowledgements Institute for Safe Medication Practice No conflict of interest.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".