Implementation of the I‐PASS handoff program in diverse clinical environments: A multicenter prospective effectiveness implementation study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Handoff miscommunications are a leading source of medical errors. Harmful medical errors decreased in pediatric academic hospitals following implementation of the I-PASS handoff improvement program. However, implementation across specialties has not been assessed. OBJECTIVE: To determine if I-PASS implementation across diverse settings would be associated with improvements in patient safety and communication. DESIGN: Prospective Type 2 Hybrid effectiveness implementation study. SETTINGS AND PARTICIPANTS: Residents from diverse specialties across 32 hospitals (12 community, 20 academic). INTERVENTION: External teams provided longitudinal coaching over 18 months to facilitate implementation of an enhanced I-PASS program and monthly metric reviews. MAIN OUTCOME AND MEASURES: Systematic surveillance surveys assessed rates of resident-reported adverse events. Validated direct observation tools measured verbal and written handoff quality. RESULTS: 2735 resident physicians and 760 faculty champions from multiple specialties (16 internal medicine, 13 pediatric, 3 other) participated. 1942 error surveillance reports were collected. Major and minor handoff-related reported adverse events decreased 47% following implementation, from 1.7 to 0.9 major events/person-year (p < .05) and 17.5 to 9.3 minor events/person-year (p < .001). Implementation was associated with increased inclusion of all five key handoff data elements in verbal (20% vs. 66%, p < .001, n = 4812) and written (10% vs. 74%, p < .001, n = 1787) handoffs, as well as increased frequency of handoffs with high quality verbal (39% vs. 81% p < .001) and written (29% vs. 78%, p < .001) patient summaries, verbal (29% vs. 78%, p < .001) and written (24% vs. 73%, p < .001) contingency plans, and verbal receiver syntheses (31% vs. 83%, p < .001). Improvement was similar across provider types (adult vs. pediatric) and settings (community vs. academic).
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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 | 0.002 | 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 it