Family medicine–directed hepatitis C care and barriers to treatment: a mixed-methods study
Bibliographic record
Abstract
BACKGROUND: Antivirals for the treatment of hepatitis C virus (HCV) infection are effective, but many patients remain untreated and treatment is not yet routine in primary care. We evaluated the characteristics of patients who engaged in HCV treatment, and clinician perspectives on the barriers and facilitators to treatment. METHODS: Our mixed-method, parallel-design study was conducted at a multisite primary care centre in downtown Toronto. In a retrospective chart review, we searched records from 2011 to 2017 to collect quantitative data, including HCV infection status and HCV treatment status. To contextualize the data, we conducted in-depth interviews with select physicians between Aug. 1 and Nov. 1, 2017, and analyzed the transcripts using content analysis. RESULTS: Of the 40 381 charts reviewed, 727 patients (1.8%, 95% confidence interval [CI] 1.7%-1.9%) were infected with HCV, and 542 (74.6%) had HCV infection requiring treatment. Of those, 255 patients (47.0%) had engaged in treatment. Patients who had engaged in treatment were more likely to be male (odds ratio [OR] 1.63, 95% CI 1.10-2.42), older (OR 1.04 per year increase in age, 95% CI 1.02-1.05) and housed (OR 2.2, 95% CI 1.36-3.75), and they were more likely not to have engaged in injection drug use (OR 1.87, 95% CI 1.33-2.63). Based on interviews with 8 physicians, treatment barriers included a lack of knowledge about HCV treatment, concerns that patients would not adhere to medications and challenges related to medication access. Facilitators of treatment included access to specialist consultation, pharmacist support and primary care treatment guidelines. Common themes that emerged in both quantitative and qualitative components were the roles of unstable housing and intravenous drug use as barriers to engaging in and completing treatment. INTERPRETATION: Our study captured provider-identified barriers to HCV care and the key factors related to retention in HCV care, including gender, age, housing status and experience with drug use. Successful primary-care-led HCV treatment programs may incorporate specialist and pharmacy support and focus on younger, female, underhoused populations and people who use drugs.
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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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| 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".