Increasing Parent Satisfaction With Discharge Planning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Neonatal intensive care unit (NICU) families are often overwhelmed by the discharge process. Their anxiety can inhibit learning and contribute to poor infant outcomes and increased healthcare utilization after discharge. Quality of the discharge teaching is the strongest predictor of discharge readiness, so NICUs must develop excellent discharge preparation programs. PURPOSE: This improvement project enhances NICU discharge preparedness by providing consistent, early discharge teaching using technology as a supplemental resource and raises parental satisfaction with the process. METHODS: Neonatal intensive care unit staff and former NICU parents developed a task force to create technology-based discharge education content. The content was originally uploaded to an e-book and later transferred to the electronic health record inpatient portal. Families were able to view discharge teaching content at their own convenience and pace and review topics as needed with the NICU staff. Postdischarge follow-up phone calls provided insight into parental reaction to the new education format. RESULTS: Parent satisfaction top-box scores, reflecting the highest rating in the "Prepared for Discharge" category of the patient satisfaction survey, improved from a baseline of 47% in 2017 to 70% in 2019. Overwhelmingly, 92% of families highly rated the tablet-based discharge teaching during postdischarge phone calls. IMPLICATIONS FOR PRACTICE: A comprehensive, consistent, and early discharge program using technology can lead to more effective and efficient NICU discharge education and improved parent satisfaction. IMPLICATIONS FOR RESEARCH: Further studies are needed to generalize hospital-based inpatient portal teaching as an additional resource for parental education in the NICU.
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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) | 0.000 | 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 it