P169 The cost of elimination: a cost-saving model to deliver and sustain HCV elimination in an urban drug and alcohol service in London
Bibliographic record
Abstract
The NHS England HCV Elimination Programme fostered partnerships between drug treatment services (DTS), the NHS and the pharmaceutical industry. ARC Hounslow, a CNWL-led NHS community DTS, collaborated with HCUL, ChelWest, WL ODN, the HCT and Gilead to achieve and sustain micro-elimination through enhanced testing and access to treatment. As funding models transition from national to local levels, determining the cost-effectiveness of successful HCV elimination models may support local commissioning. ARC Hounslow manages ~1,000 patients annually (2019–2024), with 41% new to treatment and 15–25% having a history of injecting. In 2020, the service launched an HCV elimination programme to identify and test patients at risk of HCV transmission, with annual re-testing and harm reduction for those with ongoing transmission risks. ChelWest delivered fortnightly HCV treatment clinics at ARC Hounslow for HCV RNA+ patients in addition to virtual and home appointments. Patients were supported to complete treatment by ARC Hounslow, ChelWest, WL ODN and HCT. Pathway stakeholders were interviewed to document HCV activities. Staffing costs were provided by ARC Hounslow, HCT and NHS pay bands. Testing and treatment costs were calculated from lab invoices and NHS tariffs. This informed the development of a micro-costing economic model. The model included two main components: micro-costing component which estimated all costs associated with the programme including cost of screening and linkage to care, adherence support, treatment and monitoring, lab and imaging, wages and appointments; long-term cost-effectiveness of implementation, based on a state transition model. To our knowledge, this approach to estimating granular costs relevant to a local service which then informs top-down cost-effectiveness over patients’ lifetime has not yet been adopted in HCV. By 2023, ARC Hounslow achieved micro-elimination. All patients with an injecting history had a known HCV status, with nearly all HCV+ patients treated and cured. This has been sustained for 24 months. The programme was determined to be cost-saving over the long-term using the cost-effectiveness model, with an additional 0.3 quality-adjusted life years (QALYs) gained and cost-savings of £2,015 per patient. Projected to overall caseload, upfront costs of the programme of £169,325 resulted in overall lifetime cost-savings of £3,010,450 to the healthcare system achieved by long-term reductions in disease severity and liver-related events offsetting initial costs. ARC Hounslow demonstrated that a comprehensive testing and partnership model enables successful, sustained HCV micro-elimination. This approach reduces morbidity and proves cost-saving longer term. Disclosure Economic model and some staff costs funded by Gilead.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".