Cost Effectiveness and Resource Allocation最新文献

Background: According to the Chinese guidelines for lipid management (2023), evolocumab in combination with statins was recommended as secondary prevention of cardiovascular disease. However, because of the variation in the price of evolocumab and its different methods of confirming clinical efficacy, it was necessary to explore its economics and the impact of different methods of confirming efficacy on its economic studies.

Objective: The purpose of this paper was to assess the cost-effectiveness of evolocumab with statins versus statins alone for patients with acute myocardial infarction(AMI) in China and to investigate the impact of different clinical effectiveness modeling approaches on economic outcomes.

Methods: A Markov cohort state-transition model was used to estimate the incremental cost-effectiveness ratio (ICER) based on Chinese observational data on cardiovascular event rates, efficacy from the Asian subgroup of the FOURIER trial, cost and utility from the Chinese Yearbook of Health Statistics, health insurance data, and published studies conducted in China. This study conducted subgroup analyses for different populations and dosing regimens; sensitivity analyses for parameters such as cost, utility, and cardiovascular event rates; and scenario analyses on hospital hierarchy, time horizon, starting age, and price for statins.

Results: ICERs ranged from 27423 to 214777 Chinese yuan(CNY) per QALY gained, all below the willingness-to-pay threshold of CNY 257094. Only when the time horizon became small, the ICERs were greater than the willingness-to-pay. The probabilities that adding evolocumab to statins was cost-effective ranged from 76 to 98%. When the time horizon became small, i.e. evolocumab was discontinued before the age of 75 (after conversion), the corresponding ICERs were almost always greater than the willingness-to-pay. ICERs for modelling approaches based on clinical endpoints were 1.34 to 1.95 times higher than ICERs for modelling approaches based on reduced LDL-C levels.

Conclusions: From the Chinese healthcare and private payer perspectives, adding evolocumab to statin therapy in AMI patients is more likely to be a cost-effective treatment option at the current list price of CNY 283.8. However, evolocumab may not be cost-effective if used for shorter periods of time. The results based on different clinical effectiveness modeling approaches were significantly different.

Background: Triple-negative breast cancer (TNBC) is an aggressive and therapy-resistant form of breast cancer with a significant economic burden on patients and healthcare systems. Therefore, we completed a systematic review to classify and synthesize the literature on the direct and indirect costs of TNBC.

Methods: Databases including ISI Web of Science, Scopus, PubMed, and Google Scholar were searched for all related articles assessing the economic burden of TNBC from 2010 until December 2022. The quality and eligibility assessments were done accordingly. We adjusted all costs to January 2023 $US.

Results: From 881 records, 15 studies were eligible. We found that studies are widely disparate in the timetable, study design, patient populations, and cost components assessed. The annual per-patient direct costs of metastatic TNBC (mTNBC) were about $24,288 to $316,800. For early TNCB patients (eTNBC) this was about $21,120 to $105,600. Cancer management anticancer therapy costs account for the majority of direct costs. Along with an increase in cancer stage and line of therapy, healthcare costs were increased. Moreover, the indirect costs of patients with mTNBC and eTNBC were about $1060.875 and about $186,535 for each patient respectively.

Conclusion: The results showed that the direct and indirect costs of TNBC, mainly those of mTNBC, were substantial, suggesting attention to medical progress in cancer prognosis and therapy approaches.

Objective: The aim of this article is to evaluate the cost-effectiveness of abemaciclib plus endocrine therapy (ABE + ET) vs. ET as adjuvant treatment for high-risk hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+/HER2-) early breast cancer in China.

Methods: From the perspective of the Chinese health care system, a 5-state Markov model was developed with a lifetime horizon. Data of the monarchE phase III clinical trial were used to model the invasive disease-free survival (iDFS) and standard parameters models were used for data extrapolation. Costs were obtained from national data sources, expert opinions and published literature using 2023 US dollars and discounted by 5%. The results were evaluated in terms of life-years (LYs) and quality-adjusted life-years (QALYs). Sensitivity analyses and scenario analyses were performed to test the robustness of the basic results.

Results: In the base-case analysis result, the model projected improved outcomes (by 0.65 LYs and 0.72 QALYs) and increased costs (by $16,057.72) for incremental cost-effectiveness ratios (ICERs) of $24,841/LY and $22,385/QALY for ABE + ET vs. ET patients. The results in scenario analysis estimated the ICERs of ABE + ET treatment to be $16,959/LY and $15,264/QALY in a mixture cure model, and $13,560/LY and $12,191/QALY in a non-mixture cure model. The model was sensitive to outcome discount rate and utility of iDFS.

