Strokes remain a leading cause of death and disability worldwide. The STROKE OWL study evaluated a novel case management approach for patients with stroke (modified Rankin Scale 0-4) or transient ischemic attack (TIA) who received support across healthcare settings and secondary prevention training from case managers for one year. The primary aim of this quasi-experimental study was a reduction in stroke recurrence. Here, we report the results of a health economic analysis of the STROKE OWL study, conducted in accordance with CHEERS guidelines. The calculations were based on claims data of cooperating statutory health insurance companies. In addition to a regression analysis for cost comparison, the incremental cost-effectiveness ratio was determined, and a probabilistic sensitivity analysis was carried out. In total, 1167 patients per group were included in the analysis. The intervention group incurred 32.3% higher direct costs (p < 0.001) than the control group. With a difference of EUR 1384.78 (95% CI: [1.2384-1.4143], p < 0.0001) and a 5.32% increase in hazards for the intervention group (HR = 1.0532, 95% CI: [0.7869-1.4096], p = 0.7274) resulting in an ICER of EUR 260.30, we found that the case management intervention dominated in the total stroke population, even for an arbitrarily high willingness to pay. In the TIA subgroup, however, the intervention was cost-effective even for a low willingness to pay. Our results are limited by small samples for both TIA and severe stroke patients and by claims data heterogeneity for some cost components, which had to be excluded from the analysis. Future research should investigate the cost-effectiveness of case management interventions for both severe stroke and TIA populations using appropriate data.

OBJECTIVE: Assessing the value of tumor-agnostic drugs (TAD) is challenging given the potential variability in treatment effects, trials with small sample sizes, different standards of care (SoC), and lack of comparative data from single-arm basket trials. Our study developed and applied novel methods to assess the value of pembrolizumab compared with SoC to inform coverage decisions.
METHODS: We developed a partitioned survival model to evaluate the cost-utility of pembrolizumab for previously treated patients with 8 advanced or metastatic microsatellite instability-high or mismatch repair-deficient cancers from a US commercial payer perspective. Efficacy of pembrolizumab was based on data from trials directly or with adjustment using Bayesian hierarchical models. Eight chemotherapy-based external control arms were constructed from the TriNetX electronic health record databases. Tumor-specific health-state utility values were applied. All costs were adjusted to 2022 US dollars.
RESULTS: At a lifetime horizon, pembrolizumab was associated with increased effectiveness compared with chemotherapies in colorectal (quality-adjusted life years [QALYs]: +0.64, life years [LYs]: +0.64), endometrial (QALYs: +3.79, LYs: +5.47), and small intestine cancers (QALYs: +1.73, LYs: +2.48), but not for patients with metastatic gastric, cholangiocarcinoma, pancreatic, ovarian, and brain cancers. Incremental cost-effectiveness ratios varied substantially across tumor types. Pembrolizumab was found to be cost-effective in treating colorectal and endometrial cancers (incremental cost-effectiveness ratios: $121 967 and $139 257, respectively), and not cost-effective for other assessed cancers at a $150 000 willingness-to-pay/QALY threshold, compared with SoC chemotherapies.
CONCLUSIONS: The cost-effectiveness of TADs can vary by cancers. Using analytic tools such as external controls and Bayesian hierarchical models can tackle several challenges in assessing the value of TADs and uncertainties from basket trials.

