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Record W4294990985 · doi:10.2460/javma.22.06.0268

Discussion of cost continues to be uncommon in companion animal veterinary practice

2022· article· en· W4294990985 on OpenAlexaffabout
Catherine N. H. Groves, Natasha Janke, Alexandra Stroyev, Jordan D. Tayce, Jason B. Coe

Bibliographic record

VenueJournal of the American Veterinary Medical Association · 2022
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
FundersRoyal CaninZoetis
KeywordsMedicineOddsFamily medicineLogistic regressionCompanion animalHealth careVeterinary medicineService (business)Descriptive statisticsCross-sectional studyNursingMarketingPathologyBusiness

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence and nature of cost conversations occurring during veterinarian-client-patient interactions within companion animal practice. SAMPLES: 60 randomly selected, practicing veterinarians working in 55 practices across southern Ontario, Canada, and 909 of their clients, sampled by convenience. PROCEDURES: A cross-sectional descriptive study including 917 video-recorded appointments. Associations between veterinarian, client, or appointment-level factors and occurrence of a cost conversation were evaluated using multi-level logistic regression. RESULTS: 215 of 917 (23.4%) videos included a discussion of cost between the veterinarian and client. Cost conversations involving veterinarians primarily focused on conveying the price in relation to the time or service being offered (74.0% [159/215]), whereas the benefit to the future health and wellness of the patient was conveyed in 14.4% (31/215) of veterinarians' cost conversations. Costs were most frequently discussed by veterinarians in relation to diagnostic testing (44.2% [96/215]). The odds of a cost discussion occurring were greater during problem appointments versus wellness (P = .011) or recheck (P = .029) appointments, for feline versus canine patients (P = .037), as appointment duration increased (P < .001), and as a client's number of visits in the past year decreased (P = .049). CLINICAL RELEVANCE: Discussing cost of care in veterinary practice continues to be relatively uncommon. Opportunities exist for veterinary professionals to frame their communication of the cost of veterinary care in relation to the benefits offered to the future health and wellbeing of the veterinary patient.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.185
GPT teacher head0.502
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes2
Has abstractyes

Explore more

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