Conclusion: ABE + ET might not have an economic advantage over ET at a willingness-to-pay (WTP) threshold of one time the per capita GDP in China, but was expected to be more cost-effective at a WTP threshold of three times the per capita GDP. Further analysis will be conducted once data from longer-term studies become available.

Background: Sixteen of the 30 countries with a high tuberculosis (TB) burden are in Sub-Saharan Africa (SSA). Over 25% of TB deaths occur in the Africa region. This study aims to estimate the productivity changes of TB programs in 16 SSA countries where TB is endemic.

Methods: We used Hicks-Moorsteen index to compute and decompose Total factor productivity (TFP), and the β-convergence and σ-convergence tests to check for convergence patterns among SSA countries.

Results: We found that technological change has been the main driver of the TFP growth, and that increasing technical efficiency may be the first objective in efforts to improve TFP of TB programs. Moreover, the convergence tests reveal significant homogeneity in terms of TFP change between SSA countries studied.

Conclusion: The findings suggest that improving technical efficiency of TB programs mainly calls for better resource allocation, capacity building in governance and management of programs, improved training of the health providers and stronger prevention policies. Policymakers must design models for integration of TB treatment under the universal health insurance schemes.

Introduction: This study investigates Iranian men's willingness to pay (WTP) for prostate cancer (PCa) screening and influencing factor, along with the impact of information.

Method: We assessed preferences for prostate cancer screening in 771 Iranian men aged 40 and above using an internet-based questionnaire survey. Participants received basic and complementary information, and their willingness to pay was determined through a payment card approach. A Wilcoxon test assessed the impact of information. We also analyzed prostate cancer screening demand and employed Heckman's two-step model to evaluate factors influencing the willingness to pay. Additionally, reasons for unwillingness to pay were explored.

Results: Willingness to pay significantly decreased with complementary information relative to basic information (16.3$ vs 17.8$). Heckman model, using WTP based on basic information shows age, education, and monthly household expenditure positively influenced the decision to pay. In contrast, health status, expectations of remaining life and prostate problems history positively affect amount of WTP for PCa screening, and insurance coverage has a negative impact on it. Majority of respondents (91%) supported PCa screening, with 82% expressing a willingness to pay. Common reasons for not paying include seeing screening as a public good (43%), financial constraints (35%), and having insurance (20%). The screening demand is price-sensitive.

Conclusion: The basic mindset of Iranian men exaggerates the risk of prostate cancer. Reduced willingness to pay after receiving information reassures the reliability of their financial expectation. Taking into account the factors that influence PCa screening is essential for accurate planning and the successful implementation of this program.

Objective: To investigate the cost-effectiveness of using Implant Movement Analysis (IMA) to follow up suspected aseptic loosening when the diagnosis after an initial X-ray is not conclusive, compared with a diagnostic pathway with X-ray follow-up.

Methods: A health-economic model in the form of a decision tree was developed using quality-adjusted life years (QALY) from the literature, cost-per-patient data from a university hospital and the probabilities of different events from expert physicians' opinions. The base case incremental cost-effectiveness ratio (ICER) was compared with established willingness-to-pay thresholds and sensitivity analyses were performed to account for assumptions and uncertainty.

Results: The base case ICER indicated that the IMA pathway was cost effective (SEK 99,681, compared with the SEK 500,000 threshold). In the sensitivity analysis, the IMA pathway remained cost effective during most changes in parameters. ICERs above the threshold value occurred in cases where a larger or smaller proportion of people receive immediate surgery.

Conclusion: A diagnostic pathway using IMA after an inconclusive X-ray for suspected aseptic loosening was cost effective compared with a pathway with X-ray follow-up.

Background: Demonstrating safety and efficacy of new medical treatments requires clinical trials but clinical trials are costly and may not provide value proportionate to their costs. As most health systems have limited resources, it is therefore important to identify the trials with the highest value. Tools exist to assess elements of a clinical trial such as statistical validity but are not wholistic in their valuation of a clinical trial. This study aims to develop a measure of clinical trials value and provide an online tool for clinical trial prioritisation.

Methods: A search of the academic and grey literature and stakeholder consultation was undertaken to identify a set of criteria to aid clinical trial valuation using multi-criteria decision analysis. Swing weighting and ranking exercises were used to calculate appropriate weights of each of the included criteria and to estimate the partial-value function for each underlying metric. The set of criteria and their respective weights were applied to the results of six different clinical trials to calculate their value.

Results: Seven criteria were identified: 'unmet need', 'size of target population', 'eligible participants can access the trial', 'patient outcomes', 'total trial cost', 'academic impact' and 'use of trial results'. The survey had 80 complete sets of responses (51% response rate). A trial designed to address an 'Unmet Need' was most commonly ranked as the most important with a weight of 24.4%, followed by trials demonstrating improved 'Patient Outcomes' with a weight of 21.2%. The value calculated for each trial allowed for their clear delineation and thus a final value ranking for each of the six trials.

