Abstract 19608: Public Report Cards Associated With Decreased Heart Failure Readmissions in the Effect Study
Bibliographic record
Abstract
Background: Public reporting of hospital performance on in-hospital heart failure (HF) quality indicators is increasingly common although its effectiveness in reducing HF readmissions is uncertain. We conducted an analysis of data from the Enhanced Feedback for Effective Cardiac Treatment (EFFECT) (clinicaltrials.gov NCT00187460) cluster randomized trial of cardiac report cards to evaluate the hypothesis that public reporting of hospital performance might be associated with reduced HF readmission rates. Methods: Patients included in this post-hoc analysis (n=7,399) were those hospitalized for an index episode of HF identified as part of the follow-up cohort in the EFFECT study, conducted in Ontario, Canada. Participating Ontario hospital corporations (n=86) were randomized to early (January 2004) or delayed feedback (September 2005) of a report card on their baseline performance (1999 to 2001) on a set of 6 process-of-care indicators for HF. Follow-up data were collected between April 2004 and March 2005....
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".