Hepatitis C screening in community pharmacies—A feasibility and knowledge transfer study: PHARMA-C
Bibliographic record
Abstract
Background: New strategies are needed to increase access to hepatitis C virus (HCV) testing. This study evaluated the feasibility of HCV rapid testing in community pharmacies in Quebec (Canada) and assessed knowledge transfer (KT). Methods: PHARMA-C was a 6-month (February to September 2022) prospective KT study. Community pharmacists (CPs) were recruited and trained to identify HCV risk factors, conduct rapid antibody tests (OraQuickHCV), and pre- and post-test counselling, and link positive cases to care. Health care users (HUs) were included according to HCV risk factors. An advisory committee and focus groups provided guidance, feedback, and identified barriers and facilitators to improve the program. A pre- and post-intervention questionnaire was completed by CPs to assess feasibility and KT. HUs completed a satisfaction survey. Results: A total of 32 CPs were included and 16 performed 101 HCV tests. Two positive cases were identified and linked to care. Comparison of pre- and post-intervention surveys shows that pharmacists felt more confident in identifying HCV risk factors, communicating information to patients related to HCV, and performing the HCV screening test at the end of the intervention. HCV screening in pharmacies was considered feasible by 77.8% of CPs. The intervention lasted approximately 22 minutes. The main barriers to implementation were lack of time and fear of stigmatizing HUs. Promotional material and training were the main facilitators. Conclusion: HCV point-of-care testing by CPs is feasible in Quebec. Expanding pharmacists' scope of practice to include HCV screening and increasing pharmacists' role in the HCV care cascade is encouraged in order to further efforts toward HCV elimination.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".