Safely and effectively reducing inpatient length of stay: a controlled study of the General Internal Medicine Care Transformation Initiative
Bibliographic record
Abstract
PURPOSE: Whether improving the efficiency of hospital care will worsen post-discharge outcomes is unclear. We designed this study to evaluate the General Internal Medicine (GIM) Care Transformation Initiative implemented at one of the seven teaching hospitals in the Canadian province of Alberta. METHODS: Controlled before-after study of GIM patients hospitalised at the University of Alberta Hospital (UAH, intervention site, n=1896) or the six other teaching hospitals in Alberta-three in Edmonton (intra-regional controls (IRC), n=4550) and three in Calgary (extra-regional controls (ERC), n=4095). The primary effectiveness outcome was risk-adjusted length of stay (LOS) and the primary safety outcome was 'mortality during index hospitalisation or all-cause readmission or death within 30-days of discharge'. RESULTS: LOS for GIM patients decreased by 0.68 days at Alberta teaching hospitals between 2009 and 2012; GIM patients hospitalised at the UAH exhibited a further 20% relative decline in adjusted LOS (total reduction=1.43 days, 95% CI 0.94 to 1.92 days) from PRE to POST. Interrupted time series (ITS) confirmed that the 1.43 day reduction at the UAH was statistically significant (level change p=0.003), while the declines at the IRC (p=0.37) and ERC (p=0.45) were not. Our safety outcome did not change for UAH patients (18.4% PRE-intervention vs 17.8% POST-intervention, adjusted OR 1.02 (95%CI 0.80 to 1.31), p=0.42 on ITS), nor for those hospitalised at the IRC (p=0.33) or the ERC (p=0.73) sites. CONCLUSIONS: The Care Transformation Initiative was associated with substantial reductions in LOS without increasing post-discharge events commonly quoted as proxies for quality.
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 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 | 0.003 | 0.001 |
| 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 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".