The missing risks of climate change.

The risks of climate change are enormous, threatening the lives and livelihoods of millions to billions of people. The economic consequences of many of the complex risks associated with climate change cannot, however, currently be quantified. Here we argue that these unquantified, poorly understood and often deeply uncertain risks can and should be included in economic evaluations and decision-making processes. We present an overview of these unquantified risks and an ontology of them founded on the reasons behind their lack of robust evaluation. These consist of risks missing owing to delays in sharing knowledge and expertise across disciplines, spatial and temporal variations of climate impacts, feedbacks and interactions between risks, deep uncertainty in our knowledge, and currently unidentified risks. We highlight collaboration needs within and between the natural and social science communities to address these gaps. We also provide an approach for integrating assessments or speculations of these risks in a way that accounts for interdependencies, avoids double counting and makes assumptions clear. Multiple paths exist for engaging with these missing risks, with both model-based quantification and non-model-based qualitative assessments playing crucial roles. A wide range of climate impacts are understudied or challenging to quantify, and are missing from current evaluations of the climate risks to lives and livelihoods. Strong interdisciplinary collaboration and deeper engagement with uncertainty is needed to properly inform policymakers and the public about climate risks.

Enabling conditions for an equitable and sustainable blue economy.

The future of the global ocean economy is currently envisioned as advancing towards a 'blue economy'-socially equitable, environmentally sustainable and economically viable ocean industries1,2. However, tensions exist within sustainable development approaches, arising from differing perspectives framed around natural capital or social equity. Here we show that there are stark differences in outlook on the capacity for establishing a blue economy, and on its potential outcomes, when social conditions and governance capacity-not just resource availability-are considered, and we highlight limits to establishing multiple overlapping industries. This is reflected by an analysis using a fuzzy logic model to integrate indicators from multiple disciplines and to evaluate their current capacity to contribute to establishing equitable, sustainable and viable ocean sectors consistent with a blue economy approach. We find that the key differences in the capacity of regions to achieve a blue economy are not due to available natural resources, but include factors such as national stability, corruption and infrastructure, which can be improved through targeted investments and cross-scale cooperation. Knowledge gaps can be addressed by integrating historical natural and social science information on the drivers and outcomes of resource use and management, thus identifying equitable pathways to establishing or transforming ocean sectors1,3,4. Our results suggest that policymakers must engage researchers and stakeholders to promote evidence-based, collaborative planning that ensures that sectors are chosen carefully, that local benefits are prioritized, and that the blue economy delivers on its social, environmental and economic goals.

The economic case for scaling up health research and development: Lessons from the COVID-19 pandemic.

In response to the COVID-19 pandemic, governments directly funded vaccine research and development (R&D), quickly leading to multiple effective vaccines and resulting in enormous health and economic benefits to society. We develop a simple economic model showing this feat could potentially be repeated for other health challenges. Based on inputs from the economic and medical literatures, the model yields estimates of optimal R&D spending on treatments and vaccines for known diseases. Taking a global and societal perspective, we estimate the social benefits of such spending and a corresponding rate of return. Applications to Streptococcus A vaccines and Alzheimer's disease treatments demonstrate the potential of enhanced research and development funding to unlock massive global health and health-related benefits. We estimate that these benefits range from 2 to 60 trillion (2020 US$) and that the corresponding rates of return on R&D spending range from 12% to 23% per year for 30 y. We discuss the current shortfall in R&D spending and public policies that can move current funding closer to the optimal level.

Investing in nature can improve equity and economic returns.

Sustainable development requires jointly achieving economic development to raise standards of living and environmental sustainability to secure these gains for the long run. Here, we develop a local-to-global, and global-to-local, earth-economy model that integrates the Global Trade Analysis Project (GTAP)-computable general equilibrium model of the economy with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model of fine-scale, spatially explicit ecosystem services. The integrated model, GTAP-InVEST, jointly determines land use, environmental conditions, ecosystem services, market prices, supply and demand across economic sectors, trade across regions, and aggregate performance metrics like GDP. We use the integrated model to analyze the contribution of investing in nature for economic prosperity, accounting for the impact of four important ecosystem services (pollination, timber provision, marine fisheries, and carbon sequestration). We show that investments in nature result in large improvements relative to a business-as-usual path, accruing annual gains of $100 to $350 billion (2014 USD) with the largest percentage gains in the lowest-income countries. Our estimates include only a small subset of ecosystem services and could be far higher with inclusion of more ecosystem services, incorporation of ecological tipping points, and reduction in substitutability that limits economic adjustments to declines in natural capital. Our analysis highlights the need for improved environmental-economic modeling and the vital importance of integrating environmental information firmly into economic analysis and policy. The benefits of doing so are potentially very large, with the greatest percentage benefits accruing to inhabitants of the poorest countries.

