Abstract 74: A Population-Based Study to Evaluate the Effectiveness of Multi-Disciplinary Heart Failure Clinics and Identify Important Service Components
Bibliographic record
Abstract
Background Multi-disciplinary heart failure (HF) clinics improve outcomes for HF patients in randomized clinical trials. It is unclear if this efficacy translates to real world effectiveness. Accordingly, our objectives were to 1) compare real world outcomes of HF patient treated in HF clinics vs that in standard care and 2) identify HF clinic features associated with improved outcomes. Methods The service components at all 34 HF clinics in Ontario, Canada were evaluated and scored using a validated instrument. Based these scores, the clinics were categorized by an expert panel into high/medium or low intensity strata. Our cohort consisted of all patients discharged alive after a HF hospitalization in 2006-07. Patients were classified as either HF clinic or standard care patients and followed until March 31st, 2010, to evaluate mortality, all-cause hospitalization, and HF hospitalization. Propensity score matching was used to compare outcomes between comparable groups of patients in the two groups, using Kaplan-Meier survival curves. We explored the clinic level characteristics associated with improved outcomes by developing marginal Cox-proportional hazard models, restricted to the overall sample of HF clinic patients, so as to account for clustering by HF clinic. Results We identified 14,468 HF patients, of whom 1,288 were seen in HF clinics. In a matched sample of 1,288 pairs, systematic differences between groups were substantially reduced. Over 3 years of follow-up, 52.1% of HF clinic patients died, compared to 54.7% of standard care patients (p-value 0.02). HF clinic patients had a significant increase in hospitalization (87.4% vs 86.6% for all-cause [p-value 0.009]; 58.7% vs 47.3% for HF-related [p-value <0.001]). Clinics in the high intensity strata were associated with lower mortality (hazard ratio [HR] 0.68 (95% confidence interval [CI] 0.48-0.98; p-value 0.04) but higher rates of all-cause hospitalization (HR 1.48; 95% CI 1.01-2.18; p-value 0.04) and HF hospitalization (HR 1.98; 95% CI 1.42-2.77; p-value <0.001), compared to low intensity clinics. HF clinics that targeted both the patient and caregiver were associated with improved survival compared to those that only focused on the patient, as were clinics with an emphasis on peer support. Clinics with frequent contacts between providers and patients had a significant reduction in mortality (HR 0.15; 95% CI 0.09-0.25; p-value <0.0001). A more intensive medication management program was associated with reduced all cause and HF hospitalization (HR 0.35 and HR 0.27 respectively). Conclusions Multi-disciplinary HF clinics are associated with a decrease in mortality but increase in re-hospitalizations compared to standard care. A gradient was observed between clinic intensity and outcomes whereby greater intensity of clinic services was associated with mortality reductions but increased hospitalization.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".