Survey of Equine Referring Veterinarians' Satisfaction with Their Most Recent Equine Referral Experience
Bibliographic record
Abstract
BACKGROUND: Little is known about the veterinary referral process and factors that contribute to positive outcomes. OBJECTIVE: To investigate equine referring veterinarians' (rDVMs') satisfaction with their most recent referral experience and compare rDVM and specialist perspectives. SAMPLE: 187 rDVMs and 92 specialists (referral care providers). METHODS: Cross-sectional observational study. An online survey was administered to both rDVMs and specialists. Referring veterinarian satisfaction with their most recent referral experience was evaluated. Both rDVMs and specialists were asked to identify factors influencing a rDVM's decision where to refer, and the top 3 factors they perceive are barriers to referral care. RESULTS: Median rDVM satisfaction with their most recent referral care experience was 80 of 100 (mean, 75; range, 8-100). Referring veterinarians provided the lowest satisfaction score for the item asking about "The competition the referral hospital poses to your practice" (mean, 56.96; median, 62; range, 0-100). The top factor rDVMs identified as influencing their decision where to refer was "quality of care," whereas specialists identified "quality of communication and updates from the clinician." Referring veterinarians' top barrier to referral care was "high cost of referral care," and for specialists was "poor service provided to the client by the referral hospital." CONCLUSIONS AND CLINICAL IMPORTANCE: Referring veterinarians generally were satisfied with referral care, but areas exist where rDVMs and specialists differ in what they view as important to the referral process. Exploring opportunities to overcome these differences is likely to support high quality care.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".