Effectiveness and Cost-Effectiveness of Colorectal Cancer Screening With a Blood Test That Meets the Centers for Medicare & Medicaid Services Coverage Decision.

BACKGROUND & AIMS: A blood-based colorectal cancer (CRC) screening test may increase screening participation. However, blood tests may be less effective than current guideline-endorsed options. The Centers for Medicare & Medicaid Services (CMS) covers blood tests with sensitivity of at least 74% for detection of CRC and specificity of at least 90%. In this study, we investigate whether a blood test that meets these criteria is cost-effective. METHODS: Three microsimulation models for CRC (MISCAN-Colon, CRC-SPIN, and SimCRC) were used to estimate the effectiveness and cost-effectiveness of triennial blood-based screening (from ages 45 to 75 years) compared to no screening, annual fecal immunochemical testing (FIT), triennial stool DNA testing combined with an FIT assay, and colonoscopy screening every 10 years. The CMS coverage criteria were used as performance characteristics of the hypothetical blood test. We varied screening ages, test performance characteristics, and screening uptake in a sensitivity analysis. RESULTS: Without screening, the models predicted 77-88 CRC cases and 32-36 CRC deaths per 1000 individuals, costing $5.3-$5.8 million. Compared to no screening, blood-based screening was cost-effective, with an additional cost of $25,600-$43,700 per quality-adjusted life-year gained (QALYG). However, compared to FIT, triennial stool DNA testing combined with FIT, and colonoscopy, blood-based screening was not cost-effective, with both a decrease in QALYG and an increase in costs. FIT remained more effective (+5-24 QALYG) and less costly (-$3.2 to -$3.5 million) than blood-based screening even when uptake of blood-based screening was 20 percentage points higher than uptake of FIT. CONCLUSION: Even with higher screening uptake, triennial blood-based screening, with the CMS-specified minimum performance sensitivity of 74% and specificity of 90%, was not projected to be cost-effective compared with established strategies for colorectal cancer screening.

Epidemiological and health economic implications of symptom propagation in respiratory pathogens: A mathematical modelling investigation.

BACKGROUND: Respiratory pathogens inflict a substantial burden on public health and the economy. Although the severity of symptoms caused by these pathogens can vary from asymptomatic to fatal, the factors that determine symptom severity are not fully understood. Correlations in symptoms between infector-infectee pairs, for which evidence is accumulating, can generate large-scale clusters of severe infections that could be devastating to those most at risk, whilst also conceivably leading to chains of mild or asymptomatic infections that generate widespread immunity with minimal cost to public health. Although this effect could be harnessed to amplify the impact of interventions that reduce symptom severity, the mechanistic representation of symptom propagation within mathematical and health economic modelling of respiratory diseases is understudied. METHODS AND FINDINGS: We propose a novel framework for incorporating different levels of symptom propagation into models of infectious disease transmission via a single parameter, α. Varying α tunes the model from having no symptom propagation (α = 0, as typically assumed) to one where symptoms always propagate (α = 1). For parameters corresponding to three respiratory pathogens-seasonal influenza, pandemic influenza and SARS-CoV-2-we explored how symptom propagation impacted the relative epidemiological and health-economic performance of three interventions, conceptualised as vaccines with different actions: symptom-attenuating (labelled SA), infection-blocking (IB) and infection-blocking admitting only mild breakthrough infections (IB_MB). In the absence of interventions, with fixed underlying epidemiological parameters, stronger symptom propagation increased the proportion of cases that were severe. For SA and IB_MB, interventions were more effective at reducing prevalence (all infections and severe cases) for higher strengths of symptom propagation. For IB, symptom propagation had no impact on effectiveness, and for seasonal influenza this intervention type was more effective than SA at reducing severe infections for all strengths of symptom propagation. For pandemic influenza and SARS-CoV-2, at low intervention uptake, SA was more effective than IB for all levels of symptom propagation; for high uptake, SA only became more effective under strong symptom propagation. Health economic assessments found that, for SA-type interventions, the amount one could spend on control whilst maintaining a cost-effective intervention (termed threshold unit intervention cost) was very sensitive to the strength of symptom propagation. CONCLUSIONS: Overall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq, and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq, and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq, and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods, and it provides a framework for benchmarking further improvements of scRNA-seq protocols.

