Health Economics Review最新文献

Background: Recently, the endovascular treatment (EVT) of acute ischemic stroke has made significant progress in many aspects. Intravenous thrombolysis (IVT) is usually recommended before endovascular treatment in clinical practice, but the value of the practice is controversial. The latest meta-analysis evaluation was that the effect of EVT versus EVT plus IVT did not differ significantly. The cost-effectiveness analysis of EVT plus IVT needs further analysis. This study assesses the health benefits and economic impact of EVT plus IVT in Shandong Peninsula of China.

Method: We followed a cross-section design using the Chinese-Shandong Peninsula public hospital database between 2013 and 2023. The real-world costs and health outcomes were collected through the Hospital Information System (HIS) and published references. We calculated incremental cost-effectiveness ratios (ICERs) from the perspective of Chinese healthcare using the complex decision model to compare the costs and effectiveness between EVT versus EVT + IVT. One-way and Monte Carlo probabilistic sensitivity analyses were performed to assess the robustness of the economic evaluation model.

Results: EVT alone had a lower cost compared with EVT + IVT whether short-term or long-term. Until 99% dead of AIS patients, the ICER per additional QALY was RMB696399.30 over the willingness-to-pay (WTP) threshold of 3× gross domestic product (GDP) per capita in Shandong. The probabilistic sensitivity analysis of 3 months, 1 year and long-term horizons had a 97.90%, 97.43% and 96.89% probability of cost-effective treatment under the WTP threshold (1×GDP). The results of the one-way sensitivity analysis showed that direct treatment costs for EVT alone and EVT + IVT were all sensitive to ICER.

Conclusions: EVT alone was more cost-effective treatment compared to EVT + IVT in the Northeast Coastal Area of China. The data of this study could be used as a reference in China, and the use of the evaluation in other regions should be carefully considered.

Background: Earlier studies have estimated the impact of increased body mass index (BMI) on healthcare costs. Various methods have been used to avoid potential biases and inconsistencies. Each of these methods measure different local effects and have different strengths and weaknesses.

Methods: In the current study we estimate the impact of increased BMI on healthcare costs using nine common methods from the literature: multivariable regression analyses (ordinary least squares, generalized linear models, and two-part models), and instrumental variable models (using previously measured BMI, offspring BMI, and three different weighted genetic risk scores as instruments for BMI). We stratified by sex, investigated the implications of confounder adjustment, and modelled both linear and non-linear associations.

Results: There was a positive effect of increased BMI in both males and females in each approach. The cost of elevated BMI was higher in models that, to a greater extent, account for endogenous relations.

Conclusion: The study provides solid evidence that there is an association between BMI and healthcare costs, and demonstrates the importance of triangulation.

Background: Estimating program costs when planning community-based mental health programs can be burdensome. Our aim was to retrospectively document the cost for the first year of planning and implementing Healthy Minds Healthy Communities (HMHC), a mental health promotion and prevention multi-level intervention initiative. This Program is among the first to use the Community Initiated Care (CIC) model in the US and is aimed at building community resilience and the capacity for communities to provide mental health support, particularly among those disproportionately impacted by COVID-19. Our objective is to share our methods for costing a program targeting 10 zip codes that are ethnically and linguistically diverse and provide an example for estimating the cost of a mental health prevention and promotion programs consisting of multiple evidence-based interventions.

Methods: We used a semi-structured interview process to collect cost data through the first year of program planning, start-up and initial implementation from key staff. We calculated costs for each activity, grouped them by major project categories, and identified the cost drivers of each category. We further validated cost estimates through extensive literature review. The cost analysis was done from the provider's perspective, which included the implementing agency and its community partners. We delineated costs that were in-kind contributions to the program by other agency, and community partners. Sensitivity analyses were conducted to estimate uncertainty around parameters.

Results: For the first year of the development and implementation of the program, (funded through program and in-kind) is estimated at $1,382,669 (2022 US$). The costs for the three main activity domains for this project are: project management $135,822, community engagement $364,216 and design and execution $756,934. Overall, the cost drivers for the first year of this intervention were: hiring and onboarding staff, in-person community building/learning sessions, communications and marketing, and intervention delivery.

Conclusion: Implementation of community-based mental health promotion and prevention programs, when utilizing a participatory approach, requires a significant amount of upfront investment in program planning and development. A large proportion of this investment tends to be human capital input. Developing partnerships is a successful strategy for defraying costs.

Background: With the increasing demand for fertility services, it is urgent to select the most cost-effective assisted reproductive technology (ART) treatment plan and include it in medical insurance. Economic evaluation reports are an important reference for medical insurance negotiation. The aim of this study is to systematically evaluate the economic evaluation research of ART, analyze the existing shortcomings, and provide a reference for the economic evaluation of ART.

Methods: PubMed, EMbase, Web of Science, Cochrane Library and ScienceDirect databases were searched for relevant articles on the economic evaluation of ART. These articles were screened, and their quality was evaluated based on the Comprehensive Health Economics Evaluation Report Standard (CHEERS 2022), and the data on the basic characteristics, model characteristics and other aspects of the included studies were summarized.

Results: One hundred and two related articles were obtained in the preliminary search, but based on the inclusion criteria, 12 studies were used for the analysis, of which nine used the decision tree model. The model parameters were mainly derived from published literature and included retrospective clinical data of patients. Only two studies included direct non-medical and indirect costs in the cost measurement. Live birth rate was used as an outcome indicator in half of the studies.

