The untapped potential of Registered Veterinary Technicians in hospice care
Bibliographic record
Abstract
Abstract Background: As veterinary medicine evolves to include more comprehensive hospice and end-of-life care, Registered Veterinary Technicians remain an underutilized resource in hospice and palliative care programs. This systematic review investigates the barriers and opportunities for Registered Veterinary Technicians to assume leadership roles in veterinary hospice care. Methods: A systematic review of peer-reviewed veterinary literature from 2000 to 2024 was conducted using PubMed, CAB Abstracts, and Google Scholar. Search terms included “veterinary hospice,” “palliative care,” “Registered Veterinary Technician,” “veterinary nurse,” “hospice and end-of-life care,” and “access to care.” Inclusion criteria were English-language studies focused on veterinary medicine, with emphasis on Registered Veterinary Technician roles, training, clinic economics, and accessibility of care. Human health and non-hospice veterinary studies were excluded except where explicitly used for comparative context. A total of 86 articles were screened; 21 met all inclusion criteria and were analyzed thematically. Results: Thematic analysis revealed six recurring themes: (1) underutilization of Registered Veterinary Technicians; (2) misunderstandings around Registered Veterinary Technician abilities; (3) nurse-led hospice care; (4) lack of dedicated hospice training; (5) Registered Veterinary Technicians can help increase access to care; and (6) high veterinarian workload limits hospice capacity. Despite the potential of Registered Veterinary Technicians to support compassionate hospice and end-of-life care, training gaps, cultural resistance, economic oversight, and regulatory ambiguity persist. Conclusions: Registered Veterinary Technicians are well-positioned to lead and enhance veterinary hospice services. Addressing training deficiencies, expanding scope-of-practice clarity, and promoting technician-led care models may help veterinary practices better serve animals and families during the most vulnerable life stage.
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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 | 0.027 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".