BACKGROUND: Training plays a role in reducing traffic accidents, and evaluating the effectiveness of training programs in managers\' decision-making for training continuation is important. Thus, the present study aimed to evaluate the cost-effectiveness of a single-credit traffic safety course based on the four levels of the Kirkpatrick model in all Iranian universities.
METHODS: This interventional study aimed to evaluate the cost-effectiveness of a single-credit traffic safety course based on the Kirkpatrick model from 2016 to 2020 in Iran. The data were collected in three stages: (1) calculating the costs of offering traffic safety courses, (2) determining the effectiveness of providing such courses based on the levels of the Kirkpatrick model, and (3) evaluating the cost-effectiveness of administering traffic safety courses. Data were collected through researcher-made and standardized questionnaires. The research population included traffic safety course instructors and university students who could take this course. Finally, the data were analyzed with SPSS v. 23 and also calculations related to ICER, which shows the cost effectiveness of providing single credit course.
RESULTS: Scores of the students\' reaction level to the traffic safety course was 41.8% before the course; this score was estimated at 67% after the course. At the level of learning, students\' knowledge was 43.6% before the training course, which reached 73% after the course. At the level of behavior, the state of students\' desirable traffic behaviors was 54% before the course, which reached 66.1% after the course. The educational effectiveness of the course presentation at the level of results was 58.2% before and 74.8% after the course. While assuming that the weights of all model levels were constant, the cost of a 1% increase in the overall educational effectiveness by using the Kirkpatrick model, compared to not providing the course (not administering the intervention) was 486.46 USD.
CONCLUSIONS: The results showcased the effectiveness of the traffic safety course in all four levels of The Kirkpatrick model. Therefore, policy-makers and officials in charge of delivering this program should strengthen it and resolve its deficiencies to realize all its educational goals at the highest level.

BACKGROUND: The partitioned survival model (PSM) and the state transition model (STM) are widely used in cost-effectiveness analyses of anticancer drugs. Using different modeling approaches with or without consideration of brain metastasis, we compared the quality-adjusted life-year (QALY) estimates of Osimertinib and pemetrexed-platinum in advanced non-small cell lung cancer with epidermal growth factor receptor mutations.
METHODS: We constructed three economic models using parametric curves fitted to patient-level data from the National Health Insurance Review and Assessment claims database from 2009 to 2020. PSM and 3-health state transition model (3-STM) consist of three health states: progression-free, post-progression, and death. The 5-health state transition model (5-STM) has two additional health states (brain metastasis with continuing initial therapy, and with subsequent therapy). Time-dependent transition probabilities were calculated in the state transition models. The incremental life-year (LY) and QALY between the Osimertinib and pemetrexed-platinum cohorts for each modeling approach were estimated over seven years.
RESULTS: The PSM and 3-STM produced similar incremental LY (0.889 and 0.899, respectively) and QALY (0.827 and 0.840, respectively). However, 5-STM, which considered brain metastasis as separate health states, yielded a slightly higher incremental LY (0.910) but lower incremental QALY (0.695) than PSM and 3-STM.
CONCLUSIONS: Our findings indicate that incorporating additional health states such as brain metastases into economic models can have a considerable impact on incremental QALY estimates. To ensure appropriate health technology assessment decisions, comparison and justification of different modeling approaches are recommended in the economic evaluation of anticancer drugs.

BACKGROUND: Active case finding (ACF) is a potentially promising approach for the early identification and treatment of tuberculosis patients. However, evidence on its cost-effectiveness, particularly in low- and middle-income countries, remains limited. This study evaluates the cost-effectiveness of a community-based ACF practice in Shenzhen, China.
METHODS: We employed a Markov model-based decision analytic method to assess the costs and effectiveness of 3 tuberculosis detection strategies: passive case finding (PCF), basic ACF, and advanced ACF. The analysis was conducted from a societal perspective on a dynamic cohort over a 20-year horizon, focusing on active tuberculosis (ATB) prevalence and the incremental cost-effectiveness ratio (ICER).
RESULTS: Compared to the PCF strategy, the basic and advanced ACF strategies effectively reduced ATB cases by 6.8 and 10.2 per 100 000 population, respectively, by the final year of this 20-year period. The ICER for the basic and advanced ACF strategies were ¥14 757 and ¥8217 per quality-adjusted life-year, respectively. Both values fell below the cost-effectiveness threshold.
CONCLUSIONS: Our findings indicate that the community-based ACF screening strategy, which targets individuals exhibiting tuberculosis symptoms, is cost-effective. This underscores the potential benefits of adopting similar community-based ACF strategies for symptomatic populations in tuberculosis-endemic areas.

