Potential interventions to support HCV treatment uptake among HIV co-infected people in Canada: Perceptions of patients and health care providers
Bibliographic record
Abstract
BACKGROUND: Increasing direct-acting antiviral (DAA) treatment uptake is key to eliminating HCV infection as a public health threat in Canada. People living with human immunodeficiency virus (HIV) and hepatitis C (HCV) co-infection face barriers to HCV treatment initiation. We sought to identify interventions that could support HCV treatment initiation based on patient and HCV care provider perspectives. METHODS: = 6). Following the nominal group technique, transcripts and intervention lists underwent thematic analysis and ranking scores were merged to create consolidated and prioritized lists from patient and provider perspectives. RESULTS: Patient participants identified a total of eight interventions. The highest-ranked interventions were multidisciplinary clinics, HCV awareness campaigns and patient education, nurse- or pharmacist-led care, peer involvement, and more and better-prepared health professionals. Provider participants identified 11 interventions. The highest-ranked were mobile outreach, DAA initiation at pharmacies, a simplified process of DAA prescription, integration of primary and specialist care, and patient-centred approaches. CONCLUSION: Participants proposed alternatives to hospital-based specialist HCV care, which require increasing capacity for nurses, pharmacists, primary care providers, and peers to have more direct roles in HCV treatment provision. They also identified the need for structural changes and educational initiatives. In addition to optimizing HCV care, these interventions might result in broader benefits for the health of HIV-HCV co-infected people.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".