Costs and health effects of CT perfusion-based selection for endovascular thrombectomy within 6 hours of stroke onset: a model-based health economic evaluation.

BACKGROUND: Although CT perfusion (CTP) is often incorporated in acute stroke workflows, it remains largely unclear what the associated costs and health implications are in the long run of CTP-based patient selection for endovascular treatment (EVT) in patients presenting within 6 hours after symptom onset with a large vessel occlusion. METHODS: Patients with a large vessel occlusion were included from a Dutch nationwide cohort (n=703) if CTP imaging was performed before EVT within 6 hours after stroke onset. Simulated cost and health effects during 5 and 10 years follow-up were compared between CTP based patient selection for EVT and providing EVT to all patients. Outcome measures were the net monetary benefit at a willingness-to-pay of €80 000 per quality-adjusted life year, incremental cost-effectiveness ratio), difference in costs from a healthcare payer perspective (ΔCosts) and quality-adjusted life years (ΔQALY) per 1000 patients for 1000 model iterations as outcomes. RESULTS: Compared with treating all patients, CTP-based selection for EVT at the optimised ischaemic core volume (ICV≥110 mL) or core-penumbra mismatch ratio (MMR≤1.4) thresholds resulted in losses of health (median ΔQALYs for ICV≥110 mL: -3.3 (IQR: -5.9 to -1.1), for MMR≤1.4: 0.0 (IQR: -1.3 to 0.0)) with median ΔCosts for ICV≥110 mL of -€348 966 (IQR: -€712 406 to -€51 158) and for MMR≤1.4 of €266 513 (IQR: €229 403 to €380 110)) per 1000 patients. Sensitivity analyses did not yield any scenarios for CTP-based selection of patients for EVT that were cost-effective for improving health, including patients aged ≥80 years CONCLUSION: In EVT-eligible patients presenting within 6 hours after symptom onset, excluding patients based on CTP parameters was not cost-effective and could potentially harm patients.

A US payer perspective health economic model assessing value of monitoring disease activity to inform discontinuation and re-initiation of DMT in multiple sclerosis.

OBJECTIVES: We evaluate the potential clinical and cost impacts of discontinuing disease-modifying therapy (DMT) in people with multiple sclerosis (PwMS) when age-related immunosenescence can reduce DMT efficacy while increasing associated risks. METHODS: A Markov model simulated clinical and cost impacts to the patient and payers when a proportion of eligible patients with relapsing remitting multiple sclerosis (RRMS) discontinue DMT. Eligibility was defined as age >55 years, an RRMS diagnosis of >5 years, and no history of relapses for 5 years. Increasing the proportion of eligible patients willing to discontinue therapy was also modeled. Clinical and cost inputs were from published literature. RESULTS: Difference in EDSS progression between eligible patients who did and did not attempt discontinuation was not significant. After 1 year of eligibility, per-patient costs were $96k lower in the cohort that attempted discontinuation; however a higher proportion of relapses were seen in this group. When the proportion of patients willing to discontinue DMT increased, clinical findings remained consistent while the average cost per patient decreased. CONCLUSION: While there are increased clinical and cost benefits as more eligible patients attempt discontinuation, the risk of relapses can increase. Timely disease monitoring is required to manage safe DMT discontinuation.

Is the Comparator in Your Diagnostic Cost-Effectiveness Model "Standard of Care"? Recommendations from Literature Reviews and Expert Interviews on How to Identify and Operationalize It.

