Measuring Potentially Avoidable Acute Care Transfers From Long-Term Care Homes in Quebec: a Cross Sectional Study
Bibliographic record
Abstract
Background: Potentially avoidable emergency department transfers (PAEDTs) and hospitalizations (PAHs) from long-term care (LTC) homes are two key quality improvement metrics. We aimed to: 1) Measure proportions of PAEDTs and PAHs in a Quebec sample; and 2) Compare them with those reported for the rest of Canada. Methods: We conducted a repeated cross-sectional study of residents who were received at one tertiary hospital between April 2017 and March 2019 from seven LTC homes in Quebec, Canada. The MedUrge emergency department database was used to extract transfers and resident characteristics. Using published definitions, PAEDTs and PAHs were identified from principal emergency department and hospitalization diagnoses, respectively. PAEDT and PAH proportions were compared to those reported by the Canadian Institute for Health Information. Results: A total of 1,233 transfers by 692 residents were recorded, among which 36.3% were classified as being potentially avoidable: 22.8% 'PAEDT only', 11.6% 'both PAEDT & PAH', and 1.9% 'PAH only'. Shortness of breath was the most common reason for transfer. Pneumonia was the most common diagnosis from the 'both PAEDT & PAH' category. PAEDTs and PAHs accounted for 95% and 37% of potentially avoidable transfers, respectively. Among 533 hospitalizations, 31.3% were PAHs. These proportions were comparable to the rest of Canada, with some differences in proportions of transfers due to congestive heart failure, urinary tract infection, and implanted device management. Conclusions: PAEDTs far outweigh PAHs in terms of frequency, and their monitoring is important for quality assurance as they may inform LTC-level interventions aimed at their reduction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".