Billing for Cognitive Services: Understanding Québec Pharmacists' Behavior
Bibliographic record
Abstract
BACKGROUND: There is growing evidence that pharmacists' interventions to solve drug-related problems are effective and cost-saving. Since 1978, under the Quebec provincial drug plan, payment for two cognitive services, the pharmaceutical opinion and the refusal to dispense a prescription, has been disbursed to community pharmacists. However, the number of claims for these services lags far behind expectations. OBJECTIVE: To identify factors influencing Quebec community pharmacists in the billing for a pharmaceutical opinion or for a refusal to dispense. METHODS: Questions on predisposing, enabling, and reinforcing factors potentially related to pharmacists' behavior were included in a self-administered questionnaire sent to all 3517 community pharmacists practicing in the province of Quebec during 1996. Using multivariate logistic regression, models were built to explain billing for an opinion and billing for a refusal. RESULTS: According to our models, the typical pharmacist who billed for opinions or refusals in Quebec is <45 years of age, has attended a continuing education program on this topic, and believes that billing for interventions is important. This typical pharmacist handles a mean daily volume of 100-250 prescriptions, uses a decision-support computer program, and has sufficient technical staff assistance. This pharmacist believes that interventions can be billed rapidly and are consistently paid by the province's drug plan. CONCLUSIONS: In order to increase the billing of pharmaceutical care in community pharmacies, tailored educational programs should be offered to pharmacists. There is also a need to improve working conditions in pharmacies.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".