Conclusion: Suggesting the setting of the threshold range in the field of fertility should be actively discussed, and the monetary value of each live birth is assumed to be in a certain range when the WTP threshold for fertility is uncertain. The range of the parameter sources should be expanded. Direct non-medical and indirect costs should be included in the calculation of costs, and the analysis should be carried out from the perspective of the whole society. In the evaluation of clinical effect, the effectiveness and safety indexes should be selected for a comprehensive evaluation, thereby making the evaluation more comprehensive and reliable. At least subgroup analysis based on age stratification should be considered in the relevant economic evaluation.

Background: Due to population aging, healthcare expenditure is projected to increase substantially in developed countries like Spain. However, prior research indicates that health status, not merely age, is a key driver of healthcare costs. This study analyzed data from over 1.25 million residents of Spain's Murcia region to develop a capitation-based healthcare financing model incorporating health status via Adjusted Morbidity Groups (AMGs). The goal was to simulate an equitable area-based healthcare budget allocation reflecting population needs.

Methods: Using 2017 data on residents' age, sex, AMG designation, and individual healthcare costs, generalized linear models were built to predict healthcare expenditure based on health status indicators. Multiple link functions and distribution families were tested, with model selection guided by information criteria, residual analysis, and goodness-of-fit statistics. The selected model was used to estimate adjusted populations and simulate capitated budgets for the 9 healthcare districts in Murcia.

Results: The gamma distribution with logarithmic link function provided the best model fit. Comparisons of predicted and actual average costs revealed underfunded and overfunded areas within Murcia. If implemented, the capitation model would decrease funding for most districts (up to 15.5%) while increasing it for two high-need areas, emphasizing allocation based on health status and standardized utilization rather than historical spending alone.

Conclusions: AMG-based capitated budgeting could improve equity in healthcare financing across regions in Spain. By explicitly incorporating multimorbidity burden into allocation formulas, resources can be reallocated towards areas with poorer overall population health. Further policy analysis and adjustment is needed before full-scale implementation of such need-based global budgets.

Introduction: In 2022, updated guidance from NICE expanded the options for self-monitoring of blood glucose for patients with type 2 diabetes (T2DM), to include continuous glucose monitoring (CGM). In this budget impact analysis, the cost impact of CGM was compared with traditional self-monitoring of blood glucose (SMBG) in adults with T2DM over 1 year from the commissioner perspective in England.

Research design and methods: The NICE-eligible T2DM cohort was split into 4 subgroups to enable nuanced costing by insulin administration frequency: basal human insulin, premixed insulin, basal-bolus insulin and bolus insulin. The model's cost components comprised mild and severe hypoglycaemia (SH), diabetic ketoacidosis (DKA), consumables and healthcare resource utilisation in primary and secondary care.

Results: The introduction of CGM is estimated to be cost additive by approximately £4.6 million in the basecase, driven by increased spending on the CGM device. Overall, healthcare activity was reduced by approximately 20,000 attendances, due to fewer SH and DKA episodes in the CGM arm. General Practitioner (GP) practice-based activity is expected to drop after the first year as patients requiring CGM training is reduced. The budget impact could be neutralised if the CGM sensor was discounted by 13.2% (£29.76 to £25.83).

Conclusions: CGM may result in increased spending in the NICE-eligible T2DM cohort but is expected to reduce demand on secondary care services and GP time. These findings may be of interest to local decision-makers who wish to resolve the COVID-19 backlog with transformational investment in primary care to reduce secondary care activity.

Background: To estimate the long-term cost-effectiveness of once-weekly semaglutide versus sitagliptin as an add-on therapy for type 2 diabetes patients inadequately controlled on metformin in China, to better inform healthcare decision making.

Methods: The Cardiff diabetes model which is a Monte Carlo micro-simulation model was used to project short-term effects of once-weekly semaglutide versus sitagliptin into long-term outcomes. Short-term data of patient profiles and treatment effects were derived from the 30-week SUSTAIN China trial, in which 868 type 2 diabetes patients with a mean age of 53.1 years inadequately controlled on metformin were randomized to receive once-weekly semaglutide 0.5 mg, once-weekly semaglutide 1 mg, or sitagliptin 100 mg. Costs and quality-adjusted life years (QALYs) were estimated from a healthcare system perspective at a discount rate of 5%. Univariate sensitivity analysis, scenario analysis, and probabilistic sensitivity analysis were conducted to test the uncertainty.

Results: Over patients' lifetime projections, patients in both once-weekly semaglutide 0.5 mg and 1 mg arms predicted less incidences of most vascular complications, mortality, and hypoglycemia, and lower total costs compared with those in sitagliptin arm. For an individual patient, compared with sitagliptin, once-weekly semaglutide 0.5 mg conferred a small QALY improvement of 0.08 and a lower cost of $5173, while once-weekly semaglutide 1 mg generated an incremental QALY benefit of 0.12 and a lower cost of $7142, as an add-on to metformin. Therefore, both doses of once-weekly semaglutide were considered dominant versus sitagliptin with more QALY benefits at lower costs.

Conclusion: Once-weekly semaglutide may represent a cost-effective add-on therapy alternative to sitagliptin for type 2 diabetes patients inadequately controlled on metformin in China.