The effects of acute care hospitalization on health and cost trajectories for nursing home residents: A matched cohort study
Bibliographic record
Abstract
Thirty five percent to sixty seven percent of admissions to acute care hospitals from nursing homes are potentially preventable. Limited data exist regarding clinical and cost trajectories post an acute care hospitalization. To describe clinical impact and post-hospitalization costs associated with acute care admissions for nursing home residents. Analysis of population-based data. The 65,996 nursing home residents from a total of 645 nursing homes. Clinical outcomes assessed with the Changes in Health, End-stage disease and Symptoms and Signs (CHESS) scores, and monthly costs. Post-index date, hospitalized residents worsened their clinical conditions, with increases in CHESS scores (CHESS 3 + 24.5% vs 7.6%, SD 0.46), more limitations in activities of daily living (ADL) (86.1% vs 76.0%, SD 0.23), more prescriptions (+1.64 95% CI 1.43-1.86, P < .001), falls (30.9% vs 18.1%, SD 0.16), pressure ulcers (16.4% vs 8.6%, SD 0.37), and bowel incontinence (47.3% vs 39.3%, SD 0.35). Acute care hospitalizations for nursing home residents had a significant impact on their clinical and cost trajectories upon return to the nursing home. Investments in preventive strategies at the nursing home level, and to mitigate functional decline of hospitalized frail elderly residents may lead to improved quality of care and reduced costs for this population. Pre-hospitalization costs were not different between the hospitalized and control groups but showed an immediate increase post-hospitalization (CAD 1882.60 per month, P < .001).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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".