A randomised controlled trial assessing the efficacy of an electronic discharge communication tool for preventing death or hospital readmission
Bibliographic record
Abstract
OBJECTIVE: To assess the efficacy of an electronic discharge communication tool (e-DCT) for preventing death or hospital readmission, as well as reducing patient-reported adverse events after hospital discharge. The e-DCT assessed has already been shown to yield high-quality discharge summaries with high levels of patient and physician satisfaction. METHODS: This two-arm randomised controlled trial was conducted in a Canadian tertiary care centre's internal medicine medical teaching units. Out of the 1953 patients approached and screened for inclusion, 1399 were randomised and available for data linkage for determination of the primary outcome. Participants were randomly assigned to e-DCT versus usual care (traditional discharge communication generated by dictation). The primary outcome was a composite of death or readmission within 90 days. The secondary outcome included any patient-reported adverse events within 30 days of discharge. RESULTS: Among 1399 randomised participants, 230 of 701 participants (32.8%) in the e-DCT group experienced the primary composite outcome of death or readmission within 90 days vs 205 of 698 participants (29.4%) in the usual care group (p=0.166). The incidence at 30 days of patient-reported adverse outcomes (35% for e-DCT vs 34% for usual care) and adverse events (2.1% for e-DCT vs 1.8% for usual care) also did not differ significantly between groups. CONCLUSIONS: The e-DCT tested did not reduce the composite endpoint of death or readmission at 90 days, nor the incidence of patient-reported adverse events at 30 days. This neutral finding for hard clinical endpoints needs to be considered in the context of high patient and physician satisfaction, and high quality of discharge summaries.
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How this classification was reachedexpand
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".