A systematic review of clinical audit in companion animal veterinary medicine
Bibliographic record
Abstract
BACKGROUND: Clinical audit is a quality improvement process with the goal of continuously improving quality of patient care as assessed by explicit criteria. In human medicine clinical audit has become an integral and required component of the standard of care. In contrast, in veterinary medicine there appear to have been a limited number of clinical audits published, indicating that while clinical audit is recognised, its adoption in veterinary medicine is still in its infancy. A systematic review was designed to report and evaluate the veterinary literature on clinical audit in companion animal species (dog, cat, horse). A systematic search of English and French articles using Proquest Dissertations and Theses database (February 6, 2014), CAB Abstracts (March 21, 2014 and April 4, 2014), Scopus (March 21, 2014), Web of Science Citation index (March 21, 2014) and OVID Medline (March 21, 2014) was performed. Included articles were those either discussing clinical audit (such as review articles and editorials) or reporting parts of, or complete, audit cycles. RESULTS: The majority of articles describing clinical audit were reviews. From 89 articles identified, twenty-one articles were included and available for review. Twelve articles were reviews of clinical audit in veterinary medicine, five articles included at least one veterinary clinical audit, one thesis was identified, one report was of a veterinary clinical audit website and two articles reported incomplete clinical audits. There was no indication of an increase in the number of published clinical audits since the first report in 1998. However, there was evidence of article misclassification, with studies fulfilling the criteria of clinical audit not appropriately recognised. Quality of study design and reporting of findings varied considerably, with information missing on key components, including duration of study, changes in practice implemented between audits, development of explicit criteria and appropriate statistical analyses. CONCLUSIONS: Available evidence suggests the application and reporting of clinical audit in veterinary medicine is sporadic despite the potential to improve patient care, though the true incidence of clinical audit reporting is likely to be underestimated due to incorrect indexing. Reporting standards of clinical audits are highly variable, limiting evaluation, application and repeatability of published work.
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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 | 0.020 | 0.110 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".