Barriers and Enablers to Implementing a High-Dependency Care Model in Pediatric Care
Bibliographic record
Abstract
BACKGROUND: As the level of acuity of pediatric hospital admissions continues to increase, additional pressure is being placed on hospital resources and the nursing workforce. LOCAL PROBLEM: Currently, there is no formalized approach to care for high-acuity patients on our pediatric inpatient unit. METHODS: We used a qualitative descriptive design, guided by the Theoretical Domains Framework and Capability, Opportunity, Motivation-Behaviour (COM-B) model, to conduct focus groups and interviews with clinicians and administrators to identify potential barriers and enablers to implementing a high-dependency care (HDC) model. An HDC model focuses on the relationship between adequate nursing staff resources and patient acuity to improve patient health outcomes. RESULTS: Participants identified the need for clear guidelines and supportive physical structures to facilitate HDC implementation. Anticipated benefits included enhanced nursing confidence and family-centered care. CONCLUSIONS: Study findings highlight multilevel factors to consider prior to implementing an HDC model on a pediatric inpatient unit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".