OBJECTIVES: This research aimed to develop best-practice recommendations for identifying the "standard of care" (SoC) and integrate it when it is the comparator in diagnostic economic models (SoC comparator). METHODS: A multi-methods approach comprising 2 pragmatic literature reviews and 9 expert interviews was used. Experts rated their agreement with draft recommendations based on the authors' analysis of the reviews. These were refined iteratively to produce final recommendations. RESULTS: Fourteen best-practice recommendations are provided. Care pathway mapping (using quantitative, qualitative, or mixed-methods approaches) should be used for identifying the SoC comparator. Guidelines analysis can be integrated with expert opinion to identify pathway variability and discrepancies from clinical practice. For integrating the SoC comparator into the model, recommendations around structure, input sourcing, data aggregation and reporting, input uncertainty, and model variability are presented. For example, modelers should consider that the reference standard is not synonymous with the SoC, and the SoC may not be the only comparator. The comparator limitations should be discussed with clinical experts, but elicitation of its diagnostic accuracy is not recommended. Probabilistic sensitivity analysis is recommended when evaluating the overall input uncertainty, and deterministic sensitivity analysis is useful when there is high model uncertainty or SoC variability. Consensus could not be reached for some topics (eg, the role of real-world data, model averaging, and alternative model structures), but the reported discussions provide points for consideration. CONCLUSIONS: To our knowledge, this is the first guidance to support modelers when identifying and operationalizing the SoC comparator in diagnostic cost-effectiveness models.

Challenges of Incorporating Life Cycle Drug Pricing in Cost-Effectiveness Models: A Review of Methods and Modeling Suggestions.

OBJECTIVES: This study aimed to conduct a review of existing methods used to incorporate life cycle drug pricing (LCDP) in cost-effectiveness analyses (CEAs), identify common methodological challenges, and suggest modeling approaches for prospectively implementing LCDP in CEA. METHODS: Two complementary searches were conducted in PubMed, combined with hand searching and reference mining, to identify English language full-text articles that explored (1) how drug prices change over time and (2) methods used to apply dynamic pricing in cost-effectiveness models (CEMs). Relevant articles were reviewed, and authors discussed the common methodological practices used in the literature and their associated challenges on prospectively implementing LCDP in CEMs. For each key challenge identified, we provide modeling suggestions to address the issue. RESULTS: We screened 1200 studies based on title and abstract; 117 were reviewed for eligibility, and 47 individual studies were included across both searches. Variations in prices over a product's life cycle are complex and multifactorial, and models applying LCDP in CEA varied in their methodology. We identified 4 key challenges to modeling LCDP in CEA, including how to model price trends before and after loss of exclusivity, how to capture the effect of price changes on future patient cohorts, and how to report results. CONCLUSION: Accurately quantifying the impact of LCDP requires careful consideration of multiple aspects pertaining to both the evolution of drug prices and how to reflect these in CEA. Although uncertainties remain, our findings can aid implementation and evaluation of LCDP in economic evaluations.

Methods for Including Adverse Events in Economic Evaluations: Suggestions for Improvement.

OBJECTIVE: Inclusion of relevant effectiveness and safety outcomes in economic evaluation of health technologies is required to aid efficient healthcare decisions. Our objective was to identify the key issues related to the inclusion of adverse events (AEs) in economic evaluation and explore perspectives for good practice recommendations to handle these issues. METHODS: We focused on the frequently encountered methodological issues related to the integration of AEs in economic evaluations of health technologies. We distinguished the following elements: the incorporation of AEs in decision models, the terminology of AEs, the estimation of AEs consequences in terms of quality of life (QoL) and costs, and the exploration of the uncertainty related to the impact of AEs on the economic results. RESULTS: We illustrated and discussed each of the identified issues by giving health technology assessment examples. We focused on the extent to which the integration of AEs in decision models can be improved by dealing with the lack of relevant real-world safety data, estimating the consequences of AEs (eg, for costs and QoL loss), exploring the impacts of AEs that are not adequately captured in current measurement of health-related QoL, and identifying the need for development of a good terminology of relevant types of AEs to be incorporated in economic evaluation. CONCLUSION: Based on a reflection the key methodological issues related to the incorporation of adverse drug events in economic evaluations, we suggested several recommendations to serve a starting point for health technology assessment agencies and researchers to develop good research practices in this field.

A Scoping Review and Taxonomy of Epidemiological-Macroeconomic Models of COVID-19.

