Qualitative evaluation of a mandatory provincial programme auditing emergency department return visits
Bibliographic record
Abstract
OBJECTIVE: The objective of this qualitative study was to evaluate the perceived impact and value of the Return Visit Quality Programme (RVQP), a mandatory province-wide emergency department audit programme. DESIGN: We employed an interpretive descriptive qualitative approach with maximum variation sampling to ensure diverse representation across several geographical and institutional factors. RVQP programme leads were invited to participate in semistructured interviews and snowball sampling was used to reach non-lead physicians to capture the perspectives of those working within the programme. SETTING: In Ontario's RVQP, participating emergency departments must audit their return visits resulting in admission to identify issues that can be addressed through quality improvement initiatives. PARTICIPANTS: Between June and August 2018, we interviewed 32 participants (local programme leads and non-lead physicians) from 23 out of the 86 participating centres. RESULTS: Participants' perceived impact and value of the programme was associated with the existence (or absence) and nature of the local quality improvement culture, the implementation approach of the programme within their emergency departments, and key aspects of the programme pertaining to medicolegal concerns and resource availability. CONCLUSIONS: This study of an innovative, large-scale programme aimed at promoting continuous quality improvement in emergency departments showed that while its perceived impact has been meaningful, there are key structural and operational elements that support and hinder this aim. Healthcare leaders should consider these findings when looking to implement large-scale audit or quality improvement programmes.
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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 | 0.048 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".