Implementing a Family-Centered Rounds Intervention Using Novel Mentor-Trios
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Patient and Family Centered I-PASS (PFC I-PASS) emphasizes family and nurse engagement, health literacy, and structured communication on family-centered rounds organized around the I-PASS framework (Illness severity-Patient summary-Action items-Situational awareness-Synthesis by receiver). We assessed adherence, safety, and experience after implementing PFC I-PASS using a novel "Mentor-Trio" implementation approach with multidisciplinary parent-nurse-physician teams coaching sites. METHODS: Hybrid Type II effectiveness-implementation study from 2/29/19-3/13/22 with ≥3 months of baseline and 12 months of postimplementation data collection/site across 21 US community and tertiary pediatric teaching hospitals. We conducted rounds observations and surveyed nurses, physicians, and Arabic/Chinese/English/Spanish-speaking patients/parents. RESULTS: We conducted 4557 rounds observations and received 2285 patient/family, 1240 resident, 819 nurse, and 378 attending surveys. Adherence to all I-PASS components, bedside rounding, written rounds summaries, family and nurse engagement, and plain language improved post-implementation (13.0%-60.8% absolute increase by item), all P < .05. Except for written summary, improvements sustained 12 months post-implementation. Resident-reported harms/1000-resident-days were unchanged overall but decreased in larger hospitals (116.9 to 86.3 to 72.3 pre versus early- versus late-implementation, P = .006), hospitals with greater nurse engagement on rounds (110.6 to 73.3 to 65.3, P < .001), and greater adherence to I-PASS structure (95.3 to 73.6 to 72.3, P < .05). Twelve of 12 measures of staff safety climate improved (eg, "excellent"/"very good" safety grade improved from 80.4% to 86.3% to 88.0%), all P < .05. Patient/family experience and teaching were unchanged. CONCLUSIONS: Hospitals successfully used Mentor-Trios to implement PFC I-PASS. Family/nurse engagement, safety climate, and harms improved in larger hospitals and hospitals with better nurse engagement and intervention adherence. Patient/family experience and teaching were not affected.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".