Cost Effectiveness and Resource Allocation最新文献

Background: In recent years, new treatment options for chronic lymphocytic leukemia (CLL) have shown great potential. In China, the large CLL patient base translates into considerable clinical and economic burden, factors such as cost-effectiveness will be of significant importance in guiding government decision-making.

Objective: In this study, a cost-effectiveness analysis was conducted to assess the health economic value of two important first-line treatment options for CLL.

Methods: This study developed a partitioned survival model with three health states to analyze the cost-effectiveness (CE) of Venetoclax (Ven) + Obinutuzumab (Obi) and Chlorambucil (Chl) + Obi as first-line treatments for adult CLL. The transition probabilities were calculated using data from a clinical trial. Healthcare resource utilization and costs were obtained from publicly available data and expert interviews. The tool used to calculate quality-adjusted life years (QALYs) was derived from clinical trials and literature reviews. The primary outcome measure was the incremental cost-effectiveness ratio (ICER), expressed as cost per QALYs gained.We adopted a willingness-to-pay threshold of CNY 266,203 per QALY(China, 2022).

Results: In the base case, the Ven + Obi group obtained 1.29 QALYs more than the Chl + Obi group, with a cost reduction of 152,877.43¥. Sensitivity analysis and scenario analysis results showed that even when the main parameters in the model changed within plausible ranges, the ICER of the Ven + Obi group remained cost-effective. In probabilistic sensitivity analysis, 99% of the iterations were cost-effective under the threshold.

Conclusion: This study demonstrates that, the combination of Ven + Obi as a frontline treatment for CLL is superior to Chl + Obi in terms of cost-effectiveness. Sensitivity analysis indicates that treatment costs will significantly decrease after the patent protection period of these drugs expires.

Health economics is crucial for optimizing resource allocation and achieving equitable health outcomes in Africa. This study reviewed the historical evolution and current state of health economics in Africa, focusing on healthcare financing mechanisms, resource allocation strategies, and policy interventions. Data from peer-reviewed articles, research reports, and grey literature were synthesized from databases like PubMed, Scopus, Google Scholar and African Journals Online (AJOL). While healthcare financing dominated the literature, this review also covers resource allocation and broader health economics, highlighting key gaps in African research. Findings highlight significant challenges such as low public expenditure, high out-of-pocket costs, and inadequate insurance coverage. Out-of-pocket payments constitute over 40% of total health expenditure in half of the studied countries, while public health expenditure remains between $8 and $129 per capita annually, far below the $4,000 per capita in high-income countries. Only three African countries have met the Abuja Declaration target of allocating 15% of government budgets to health. Innovative financing mechanisms, such as community-based health insurance schemes and public-private partnerships, show promise in expanding coverage and improving service delivery. However, challenges in implementation, financial sustainability, and socio-cultural barriers persist. Technological innovations, including digital health solutions and telemedicine, could enhance efficiency by up to 15% by 2030. Primary challenges in Africa's health resource allocation include insufficient funding, inadequate human resources, inefficient management, poor data quality, and lack of political commitment. Policy recommendations include increasing public investment in health, improving resource allocation efficiency, and fostering sustainable financing through private sector and international donor partnerships.

Background: To carry out external validation of the analysis of the budget impact of the drug fingolimod after its incorporation into the Brazilian Unified Health System, comparing the real parameters arising from its incorporation in the treatment of relapsing-remitting multiple sclerosis with the estimates presented in the incorporation report in 2017. This topic is highly pertinent and makes a valuable contribution to the sparse literature on real-world BIA validation, especially in low- and middle-income countries like Brazil, yielding crucial insights for enhancing health policy optimization.

Methods: Survey of the target population validated by demand measured through the dispensing of drugs, in the Brazilian Unified Health System of patients with multiple sclerosis; validation of the unit costs of drugs through purchases made by the Logistics Department of the Ministry of Health; determination of market share within the time horizon defined based on drugs purchases; estimation of direct administration costs; and monitoring of drugs to compare estimated values with the real value.

Results: Divergences were identified between real-life data collected in relation to the study's defined population and the market share of the drug fingolimod over the studied time horizon. There was a significant increase in the fingolimod market share, with the bigger market shares being in 2019 and 2020. The budget impact presented in the incorporation report was US$ 277,431,260.28, and the validated impact was US$ 194,955,442.76.

Conclusions: The validation process of the budget impact analysis of the incorporation of the drug fingolimod in 2017 resulted in savings of around US$ 82,4 million in relation to the value proposed for incorporation.

Background: Understanding insurance preferences for mental health services can help provide appropriate service demand and insurance coverage for such services.

Objectives: The present research aimed to investigate the preferences and willingness to pay of the people of Tehran for mental health insurance services using the discrete experiment method.

Methods: Quantitative methods were used in this applied research and it was conducted on 420 individuals (210 patients with mental disorders and 210 healthy people) using a discrete choice experiment. The data analysis was performed using the conditional regression model as well.

Results: The final model in this study included 6 attributes. The findings of the present research showed a statistically significant relationship (P < .001) between the odds ratios (OR) of choosing health insurance at all levels of insurance coverage except the service limit and the amount of insurance premium. Along with the increase in the cost coverage levels, the likelihood of choosing health insurance for the benefits of inpatient services at 70% and 90% levels (P < .001, OR = 1.96 and P < .001, OR = 2.28), outpatient services at 70% and 90% levels (P < .001, OR = 1.53 and P < .001, OR = 1.64), service delivery location (P < .001, OR = 1.54), and the use of online services (P < .001, OR = 0.84) increased significantly.

Conclusions: The findings showed that the people of Tehran had the highest preference and willingness to pay for the coverage of inpatient services. The results of this study can be provided to health managers and policy makers to predict the welfare effects and people's reactions to changes in mental health insurance policies so that they would be able to plan better to provide higher-quality services with the participation of people.