Five things every community pharmacist should know when dispensing for 4-legged patients
Bibliographic record
Abstract
Veterinarians are responsible for the entirety of a companion animal’s care, including the dispensing of medications. In recent years, both the Internet and media have significantly influenced pet owners to seek alternative means than the veterinarian to obtain medications by advertising substantial cost savings.1-5 The average markup on veterinary prescriptions is 100% to 200% plus a dispensing fee.6 As a result, more pet owners are asking veterinarians to write prescriptions. This shift has become so noteworthy that Bill S. 1200, The Fairness to Pet Owners Act, has been introduced to the United States Congress.7 This bill would obligate veterinarians to write a prescription for all medications and give pet owners the freedom to “shop around” for the best price on their pet’s medication. If this bill is passed in the United States, there is no question that a similar piece of legislation will be considered in Canada. With an increase in veterinary dispensing, there is a need for pharmacists to continue their professional education in the area of animal health. As of 2015, the only Canadian university with an undergraduate elective course in veterinary pharmacology is the University of Alberta.8-17 This implies that the majority of Canadian pharmacists do not receive adequate training to dispense animal prescriptions. More concerning, a survey conducted in Oregon revealed several cases of pharmacists making inappropriate medication substitutions or providing incorrect counselling on veterinary medications without consultation with the prescribing veterinarian.18 For example, the Latin veterinary abbreviation sid (once daily) is often misinterpreted by pharmacists as qid, resulting in a 4-fold overdose of the medication. Unfortunately, many of these described cases resulted in patient harm or death. As a result, the veterinary community is quite concerned with the dispensing of veterinary medications by pharmacists.19-22 The purpose of this article is to educate Canadian pharmacists on the 5 most common issues they may encounter in community practice with regard to veterinary prescriptions. The information provided is an attempt to prevent veterinary medication errors and reduce harm to our animal patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.105 | 0.039 |
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".