Improving Access to Care by Allowing Self-Referral to a Hepatitis C Clinic
Bibliographic record
Abstract
BACKGROUND: Estimates suggest that more than 250,000 Canadians are infected with hepatitis C virus (HCV), but less than 10% have been treated. Access to specialists in Canada is usually via health care professional (HCP) referral and, therefore, may be a barrier to HCV care. However, clinics that operate in conjunction with the Hepatitis Support Program, Edmonton, Alberta, allow self-referral. It is hypothesized that this improves access to care without increasing inappropriate referrals. OBJECTIVE: To compare the baseline characteristics and outcomes of HCV patients who self-referred with those who were HCP-referred. METHODS: Data were collected from the Hepatitis Support Program HCV database and chart reviews. RESULTS: Between December 17, 2002, and December 31, 2007, 1563 patients were referred including 336 self- (21.5%) and 1227 HCP-referrals (78.5%). Self- and HCP-referred patients were similar in terms of age (mean [+/- SD] 43.0+/-10.3 years versus 43.9+/-10.0 years, respectively; P=0.18), sex (56.8% versus 62.0% [men], respectively; P=0.08) and risk factors for HCV (P=0.3), with 49.7% and 52.6%, respectively, identifying injection drug use as the primary risk factor. The two groups had similar HCV genotype distributions and liver biopsy fibrosis scores with similar treatment rates (31.3% versus 33.2%; P=0.6). Treatment outcomes were excellent (sustained virological response 40.2% for genotype 1, 67% for genotypes 2 and 3) in patients completing therapy and were similar between the two groups. CONCLUSION: Self-referred patients comprised 21.5% of patients accessing care in the clinic. Self- and HCP-referred patients had similar characteristics, treatment rates and outcomes. Facilitating self referral to an HCV clinic can improve access to care, including risk reduction education and HCV treatment.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".