OBJECTIVES: The COVID-19 pandemic placed significant strain on many health systems and economies. Mitigation policies decreased health impacts but had major macroeconomic impact. This article reviews models combining epidemiological and macroeconomic projections to enable policy makers to consider both macroeconomic and health objectives. METHODS: A scoping review of epidemiological-macroeconomic models of COVID-19 was conducted, covering preprints, working articles, and journal publications. We assessed model methodologies, scope, and application to empirical data. RESULTS: We found 80 articles modeling both the epidemiological and macroeconomic outcomes of COVID-19. Model scope is often limited to the impact of lockdown on health and total gross domestic product or aggregate consumption and to high-income countries. Just 14% of models assess disparities or poverty. Most models fall under 4 categories: compartmental-utility-maximization models, epidemiological models with stylized macroeconomic projections, epidemiological models linked to computable general equilibrium or input-output models, and epidemiological-economic agent-based models. We propose a taxonomy comparing these approaches to guide future model development. CONCLUSIONS: The epidemiological-macroeconomic models of COVID-19 identified have varying complexity and meet different modeling needs. Priorities for future modeling include increasing developing country applications, assessing disparities and poverty, and estimating of long-run impacts. This may require better integration between epidemiologists and economists.

Cost-Effectiveness of 2 Models of Pessary Care for Pelvic Organ Prolapse: Findings From the TOPSY Randomized Controlled Trial.

OBJECTIVES: Pelvic organ prolapse is the descent of one or more reproductive organs from their normal position, causing associated negative symptoms. One conservative treatment option is pessary management. This study aimed to to investigate the cost-effectiveness of pessary self-management (SM) when compared with clinic-based care (CBC). A decision analytic model was developed to extend the economic evaluation. METHODS: A randomized controlled trial with health economic evaluation. The SM group received a 30-minute SM teaching session, information leaflet, 2-week follow-up call, and a local helpline number. The CBC group received routine outpatient pessary appointments, determined by usual practice. The primary outcome for the cost-effectiveness analysis was incremental cost per quality-adjusted life year (QALY), 18 months post-randomization. Uncertainty was handled using nonparametric bootstrap analysis. In addition, a simple decision analytic model was developed using the trial data to extend the analysis over a 5-year period. RESULTS: There was no significant difference in the mean number of QALYs gained between SM and CBC (1.241 vs 1.221), but mean cost was lower for SM (£578 vs £728). The incremental net benefit estimated at a willingness to pay of £20 000 per QALY gained was £564, with an 80.8% probability of cost-effectiveness. The modeling results were consistent with the trial analysis: the incremental net benefit was estimated as £4221, and the probability of SM being cost-effective at 5 years was 69.7%. CONCLUSIONS: Results suggest that pessary SM is likely to be cost-effective. The decision analytic model suggests that this result is likely to persist over longer durations.

Flexible Approaches Based on Multistate Models and Microsimulation to Perform Real-World Cost-Effectiveness Analyses: An Application to Proprotein Convertase Subtilisin-Kexin Type 9 Inhibitors.

OBJECTIVES: This study aims to show the application of flexible statistical methods in real-world cost-effectiveness analyses applied in the cardiovascular field, focusing specifically on the use of proprotein convertase subtilisin-kexin type 9 inhibitors for hyperlipidemia. METHODS: The proposed method allowed us to use an electronic health database to emulate a target trial for cost-effectiveness analysis using multistate modeling and microsimulation. We formally established the study design and provided precise definitions of the causal measures of interest while also outlining the assumptions necessary for accurately estimating these measures using the available data. Additionally, we thoroughly considered goodness-of-fit assessments and sensitivity analyses of the decision model, which are crucial to capture the complexity of individuals' healthcare pathway and to enhance the validity of this type of health economic models. RESULTS: In the disease model, the Markov assumption was found to be inadequate, and a "time-reset" timescale was implemented together with the use of a time-dependent variable to incorporate past hospitalization history. Furthermore, the microsimulation decision model demonstrated a satisfying goodness of fit, as evidenced by the consistent results obtained in the short-term horizon compared with a nonmodel-based approach. Notably, proprotein convertase subtilisin-kexin type 9 inhibitors revealed their favorable cost-effectiveness only in the long-term follow-up, with a minimum willingness to pay of 39 000 Euro/life years gained. CONCLUSIONS: The approach demonstrated its significant utility in several ways. Unlike nonmodel-based or alternative model-based methods, it enabled to (1) investigate long-term cost-effectiveness comprehensively, (2) use an appropriate disease model that aligns with the specific problem under study, and (3) conduct subgroup-specific cost-effectiveness analyses to gain more targeted insights.

