Managing Heart Failure in Long-Term Care: Recommendations from an Interprofessional Stakeholder Consultation
Bibliographic record
Abstract
Heart failure (HF) affects up to 20 per cent of residents in long-term care (LTC) and is associated with substantial morbidity, mortality, and health service utilization. Our study objective was to formulate recommendations on implementing HF care processes in LTC. A three-phase and iterative stakeholder consultation process, guided by expert panel input, was employed to develop recommendations on implementing care processes for HF in LTC. This article presents the results of the third phase, which consisted of a series of interdisciplinary workshops. We developed 17 recommendations. Key elements of these recommendations focus on improving interprofessional communication and improving HF-related knowledge among all LTC stakeholders. Engaging frontline staff, including personal support workers, was stated as an essential component of all recommendations. System-level recommendations include improving communication between LTC homes and acute care and other external health service providers, and developing facility-wide interventions to reduce dietary sodium intake and increase physical activity.
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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 | 0.057 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".