The emergency department as a setting‐specific opportunity for population‐based hepatitis C screening: An economic evaluation
Bibliographic record
Abstract
BACKGROUND AND AIMS: The World Health Organization's hepatitis C virus (HCV) elimination strategy recognizes the need for interventions that identify populations most affected by infection. The emergency department (ED) has been suggested as a setting for HCV screening. The study objective was to explore the health and economic impact of HCV screening in the ED setting. METHODS: We used a microsimulation model to conduct a cost-utility analysis evaluating two ED setting-specific strategies: no screening, and screening and subsequent treatment. Strategies were examined for two populations: (a) the general ED patient population; and (b) ED patients born between 1945 and 1975. The analysis was conducted from a healthcare payer perspective over a lifetime time horizon. A reference and high ED HCV seroprevalence measure were examined in the Canadian healthcare setting.US costs of chronic infection were used for a scenario analysis of screening in the US healthcare setting. RESULTS: For birth cohort screening, in comparison to no screening, one liver-related death was averted for every 760 and 123 persons screened for the reference and high seroprevalence measures. For general population screening, one liver-related death was averted for every 831 and 147 persons screened for the reference and high seroprevalence measures. In comparison to no screening, birth cohort screening was cost-effective at CAN$25,584/quality-adjusted life year (QALY) and US$42,615/QALY. General population screening was cost-effective at CAN$19,733/QALY and US$32,187/QALY. CONCLUSIONS: ED screening may represent a cost-effective component of population-based strategies to eliminate HCV. Further studies are warranted to explore the feasibility and acceptability of this approach.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".