Anti-Vascular Endothelial Growth Factor Drugs Compared With Panretinal Photocoagulation for the Treatment of Proliferative Diabetic Retinopathy: A Cost-Effectiveness Analysis.

OBJECTIVES: This study aimed to evaluate the cost-effectiveness of anti-vascular endothelial growth factor drugs (anti-VEGFs) compared with panretinal photocoagulation (PRP) for treating proliferative diabetic retinopathy (PDR) in the United Kingdom. METHODS: A discrete event simulation model was developed, informed by individual participant data meta-analysis. The model captures treatment effects on best corrected visual acuity in both eyes, and the occurrence of diabetic macular edema and vitreous hemorrhage. The model also estimates the value of undertaking further research to resolve decision uncertainty. RESULTS: Anti-VEGFs are unlikely to generate clinically meaningful benefits over PRP. The model predicted anti-VEGFs be more costly and similarly effective as PRP, generating 0.029 fewer quality-adjusted life-years at an additional cost of £3688, with a net health benefit of -0.214 at a £20 000 willingness-to-pay threshold. Scenario analysis results suggest that only under very select conditions may anti-VEGFs offer potential for cost-effective treatment of PDR. The consequences of loss to follow-up were an important driver of model outcomes. CONCLUSIONS: Anti-VEGFs are unlikely to be a cost-effective treatment for early PDR compared with PRP. Anti-VEGFs are generally associated with higher costs and similar health outcomes across various scenarios. Although anti-VEGFs were associated with lower diabetic macular edema rates, the number of cases avoided is insufficient to offset the additional treatment costs. Key uncertainties relate to the long-term comparative effectiveness of anti-VEGFs, particularly considering the real-world rates and consequences of treatment nonadherence. Further research on long-term visual acuity and rates of vision-threatening complications may be beneficial in resolving uncertainties.

Key considerations for modelling the long-term costs and benefits of treatments for ANCA-associated vasculitis.

OBJECTIVES: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a group of severe and chronic autoimmune diseases. Patients undergo two treatment phases: inducing remission and maintaining remission to prevent organ damage. Immunosuppressants, including glucocorticoids (GCs) are used as first-line treatment, but long-term GC use is associated with toxic effects. Novel treatments reduce or replace the need for long-term GC, and therefore can reduce GC-related toxicity. The evolving treatment landscape has presented new challenges for health technology assessment (HTA) of new treatments in AAV and long-term modelling of costs and outcomes in this disease. METHODS: Using the appraisal of avacopan in England (NICE) as a case study, this paper aims to identify the key challenges involved in the economic evaluation of new treatments for AAV, with a particular focus on the long-term modelling of the treatment costs and benefits for the purpose of HTA. The outcome of this study is a set of recommendations for modelling the cost-effectiveness of new treatments for AAV from the HTA perspective. RESULTS: The discussion focuses on the appropriate model structure, approach to modelling end-stage renal disease (ESRD) as a key determinant of costeffectiveness, capturing the impact of GC-related adverse events, and estimation of short and long-term costs of AAV. CONCLUSIONS: Economic evaluation of new treatments for AAV needs to capture all relevant downstream effects. ESRD is a key driver of cost-effectiveness but is associated with major uncertainty. Future observational studies need to offer sufficient detail to allow for differentiation in event rates across treatment options.

A Cost and Waste-Savings Comparison Between Single-Use and Reusable Pulse Oximetry Sensors Across US Operating Rooms.

