BUSI 629 Week 7 Discussion Board Forum 7 Example

Discussion Board Forum 7: Economic Evaluation in Health Care

BUSI 629 Economic Analysis in Healthcare, Discussion Board Forum 7

Thread by [Student Name]

The hospital, its emergency department and the classmates are composites; the textbook and the peer-reviewed sources cited are real.

An emergency physician at our 400-bed urban hospital has proposed opt-out hepatitis C testing for high-risk adults who come to the emergency department, with a navigator to link those who test positive to curative antiviral treatment. She estimates that about 6,000 patients a year would qualify and that 4% to 5% would test positive, most of them unaware of their infection. Our chief financial officer asked whether the program is "worth it," and this week's chapter provides a disciplined way to answer.

Lee (2015) explains that cost-effectiveness analysis compares programs by their cost per unit of health gained, commonly measured in quality-adjusted life years, a measure that weights each year lived by how healthy it is. The key figure is the incremental cost-effectiveness ratio: the additional cost of the new program compared with the alternative, divided by the additional quality-adjusted life years it produces. A lower ratio means more health per dollar. Whether a program counts as cost-effective depends on a willingness-to-pay threshold, which American studies commonly place somewhere between $100,000 and $150,000 for each quality-adjusted life year. The chapter also stresses perspective, whose costs and benefits are counted, and sensitivity analysis, which tests whether the conclusion survives changes in uncertain assumptions.

Two analyses are directly relevant. Choi et al. (2024) modeled the long-term cost-effectiveness of Project HEAL, an emergency department program at the University of Illinois that screened high-risk patients for hepatitis C and linked those infected to treatment, using a 30-year horizon from the payer's perspective. Compared with no screening, the incremental ratio ranged from $6,084 to $77,063 per quality-adjusted life year, depending on when untreated patients would otherwise eventually be treated, and screening was cost-effective at a $100,000 threshold in every scenario. When untreated patients would not be treated until they reached decompensated cirrhosis, screening was actually dominant, meaning it saved money and improved health. Girardin et al. (2021) studied screening all psychiatric inpatients in Switzerland rather than only those with substance use disorders and found a ratio of $9,188 per quality-adjusted life year, which remained favorable even at very low prevalence. Both analyses suggest that finding and treating hepatitis C in high-risk settings is excellent value.

The sensitivity analyses matter as much as the base results. Girardin et al. (2021) report that screening remained cost-effective even when prevalence fell as low as 0.07%, far below the 4% to 5% our physician expects, so our decision does not hinge on her estimate being exactly right. Choi et al. (2024) show that the result is most sensitive to what happens to people who are never screened: the later they would otherwise be treated, the more screening saves. The figure that could undermine our program is linkage, the share of positive patients who actually start and finish treatment, because a positive test that leads nowhere adds cost without health. Our pilot should therefore track three numbers each quarter: patients screened, patients linked to care and patients cured.

These are payer or provider perspectives over decades, however, and our hospital's budget works year to year. The study's authors note that U.S. payers often do not cover hepatitis C screening outside primary care, so our hospital would bear the testing and navigation costs while the savings, fewer cases of cirrhosis and liver cancer years from now, accrue largely to insurers and to society. I recommended a two-year pilot funded jointly: the hospital covers screening and navigation, and we ask our two largest Medicaid managed care plans to share costs, since their members would benefit, and apply for public health grants for the remainder. A program can be a bargain for society and still be a loss on one hospital's ledger, and the manager's job is to close that gap rather than to ignore the ratio.

