The implementation of a virtual fracture clinic in Far North Queensland: satisfaction and success without travel
Bibliographic record
Abstract
OBJECTIVE: Orthopaedic injuries often require timely management. This is challenging in remote regions, such as Far North Queensland, where patients must travel long distances. A Virtual Fracture Clinic (VFC) model offers a promising alternative, allowing remote management of select cases, and reducing travel burdens and healthcare costs. This prospective cohort study assessed the implementation of a VFC at Cairns Base Hospital. METHODS: An orthopaedic registrar triaged patients to the VFC based on predefined criteria over a 5-week period. Primary outcomes included patient satisfaction, travel distance savings and cost savings. Secondary outcomes included the clinical outcomes of the VFC and the traditional clinic. RESULTS: Out of 514 referrals, 36.4% were managed through the VFC. Compared with the traditional clinic, VFC patients had shorter wait times, and 91.4% of those seen in the VFC could be discharged without further review. VFC patients were highly satisfied, with 75.2% indicating a willingness to undergo the same treatment again. The VFC also resulted in significant travel distance and cost savings. No patients in the VFC required surgery during the follow-up period. CONCLUSION: This study provides the first prospective evidence that registrar-led VFCs in regional Australia can safely deliver orthopaedic care with substantial logistical and economic benefits. With high patient satisfaction and no compromise in safety, this model could redefine how fracture care is delivered across Australia's vast rural landscape, helping close the gap in access for remote and Indigenous populations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".