Conclusion: We confirmed that the use of the decision tool for valuing clinical trials is feasible and that the results are face valid based on the evaluation of six trials. A proof-of-concept applying this tool to a larger set of trials with an external validation is currently underway.

Background: Breast cancer represents the most prevalent cancer among Swedish women. Although considerable research has investigated the cost-effectiveness of emerging innovative medical treatments for breast cancer, studies addressing existing surgical procedures remain scant. Therefore, this study aimed to evaluate the cost-effectiveness of three surgical procedures for in situ breast cancer treatment in Sweden: mastectomy, lumpectomy without irradiation, and lumpectomy with irradiation.

Methods: A six-state Markov model with a 30-year time horizon was used to compare the cost-effectiveness of the three alternatives. Transition probabilities were based on a targeted literature review focusing on available evidence in Sweden and comparable contexts. Costs were estimated from both healthcare and societal perspectives, using patient data from the Swedish National Cancer Registry in 2020 (Cancerregistret). Health outcomes were quantified in terms of quality-adjusted life years (QALYs). Cost and health outcomes were then summarised into an incremental cost-effectiveness ratio (ICER) between competing strategies. A probabilistic sensitivity analysis (PSA) was conducted to address the uncertainties in the input parameters.

Results: The results showed that compared to lumpectomy without irradiation, lumpectomy with irradiation yielded a "moderate" ICER per QALY gained of 402,994 Swedish Krona (SEK) from a healthcare perspective and a "high" ICER of 575,833 SEK from a societal perspective. Mastectomy proved to be the costliest and least effective of the three alternatives over a 30-year period. The PSA results further substantiated these findings.

Conclusions: Our study demonstrated that lumpectomy with irradiation is "moderately" cost-effective compared with lumpectomy without irradiation. Nevertheless, extending this study by conducting a comprehensive budget impact analysis to account for the prevalence of in situ breast cancer in Sweden is prudent. These results imply that a costlier and less effective mastectomy should only be considered when lumpectomy options are infeasible. Further studies are needed to obtain more reliable parameters relevant to Sweden and to increase the consistency of the findings.

Background: Management of COVID-19 patients with mild and moderate symptoms could be isolated at home isolation (HI), community isolation (CI) or hospitel. However, it was still unclear which strategy was more cost-effective. Therefore, this study was conducted to evaluate this.

Methods: This study used data from patients who initially stayed at HI, CI, and hospitel under supervision of Ramathibodi Hospital between April and October 2021. Outcomes of interest were hospitalisation and mortality. An incremental cost-effectiveness ratios (ICER) was calculated based on hospital perspective using home isolation as the reference.

Results: From 7,077 patients, 4,349 2,356, and 372 were admitted at hospitel, HI, and CI, respectively. Most patients were females (57.04%) and the mean age was 40.42 (SD = 16.15). Average durations of stay were 4.47, 3.35, and 3.91 days for HI, CI, and hospitel, respectively. The average cost per day for staying in these corresponding places were 24.22, 63.69, and 65.23 US$. For hospitalisation, the ICER for hospitel was at 41.93 US$ to avoid one hospitalisation in 1,000 patients when compared to HI, while CI had more cost, but less cases avoided. The ICER for hospitel and CI were at 46.21 and 866.17 US$ to avoid one death in 1,000 patients.

Conclusions: HI may be cost-effective isolated strategy for preventing hospitalisation and death in developing countries with limited resources.

Introduction: Artificial Intelligence (AI) represents a significant advancement in technology, and it is crucial for policymakers to incorporate AI thinking into policies and to fully explore, analyze and utilize massive data and conduct AI-related policies. AI has the potential to optimize healthcare financing systems. This study provides an overview of the AI application domains in healthcare financing.

Method: We conducted a scoping review in six steps: formulating research questions, identifying relevant studies by conducting a comprehensive literature search using appropriate keywords, screening titles and abstracts for relevance, reviewing full texts of relevant articles, charting extracted data, and compiling and summarizing findings. Specifically, the research question sought to identify the applications of artificial intelligence in health financing supported by the published literature and explore potential future applications. PubMed, Scopus, and Web of Science databases were searched between 2000 and 2023.

Results: We discovered that AI has a significant impact on various aspects of health financing, such as governance, revenue raising, pooling, and strategic purchasing. We provide evidence-based recommendations for establishing and improving the health financing system based on AI.

Conclusions: To ensure that vulnerable groups face minimum challenges and benefit from improved health financing, we urge national and international institutions worldwide to use and adopt AI tools and applications.