Journey to mother baby care: Implementation of a combined care/couplet model in a Level 2 neonatal intensive care unit
Bibliographic record
Abstract
"Why can't I have my postpartum care in the same room as my baby?" questioned Hilary, a neonatal intensive care unit (NICU) "alumni" parent, during a design event for the new British Columbia's Women's Hospital 70 single family room NICU. This simple yet provocative question was nearly dismissed and the idea of a combined care model lost, since most members of the team thought it was simply "not possible." Hilary did not give up and continued to raise this idea throughout every design event. It was Hilary's fortitude and sharing of her NICU experience that was the inspiration for the MotherBaby Care unit. The voice of one woman has improved the birth experiences of potentially thousands of mothers and their at-risk newborns. By honoring women's voices and values in health care, positive changes that matter to women, infants, and families can be made. Mothers also shared: "I knew what was best for me was to be with my baby," "If I could stand up after my C-section, I would drag my IV pole to be with my baby!", "Teach me how to take care of my premature baby before I am ready to go home!" MotherBaby Care is a combined care or "couplet" care where one NICU nurse provides care for a postpartum mother and her at-risk newborn in the Level 2 NICU. This review describes the journey from innovation and design to the implementation of the MotherBaby Care model.
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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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".