BACKGROUND: Operating room (OR) expenditures and waste generation are a priority, with several professional societies recommending the use of reprocessed or reusable equipment where feasible. The aim of this analysis was to compare single-use pulse oximetry sensor stickers ("single-use stickers") versus reusable pulse oximetry sensor clips ("reusable clips") in terms of annual cost savings and waste generation across all ORs nationally. METHODS: This study did not involve patient data or research on human subjects. As such, it did not meet the requirements for institutional review board approval. An economic model was used to compare the relative costs and waste generation from using single-use stickers versus reusable clips. This model took into account: (1) the relative prices of single-use stickers and reusable clips, (2) the number of surgeries and ORs nationwide, (3) the workload burden of cleaning the reusable clips, and (4) the costs of capital for single-use stickers and reusable clips. In addition, we also estimated differences in waste production based on the raw weight plus unit packaging of single-use stickers and reusable clips that would be disposed of over the course of the year, without any recycling interventions. Estimated savings were rounded to the nearest $0.1 million. RESULTS: The national net annual savings of transitioning from single-use stickers to reusable clips in all ORs ranged from $510.5 million (conservative state) to $519.3 million (favorable state). Variability in savings estimates is driven by scenario planning for replacement rate of reusable clips, workload burden of cleaning (ranging from an additional expense of $618k versus a cost savings of $309k), and cost of capital-interest gained on investment of capital that is freed up by the monetary savings of a transition to reusable clips contributes between $541k (low-interest rates of 2.85%) and $1.3 million (high-interest rates of 7.08%). The annual waste that could be diverted from landfill by transitioning to reusable clips was found to be between 587 tons (conservative state) up to 589 tons (favorable state). If institutions need to purchase new vendor monitors or cables to make the transition, that may increase the 1-time capital disbursement. CONCLUSIONS: Using reusable clips versus single-use stickers across all ORs nationally would result in appreciable annual cost savings and waste generation reduction impact. As both single-use stickers and reusable clips are equally accurate and reliable, this cost and waste savings could be instituted without a compromise in clinical care.

Public health events and economic growth in a neoclassical framework.

Public health events (PHEs) have emerged as significant threats to human life, health, and economic growth. PHEs, such as COVID-19, have prompted a reevaluation for enhanced regular prevention and control (RPC). In this study, we focus on the core concept of prevention and control intensity (PCI), and establish a neoclassical economic growth model from the long-term and macro perspective to balance life protection and economic growth. The model construct the mechanism of PCI on economic growth through population dynamics and capital accumulation under the backdrop of RPC for PHEs. We find the conditions for PCI when the economy achieves steady state, and provides an algorithm establishing the optimal strategy that maximises per capita disposable income based on the optimal PCI and consumption. Simulation result quantifies an inverted U-shaped relationship between PCI and capital per capita, output per capita and consumption per capita in the steady state. The model suggests that, given the PHEs of inducing potential unemployment shock, it is worthwhile to combine the implementation of moderate PCI with coordinated policies of income distribution.

Impact of an innovative bundled payment to TB health care providers in China: an economic simulation analysis.

BACKGROUND: Tuberculosis is the second most deadly infectious disease after COVID-19 and the 13th leading cause of death worldwide. Among the 30 countries with a high burden of TB, China ranks third in the estimated number of TB cases. China is in the top four of 75 countries with a deficit in funding for TB strategic plans. To reduce costs and improve the effectiveness of TB treatment in China, the NHSA developed an innovative BP method. This study aimed to simulate the effects of this payment approach on different stakeholders, reduce the economic burden on TB patients, improve the quality of medical services, facilitate policy optimization, and offer a model for health care payment reforms that can be referenced by other regions throughout the world. METHODS: We developed a simulation model based on a decision tree analysis to project the expected effects of the payment method on the potential financial impacts on different stakeholders. Our analysis mainly focused on comparing changes in health care costs before and after receiving BPs for TB patients with Medicare in the pilot areas. The data that were used for the analysis included the TB service claim records for 2019-2021 from the health insurance agency, TB prevalence data from the local Centre for Disease Control, and health care facilities' revenue and expenditure data from the Statistic Yearbook. A Monte Carlo randomized simulation model was used to estimate the results. RESULTS: After adopting the innovative BP method, for each TB patient per year, the total annual expenditure was estimated to decrease from $2,523.28 to $2,088.89, which is a reduction of $434.39 (17.22%). The TB patient out-of-pocket expenditure was expected to decrease from $1,249.02 to $1,034.00, which is a reduction of $215.02 (17.22%). The health care provider's revenue decreased from $2,523.28 to $2,308.26, but the health care provider/institution's revenue-expenditure ratio increased from -6.09% to 9.50%. CONCLUSIONS: This study highlights the potential of BPs to improve medical outcomes and control the costs associated with TB treatment. It demonstrates its feasibility and advantages in enhancing the coordination and sustainability of medical services, thus offering valuable insights for global health care payment reform.