Yarning to reduce take own leave events in First Nations patients presenting to the Emergency Department‐presenting the qualitative themes and co‐design of the Deadly <scp>RED</scp> project
Bibliographic record
Abstract
ISSUE ADDRESSED: The Deadly RED redesign and implementation research aimed to improve take own leave (TOL) rates within a Queensland emergency department by providing a culturally competent care pathway. METHODOLOGY: A mixed methods pre/post evaluation of the feasibility, acceptability and usability of the Deadly RED pathway for First Nations patients presenting to ED was performed. This pathway combined early welcome and information sharing, introduction of screening and follow up for patients who TOL and enhanced access to alternative community healthcare. Yarning circles facilitated co-design of research protocols and tools while a purposefully designed research Yarn enhanced understanding of the 'story' of the people. Qualitative analysis of Yarns allowed deductive themes to be extracted. A Participatory Action Research (PAR) approach and Indigenous research methodology involving First Nations people in design, knowledge sharing and joint ownership of results was used. RESULTS: Common themes from the 85 yarns included the negative impact of long waiting times and positive impact from wholistic care. Unique themes identified included interpretation of waiting room placement and paracetamol prescription as a dismissal. Knowledge dissemination from yarning drove improvements in communications and processes to promote treatment completion resulting in elimination of these themes in post implementation yarns. Eighteen patients who had TOL were included in the post implementation yarns, however only eight of these believed that their treatment was incomplete. CONCLUSION: The use of yarning for consumer engagement has allowed deeper understanding of the reasons for TOL in First Nations emergency patients. The reciprocal knowledge sharing has guided targeted improvements in wholistic emergency care and communication resulting in First Nations patients feeling their care is complete even when the 'number' reports otherwise. SO WHAT?: Indigenous Research methodology including yarning with First Nations patients suggests alternative engagement methods to guide enhanced quality of care monitoring for ED presentations.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".