Reducing Waste in the Critical Care Setting
Bibliographic record
Abstract
BACKGROUND: The ICU at London Health Sciences Centre-University Hospital (LHSC-UH) is a 40-bed critical care unit that contains two separate supply rooms that carry all the essential materials necessary for patient care. However, considering the patient acuity in critical care, it is vital that this equipment is made more accessible for practitioners at the bedside. Therefore, nurse servers or bedside supply cabinets are present in each of the patient rooms. While these servers provide timely access to the supplies essential for nursing care, they are also a huge source of waste. When patients who are identified as having antibiotic-resistant organisms (AROs) are discharged, numerous unused items are discarded for infection control purposes. AIMS AND OBJECTIVES: Project objectives were to curtail waste by minimizing stocked supplies at the bedside, exploring alternative stocking options and increasing awareness of this issue with practitioners. METHODS: An interprofessional team was formed consisting of registered nurses, support service workers, environmental service workers, infection control practitioners and critical care leadership. A cost analysis of discarded supplies was undertaken, and results were communicated to all staff. Infection control practitioners developed guidelines specific to use of the nurse servers and linen supply areas. The stocking process and contents of the servers were reviewed; surplus was removed and relocated to a close central area outside patient rooms. Following agreement on new server contents, lists and photos were created and posted in each supply room. New stocking guidelines were phased in gradually and were adapted according to user feedback. RESULTS: Over a two-week period, a pilot cost analysis identified that supplies valued at $2,327.25 had been discarded from five bedsides. Future long-term cost savings will enable management to redirect such resources and therefore improve other essential care services in the ICU. CONCLUSION: Increasing awareness of wasteful stocking practices facilitated the engagement of this CQI project. New stocking practices have greatly reduced waste and increased service efficiencies while maintaining the integrity of optimal patient care.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".