Improving Transitions of Care between the Intensive Care Unit and General Internal Medicine Ward. A Demonstration Study
Bibliographic record
Abstract
Abstract Background In-hospital transfers such as from the intensive care unit (ICU) to the general internal medicine (GIM) ward place patients at risk of adverse events. A structured handover tool may improve transitions from the ICU to the GIM ward. Objective To develop, implement, and evaluate a customized user-designed transfer tool to improve transitions from the ICU to the GIM ward. Methods This was a pre–post intervention study at a tertiary academic hospital. We developed and implemented a user-designed, structured, handwritten ICU-to-GIM transfer tool. The tool included active medical issues, functional status, medications and medication changes, consulting services, code status, and emergency contact information. Transfer tool users included GIM physicians, ICU physicians, and critical care rapid response team nurses. An implementation audit and mixed qualitative and quantitative analysis of pre–post survey responses was used to evaluate clinician satisfaction and the perceived quality of patient transfers. Results The pre–post survey response rate was 51.8% (99/191). Respondents included GIM residents (58.5%), ICU rapid response team physicians and nurses (24.2%), and GIM attending physicians (17.2%). Less than half of clinicians (48.8%) reported that the preintervention transfer process was adequate. Clinicians who used the transfer tool reported that the transfer process was improved (93.3% vs. 48.8%, P = 0.03). Clinician-reported understanding of medication changes in the ICU increased (69.2% vs. 29.1%, P = 0.004), as did their ability to plan for a safe hospital discharge (69.2% vs. 31.0%, P = 0.01). However, only 64.2% of audited transfers used the tool. Frequently omitted sections included home medications (missing in 83.4% of audits), new medications (33.3%), and secondary diagnosis (33.3%). Thematic analysis of free-text responses identified areas for improvement including clarifying the course of ICU events and enhancing tool usability. Conclusion A user-designed, structured, handwritten transfer tool may improve the perceived quality of patient transfers from the ICU to the GIM wards.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".