BACKGROUND: The standard passive case-finding strategy implemented by most developing countries is inadequate to detect new cases of Tuberculosis. A household contact investigation is an alternative approach. However, there is limited cost-effectiveness data to support planning and implementation in low and middle-income countries. The study aimed to evaluate the cost-effectiveness of adding household contact investigation (HCI) to the passive case-finding (PCF) strategy in the Tuberculosis control program in Southwestern Uganda.
METHODS: We conducted an economic evaluation using a retrospective study approach and bottom-up costing (ingredients) techniques. It was a synthesis-based evaluation of existing data extracted from the District Health Information System (DHIS 2), TB registers, and a primary cost survey. The study compared two methods of Tuberculosis (TB) case finding (PCF and HCI) strategies. Regarding PCF, patients either self-reported their signs and symptoms or were prompted by healthcare workers. At the same time, HCI was done by home visiting and screening contacts of TB patients. Patients and household contacts presumed to have Tuberculosis were requested to produce samples for analysis. We applied a static decision-analytic modeling framework to examine both strategies\' costs and effectiveness. The study relied on cost and probability estimates from National Tuberculosis (TB) program data, activity costs, and published literature. It was performed from the societal and provider perspectives over 1.5 years across 12 facilities in Ntungamo, Sheema, and Rwampara Districts. The primary effectiveness measure was the number of TB cases detected (yield) and the number needed to screen (NNS). The TB yield was calculated from the number of patients screened during the period under study. The incremental cost-effectiveness ratio (ICER) was expressed as cost in 2021 US$ per additional TB case detected. We did not apply a discount rate because of the short analytic time horizon.
RESULTS: The unit costs of detecting a Tuberculosis case were US$ (United States dollar) 204.22 for PCF and US$ 315.07 for HCI. Patient and caregiver costs are five times more in PCF than in HCI [US$26.37 Vs. US$ 5.42]. The ICER was US$ 3,596.94 per additional TB case detected. The TB screening yields were 0.52% (1496/289140) for passive case finding and 5.8% (197/3414) for household contact investigation. Household contact investigation yield among children 0-14 Vs. 15+ years [6.2% Vs.5.4%] P = 0.04. The Yield among People living with HIV (PLHIV) Vs. HIV-negative [15.8% Vs.5.3%] P = 0.03 in HHCI. The PCF yield in men Vs. Women [1.12% Vs.0.28%] P<0.01. The NNS in PCF was 193 [95% CI: 186-294] and 17 [95% CI: 14-22] in HCI.
CONCLUSIONS: Our baseline assumptions and the specific implementations of adding HCI to existing PCF programs in the context of rural African settings prove to be not cost-effective, rather than HCI as a strategy. HCI effectively identifies children and PLHIV with TB and should be prioritized. Meanwhile, the Passive case-finding strategy effectively finds men with TB and costs lower than household contact investigation.

In France, the funding of mental health institutions relies on an annual budget allocation. Esketamine, a non-competitive NMDA glutamate receptor antagonist, has been approved for adults with treatment-resistant major depressive disorder since 2019. However, due to its high cost (€200 per 28 mg device, excluding tax), the aim of this work was to evaluate whether the income received by an institution for the management of a patient treated with Esketamine could cover the purchase of devices, based on real clinical data. Within our institution, seven patients underwent treatment with Esketamine during the study period resulting in a total usage of 714 devices, amounting to a purchase cost of €142,800. Over the course of the follow-up period, the institution received €149,054 in revenue for the treatment of these patients. Our analysis reveals that the expense associated with Esketamine constitutes 95.8 % of the income generated from caring for these patients. This not only raises questions about the pricing of this drug but also highlights the lack of a funding system for costly psychiatric drugs. This concern extends to somatic treatments associated with psychiatric care.

Setting priorities in healthcare is always contentious given the array of possible services at primary, secondary, and tertiary levels of care, not to mention potential public health interventions. The central goals in global policy have been reducing inequity within and between countries, protecting vulnerable groups (particularly women and children) and reducing the major communicable diseases which have historically been a major burden in lower- and middle-income countries. Here limited relative and absolute spending on healthcare have spurred a series of initiatives in Global Health over the last 50 years which have led to significant gains in measures of morbidity and mortality. Against this background there remains the continuing question of how to adapt current medical practice in higher income countries for training and planning of services in lower- and middle-income countries. Here, the historical development of Global Health is outlined, and lessons drawn from the surveys of the global burden of disease and health economic analysis to understand how we can apply these principles to define Global Hematology. It remains likely that in lower-income countries effort should be concentrated on developing laboratory services and blood transfusion, to allow safe and effective support for the assessment of treatment of anemia, sickle cell disease, maternal and child health and urgent surgery and obstetric services. However, the principles of Global Health, could also be used for hematological malignancies to develop a framework for Global Hematology for all settings.