Reply to Yara

Yara, your thread argued that your hospital cannot adopt emergency department hepatitis C screening even if it is cost-effective, because no payer will reimburse the testing in that setting. You are identifying a real problem that Lee (2015) describes as a mismatch of perspective: an economic evaluation done from the payer's or society's viewpoint can find excellent value while the organization asked to deliver the program sees only costs. Choi et al. (2024) point to exactly this gap, noting that U.S. payers often do not cover hepatitis C screening outside primary care even though their model found emergency department screening cost-effective in every scenario. That combination is what makes the decision difficult. I would suggest three ways to close the gap. First, calculate the program's budget impact for your hospital, not only its cost per life-year, so leaders see the actual annual cost, which for a navigator and testing supplies may be modest. Second, approach Medicaid managed care plans with the cost-effectiveness evidence, since they carry many of the members who would be found and treated and would see the long-term savings. Third, look for public health funding aimed at hepatitis C elimination, which often supports exactly this kind of screening. A fourth argument is reputational and regulatory: nonprofit hospitals must show community benefit, and a screening program that finds and cures a serious infection in a population with poor access to primary care is precisely the kind of activity that belongs in a community health needs assessment and its implementation plan. Counting the program there does not create cash, but it does help the board see the spending as part of the mission rather than as a loss. If none of those succeed, a targeted program limited to the highest-risk patients would keep costs lowest while capturing much of the benefit.

Reply to Caleb

Caleb, your thread described your cancer center's debate over a new consolidation therapy for limited-stage small-cell lung cancer, a disease with few treatment advances in decades, and you asked how to interpret a cost-effectiveness study that found it not cost-effective despite a survival benefit. Wang et al. (2026) used a partitioned survival model based on the trial that established the therapy and estimated an incremental cost-effectiveness ratio of $214,185 per quality-adjusted life year from the U.S. payer perspective, above a $150,000 threshold, with a low probability of cost-effectiveness in sensitivity analysis. Only one subgroup approached the threshold, at about $139,910. In China, a patient assistance program reduced the ratio dramatically, to about $18,495, showing how strongly price drives the result. Lee (2015) explains that a ratio above the threshold does not mean a treatment lacks value; it means the health gained costs more than payers usually accept to pay. For your cancer center, the analysis suggests the question is less whether the therapy works than what it costs. Manufacturer assistance, outcomes-based contracts or price negotiation could change the answer, and your financial counselors should make sure eligible patients receive assistance. I would suggest presenting the study to your pharmacy and therapeutics committee along with the price reduction that would bring the ratio under the threshold, which turns a discouraging result into a target for negotiation. It is also worth remembering the limits of a model built on one trial. The study projects survival beyond the trial's follow-up period, and those extrapolated years carry much of the benefit, so the ratio could move as longer follow-up is published. Your committee might approve the therapy for the subgroup closest to the threshold while it waits for that evidence and revisits the decision in a year, with the pharmacy tracking how many patients actually receive it.

References

Choi, S. A., Umashankar, K., Maheswaran, A., Martin, M. T., Lee, J., Odishoo, M., Lin, J. Y., & Touchette, D. R. (2024). Cost-effectiveness analysis of emergency department-based hepatitis C screening and linkage-to-care program. BMC Health Services Research, 24(1), 1308. https://doi.org/10.1186/s12913-024-11793-4

Girardin, F., Painter, C., Hearmon, N., Eddowes, L., Kaiser, S., Negro, F., & Vernaz, N. (2021). Hepatitis C prevalences in the psychiatric setting: Cost-effectiveness of scaling-up screening and direct-acting antiviral therapy. JHEP Reports, 3(3), 100279. https://doi.org/10.1016/j.jhepr.2021.100279

Lee, R. H. (2015). Economics for healthcare managers (3rd ed.). Health Administration Press.

Wang, C., Liu, S., Yang, C., Guo, Y., Zhang, R., Wang, Y., Song, Y., Liu, M., Zhang, R., Xuan, T., Zhao, W., & Li, J. (2026). Cost-effectiveness of durvalumab consolidation therapy in limited-stage small-cell lung cancer: A Chinese and U.S. payer perspective analysis. Journal of Cancer Research and Therapeutics, 22(4), 674-681. https://doi.org/10.4103/jcrt.jcrt_336_26