Improving Daily Patient Goal-Setting and Team Communication: The Liber8 Glass Door Project*
Bibliographic record
Abstract
OBJECTIVES: To develop and implement a tool to improve daily patient goal setting, team collaboration and communication. DESIGN: Quality improvement implementation project. SETTING: Tertiary-level PICU. PATIENTS: Inpatient children less than 18 years old requiring ICU level care. INTERVENTION: A "Glass Door" daily goals communication tool located in the door front of each patient room. MEASUREMENTS AND MAIN RESULTS: We used Pronovost's 4 E's model to implement the Glass Door. Primary outcomes were uptake of goal setting, healthcare team discussion rate around goals, rounding efficiency, acceptability and sustainability of the Glass Door. The total implementation duration from engagement to evaluation of sustainability was 24 months. Goal setting increased significantly from 22.9% to 90.7% ( p < 0.01) patient-days using the Glass Door compared to a paper-based daily goals checklist (DGC). One-year post implementation, the uptake was sustained at 93.1% ( p = 0.04). Rounding time decreased from a median of 11.7 minutes (95% CI, 10.9-12.4 min) to 7.5 minutes (95% CI, 6.9-7.9 min) per patient post-implementation ( p < 0.01). Goal discussions on ward rounds increased overall from 40.1% to 58.5% ( p < 0.01). Ninety-one percent of team members perceive that the Glass Door improves communication for patient care, and 80% preferred the Glass Door to the DGC for communicating patient goals with other team members. Sixty-six percent of family members found the Glass Door helpful in understanding the daily plan and 83% found it helpful in ensuring thorough discussion among the PICU team. CONCLUSIONS: The Glass Door is a highly visible tool that can improve patient goal setting and collaborative team discussion with good uptake and acceptability among healthcare team members and patient families.
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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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".