Telemedicine successfully engages marginalized rural hepatitis C patients in curative care
Bibliographic record
Abstract
Background: Rurally located individuals living with hepatitis C virus (HCV) face barriers to engagement and retention in care. Telemedicine technologies coupled with highly curative direct acting antiviral (DAA) treatments may increase accessibility to HCV care while achieving high sustained virologic response (SVR) rates. We compared clinical and socio-economic characteristics, SVR, and loss to follow-up among telemedicine (TM), mixed delivery (MD), and outpatient clinic (OPC) patients receiving care through The Ottawa Hospital Viral Hepatitis Program (TOHVHP). Methods: TOHVHP clinical database was used to evaluate patients engaging HCV care between January 1, 2012, and December 31, 2016. SVR rates by HCV care delivery method (TM versus OPC versus MD) were calculated. Results: Analysis included 1,454 patients who engaged with TOHVHP at least once. Patients were aged almost 50 years on average and were predominately male and Caucasian. A greater proportion of TM patients were rurally based, were Indigenous, had a history of substance use, and had previously been incarcerated. Per-protocol DAA SVR rates for TM, OPC, and MD patients were 100% (26/26), 93% (440/472), and 94% (44/47), respectively. Loss-to-follow-up rates for HCV-treated TM and MD patients were higher (27% [10/37], 95% CI 0.58 to 0.88, and 11% [7/62], 95% CI 0.81 to 0.97, respectively) than for those followed exclusively in the OPC (5% [39/800], 95% CI 0.94 to 0.97). Conclusions: TM can successfully engage, retain, and cure rurally based HCV patients facing barriers to care. Strategies to improve TM retention of patients initiating HCV antiviral treatment are key to optimizing the impact of this model of care.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".