Health care costs associated with chronic hepatitis C virus infection in Ontario, Canada: a retrospective cohort study
Bibliographic record
Abstract
Background: High-quality estimates of health care costs are required to understand the burden of illness and to inform economic models. We estimated the costs associated with hepatitis C virus (HCV) infection from the public payer perspective in Ontario, Canada. Methods: In this population-based retrospective cohort study, we identified patients aged 18–105 years diagnosed with chronic HCV infection in Ontario from 2003 to 2014 using linked administrative data. We allocated the time from diagnosis until death or the end of follow-up (Dec. 31, 2016) to 9 mutually exclusive health states using validated algorithms: no cirrhosis, no cirrhosis (RNA negative) (i.e., cured HCV infection), compensated cirrhosis, decompensated cirrhosis, hepatocellular carcinoma, both decompensated cirrhosis and hepatocellular carcinoma, liver transplantation, terminal (liver-related) and terminal (non–liver-related). We estimated direct medical costs (in 2018 Canadian dollars) per 30 days per health state and used regression models to identify predictors of the costs. Results: We identified 48 239 patients with chronic hepatitis C, of whom 30 763 (63.8%) were men and 35 891 (74.4%) were aged 30–59 years at diagnosis. The mean 30-day costs were $798 (95% confidence interval [CI] $780–$816) (n = 43 568) for no cirrhosis, $661 (95% CI $630–$692) (n = 6422) for no cirrhosis (RNA negative), $1487 (95% CI $1375–$1599) (n = 4970) for compensated cirrhosis, $3659 (95% CI $3279–$4039) (n = 3151) for decompensated cirrhosis, $4238 (95% CI $3480–$4996) (n = 550) for hepatocellular carcinoma, $8753 (95% CI $7130–$10 377) (n = 485) for both decompensated cirrhosis and hepatocellular carcinoma, $4539 (95% CI $3746–$5333) (n = 372) for liver transplantation, $11 202 (95% CI $10 645–$11 760) (n = 3201) for terminal (liver-related) and $8801 (95% CI $8331–$9271) (n = 5278) for terminal (non–liver-related) health states. Comorbidity was the most significant predictor of total costs for all health states. Interpretation: Our findings suggest that the financial burden of HCV infection is substantially higher than previously estimated in Canada. Our comprehensive, up-to-date cost estimates for clinically defined health states of HCV infection should be useful for future economic evaluations related to this disorder.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".