LO14: Interdepartmental program to improve outcomes for acute heart failure patients seen in the emergency department
Bibliographic record
Abstract
Introduction: An important challenge physicians face when treating acute heart failure (AHF) patients in the emergency department (ED) is deciding whether to admit or discharge, with or without early follow-up. The overall goal of our project was to improve care for AHF patients seen in the ED while avoiding unnecessary hospital admissions. The specific goal was to introduce hospital rapid referral clinics to ensure AHF patients were seen within 7 days of ED discharge. Methods: This prospective before-after study was conducted at two campuses of a large tertiary care hospital, including the EDs and specialty outpatient clinics. We enrolled AHF patients ≥50 years who presented to the ED with shortness of breath (<7 days). The 12-month before (control) period was separated from the 12-month after (intervention) period by a 3-month implementation period. Implementation included creation of rapid access AHF clinics staffed by cardiology and internal medicine, and development of referral procedures. There was extensive in-servicing of all ED staff. The primary outcome measure was hospital admission at the index visit or within 30 days. Secondary outcomes included mortality and actual access to rapid follow-up. We used segmented autoregression analysis of the monthly proportions to determine whether there was a change in admissions coinciding with the introduction of the intervention and estimated a sample size of 700 patients. Results: The patients in the before period (N = 355) and the after period (N = 374) were similar for age (77.8 vs. 78.1 years), arrival by ambulance (48.7% vs 51.1%), comorbidities, current medications, and need for non-invasive ventilation (10.4% vs. 6.7%). Comparing the before to the after periods, we observed a decrease in hospital admissions on index visit (from 57.7% to 42.0%; P <0.01), as well as all admissions within 30 days (from 65.1% to 53.5% (P < 0.01). The autoregression analysis, however, demonstrated a pre-existing trend to fewer admissions and could not attribute this to the intervention (P = 0.91). Attendance at a specialty clinic, amongst those discharged increased from 17.8% to 42.1% (P < 0.01) and the median days to clinic decreased from 13 to 6 days (P < 0.01). 30-day mortality did not change (4.5% vs. 4.0%; P = 0.76). Conclusion: Implementation of rapid-access dedicated AHF clinics led to considerably increased access to specialist care, much reduced follow-up times, and possible reduction in hospital admissions. Widespread use of this approach can improve AHF care in Canada.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".