Telemedicine and hybrid engagement models facilitate hepatitis C cascade of care during periods of healthcare disruption
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVES: To assess the utility of telemedicine in the provision of hepatitis C care, we compared characteristics and outcomes of HCV-infected patients engaging in standard in-clinic care, telemedicine only (TM), and hybrid (HB) models of care across pre-, peri‑ and post-COVID-19 pandemic periods. PATIENTS AND METHODS: HCV RNA-positive patients assessed between October 2017 and March 2025 at The Ottawa Hospital Viral Hepatitis Program (Ottawa, Canada) were retrospectively analyzed. RESULTS: Of 1118 patients, 626 (56.0%) engaged in standard care, 139 (12.4%) in TM care, and 353 (31.6%) in HB care. TM group patients were less likely to have immigrated, experienced substance abuse, housing instability, incarceration, or psychiatric conditions, or be based in Ottawa. Utilization of HB and TM care was highest during the pandemic. Across all time periods, HB care demonstrated higher DAA treatment initiation and completion compared to standard or TM care (standard: 81.5 %; TM: 79.1 %; HB: 92.1 %, p < 0.01) and (standard: 91.3%; TM: 93.6%; HB: 96.3%, p = 0.02), respectively, with no difference in SVR. During the pandemic, a greater proportion of patients experiencing barriers to cure engaged in HB or TM care and achieved DAA completion (pre: 91.1%; pandemic: 98.1%; post: 95.8%, p < 0.01). HB care was associated with increased odds of DAA initiation (OR = 2.87; 95% CI 1.82 to 4.53), including patient populations experiencing barriers to cure (OR = 2.35; 95% CI 1.35 to 4.07). CONCLUSIONS: HB models demonstrate potential in addressing public health challenges and engaging marginalized populations, supporting increased integration into HCV care programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".