Evaluation of a community-based inner-city disease management program for postmyocardial infarction patients: a randomized controlled trial.
Bibliographic record
Abstract
BACKGROUND: Disease management programs (DMPs) that use multidisciplinary teams and specialized clinics reduce hospital admissions and improve quality of life and functional status. Evaluations of cardiac DMPs delivered by home health nurses are required. METHODS: Between August 1999 and August 2000 we identified consecutive patients admitted to hospital with elevated cardiac enzymes. Patients who agreed were randomly assigned to participate in a DMP or to receive usual care. The DMP included 6 home visits by a cardiac-trained nurse, a standardized nurses' checklist, referral criteria for specialty care, communication with the family physician and patient education. We measured readmission days per 1000 follow-up days for angina, congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD); all-cause readmission days; and provincial claims for emergency department visits, physician visits, diagnostic or therapeutic services and laboratory services. RESULTS: We screened 715 consecutive patients admitted with elevated cardiac markers between August 1999 and August 2000. Of those screened 71 DMP and 75 usual care patients met the diagnostic criteria for myocardial infarction, were eligible for visits from a home health nurse and consented to participate in the study. Readmission days for angina, CHF and COPD per 1000 follow-up days were significantly higher for usual care patients than for DMP patients (incidence density ratio [IDR] = 1.59, 95% confidence interval [CI] 1.27-2.00, p < 0.001). All-cause readmission days per 1000 follow-up days were significantly higher for usual care patients than for DMP patients (IDR = 1.53, 95% CI 1.37-1.71, p < 0.001). The difference in emergency department encounters per 1000 follow-up days was significant (IDR = 2.08, 95% CI 1.56-2.77, p < 0.001). During the first 25 days after discharge, there were significantly fewer provincial claims submitted for DMP patients than for usual care patients for emergency department visits (p = 0.007), diagnostic or therapeutic services (p = 0.012) and laboratory services (p = 0.007). INTERPRETATION: The results provide evidence that an appropriately developed and implemented community-based inner-city DMP delivered by home health nurses has a positive impact on patient outcomes.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".