Reduction of Hospital Utilization in Patients With Chronic Obstructive Pulmonary Disease<subtitle>A Disease-Specific Self-management Intervention</subtitle>
Bibliographic record
Abstract
BACKGROUND: Self-management interventions improve various outcomes for many chronic diseases. The definite place of self-management in the care of chronic obstructive pulmonary disease (COPD) has not been established. We evaluated the effect of a continuum of self-management, specific to COPD, on the use of hospital services and health status among patients with moderate to severe disease. METHODS: A multicenter, randomized clinical trial was carried out in 7 hospitals from February 1998 to July 1999. All patients had advanced COPD with at least 1 hospitalization for exacerbation in the previous year. Patients were assigned to a self-management program or to usual care. The intervention consisted of a comprehensive patient education program administered through weekly visits by trained health professionals over a 2-month period with monthly telephone follow-up. Over 12 months, data were collected regarding the primary outcome and number of hospitalizations; secondary outcomes included emergency visits and patient health status. RESULTS: Hospital admissions for exacerbation of COPD were reduced by 39.8% in the intervention group compared with the usual care group (P =.01), and admissions for other health problems were reduced by 57.1% (P =.01). Emergency department visits were reduced by 41.0% (P =.02) and unscheduled physician visits by 58.9% (P =.003). Greater improvements in the impact subscale and total quality-of-life scores were observed in the intervention group at 4 months, although some of the benefits were maintained only for the impact score at 12 months. CONCLUSIONS: A continuum of self-management for COPD patients provided by a trained health professional can significantly reduce the utilization of health care services and improve health status. This approach of care can be implemented within normal practice.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".