A local quality initiative to improve follow-up times for patients with heart failure
Bibliographic record
Abstract
Introduction Heart failure is the most common cause of hospital admission in patients >65 years and around 50% of patients will be readmitted within 6 months. Inability to achieve timely outpatient follow-up may contribute to the high rates of avoidable rehospitalisation for this group of patients. Canadian guidelines recommend patients with heart failure should be seen within 14 days of discharge. Methods An audit demonstrated that less than half of advanced heart failure patients were being followed up within 14 days. In an effort to improve postdischarge follow-up in our heart function clinic, we used process mapping and applied a series of iterative changes to the appointment booking system using Plan–Do–Study–Act cycles to reduce waste and standardise. Results The primary outcome measure, tracked over a period of 20 months, was percentage of patients booked within 14 days. At baseline, 37% of patients were seen within 14 days. After our series of interventions related to streamlining and standardising the appointment booking process, 77% of patients were seen within 14 days and 100% of patients were seen within 21 days. Conclusion The changes made to the appointment booking process were reproducible, sustainable, effective and required no additional resources or funding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".