60 NICU Manager’s Perception of High Unit Activity and Its Association with Patient Care in the Neonatal Intensive Care Unit
Bibliographic record
Abstract
Abstract Background Each year, 15,000 critically ill neonates require specialized care that is offered in only 32 tertiary neonatal intensive care units (NICUs) in Canada. Previous studies have shown associations between nurse-to-patient ratios and higher bed occupancy with patient outcomes. Objective To explore neonatal managers’ perceptions of organizational factors in Canadian NICUs. Methods This was a web-based cross-sectional survey, consisting of 20 questions pertaining to the determinants of resource allocation, the ascertainment of high occupancy state, as well as the different challenges and mitigation strategies implemented during periods of high unit strain. The survey was designed following the CHERRIES guidelines and was critically reviewed through a two-round validation process prior to deployment. It was sent by e-mail to the unit managers of all Canadian Level-3 NICUs between August and November 2022. They were invited to respond based on their unit’s practices in 2021. The analysis was conducted using descriptive statistics, where units were dichotomized by size (small unit ˂36 beds, large unit ≥36 beds). Results A total of 24 unit managers (75%) completed the survey. Most respondents relied exclusively on clinical judgment to estimate the total number of nurses required per shift (33%) and the individual nurse-to-patient ratios (67%) as opposed to nursing workload assessment tools (8% and 21%, respectively). The response for the proportion of nursing shifts perceived as adequately staffed was: 0% for 100% adequately staffed, 37% for ˃80% adequately staffed, and 27% for 60%-80% adequately staffed. The response for the proportion of nursing shifts perceived as understaffed to the point of being unsafe for patient care was: 17% for no understaffed, 52% for ˂20% understaffed, and 9% for 20%-40% understaffed. The most common organizational challenges were personnel recruitment and unit occupancy (each reported as being a major issue by 38% of respondents). Although most (75%) respondents believed that high occupancy, especially when exceeding 90%, likely increases the risk of adverse patient outcomes, they revealed implementing mitigation strategies to reduce occupancy only when it exceeded 95%. At that point, the most common strategies implemented were to call for additional voluntary nurses, implement voluntary nursing overtime, and accelerate patient transfer. Conclusion Although Canadian NICUs form a very heterogeneous group, managers shared similar perspectives in terms of staffing and occupancy challenges. This emphasizes the need for collaborative NICU person-power resource management practices to improve neonatal intensive care service organization.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".