BACKGROUND: Cost-effectiveness analysis (CEA) is a standard tool for evaluating health programs and informing decisions about resource allocation and prioritization. Most CEAs evaluating health interventions in low- and middle-income countries adopt a health sector perspective, accounting for resources funded by international donors and country governments, while often excluding out-of-pocket expenditures and time costs borne by program beneficiaries. Even when patients\' costs are included, a companion analysis focused on the patient perspective is rarely performed. We view this as a missed opportunity.
METHODS: We developed methods for assessing intervention affordability and evaluating whether optimal interventions from the health sector perspective also represent efficient and affordable options for patients. We mapped the five different patterns that a comparison of the perspective results can yield into a practical framework, and we provided guidance for researchers and decision-makers on how to use results from multiple perspectives. To illustrate the methodology, we conducted a CEA of six HIV treatment delivery models in Mozambique. We conducted a Monte Carlo microsimulation with probabilistic sensitivity analysis from both patient and health sector perspectives, generating incremental cost-effectiveness ratios for the treatment approaches. We also calculated annualized patient costs for the treatment approaches, comparing the costs with an affordability threshold. We then compared the cost-effectiveness and affordability results from the two perspectives using the framework we developed.
RESULTS: In this case, the two perspectives did not produce a shared optimal approach for HIV treatment at the willingness-to-pay threshold of 0.3 × Mozambique\'s annual GDP per capita per DALY averted. However, the clinical 6-month antiretroviral drug distribution strategy, which is optimal from the health sector perspective, is efficient and affordable from the patient perspective. All treatment approaches, except clinical 1-month distributions of antiretroviral drugs which were standard before Covid-19, had an annual cost to patients less than the country\'s annual average for out-of-pocket health expenditures.
CONCLUSIONS: Including a patient perspective in CEAs and explicitly considering affordability offers decision-makers additional insights either by confirming that the optimal strategy from the health sector perspective is also efficient and affordable from the patient perspective or by identifying incongruencies in value or affordability that could affect patient participation.

Cervical cancer (CC) is globally ranked fourth in terms of incidence and mortality among women. Vaccination against Human Papillomavirus (HPV) and screening programs can significantly reduce CC mortality rates. Hence, executing cost-effective public health policies for prevention and surveillance is crucial. However, defining policies that make the best use of the available resources is not easy, as it requires predicting the long-term costs and results of interventions on a changing population. Since the simpler task of predicting the results of public health policies is difficult, devising those that make the best usage of available resources is an arduous challenge for decision-makers.
This paper proposes a fine-grained epidemiological simulation model based on differential equations, to effectively predict the costs and effectiveness of CC public health policies that include vaccination and screening. The model represents population dynamics, HPV transmission within the population, likelihood of infection clearance, virus-induced appearance of precancerous lesions and eventually CC, as well as immunity gained with vaccination and early detection with screening.
We offer a compartmentalized modeling approach that separates population, epidemics, and intervention concerns. We instantiate models with actual data from a Colombian case study and analyze their results to show how our modeling approach can support CEA studies. Moreover, we implement models in an open-source software tool to simultaneously define and evaluate multiple policies. With the support of the tool, we analyze 54 policies within a 30-year time horizon and use as a comparator the CC policy that has been used until recently. We identify 8 dominant policies, the best one with an ICER of 6.3 million COP (Colombian Pesos) per averted DALY. We also validate the modeling approach against the available population and HPV epidemic data. The effects of uncertainty in the values of key parameters (discount rate, sensitivity of screening tests) is evaluated through one-way sensitivity analysis.
Our modeling approach can provide valuable support for healthcare decision-makers. The implementation into an automated tool allows customizing the analysis with country-specific data, flexibly defining public health policies to be evaluated, and conducting disaggregate analyses of their cost and effectiveness.