Cost effectiveness of contraceptives in the United States

BACKGROUND

The study was conducted to estimate the relative cost effectiveness of contraceptives in the United States from a payer's perspective.

METHODS

A Markov model was constructed to simulate costs for 16 contraceptive methods and no method over a 5-year period. Failure rates, adverse event rates and resource utilization were derived from the literature. Sensitivity analyses were performed on costs and failure rates.

RESULTS

Any contraceptive method is superior to "no method". The three least expensive methods were the copper-T intrauterine device (IUD) (US$647), vasectomy (US$713) and levonorgestrel (LNG)-20 intrauterine system (IUS) (US$930). Results were sensitive to the cost of contraceptive methods, the cost of an unintended pregnancy and plan disenrollment rates.

CONCLUSION

The copper-T IUD, vasectomy and the LNG-20 IUS are the most cost-effective contraceptive methods available in the United States. Differences in method costs, the cost of an unintended pregnancy and time horizon are influential factors that determine the overall value of a contraceptive method.

The Economic Case for the Prevention of Mental Illness

Poor mental health has profound economic consequences. Given the burden of poor mental health, the economic case for preventing mental illness and promoting better mental health may be very strong, but too often prevention attracts little attention and few resources. This article describes the potential role that can be played by economic evidence alongside experimental trials and observational studies, or through modeling, to substantiate the need for increased investment in prevention. It illustrates areas of action across the life course where there is already a good economic case. It also suggests some further areas of substantive public health concern, with promising effectiveness evidence, that may benefit from economic analysis. Financial and economic barriers to implementation are then presented, and strategies to address the barriers and increase investment in the prevention of mental illness are suggested.

Optimizing the control of disease infestations at the landscape scale

Using a contact-process model for the spread of crop disease over a regional scale, we examine the importance of the time scale for control with respect to the cost of the epidemic. The costs include the direct cost of treating infected sites as well as the indirect costs incurred through lost yield. We first use a mean-field approximation to derive analytical results for the optimal treatment regimes that minimize the total cost of the epidemic. We distinguish short- and long-term epidemics. and show that seasonal control (short time scale) requires extreme treatment, either treating all sites or none or switching between the two at some stage during the season. The optimal long-term strategy requires an intermediate level of control that results in near eradication of the disease. We also demonstrate the importance of incorporating economic constraints by deriving a critical relationship between the epidemiological and economic parameters that determine the qualitative nature of the optimal treatment strategy. The set of optimal strategies is summarized in a policy plot, which can be used to determine the nature of the optimal treatment regime given prior knowledge of the epidemiological and economic parameters. Finally, we test the robustness of the analytical results, derived from the mean-field approximation, on the spatially explicit contact process and demonstrate robustness to implementation errors and misestimation of crucial parameters.

Cost-effectiveness of a Nutrition Education Curriculum Intervention in Elementary Schools

OBJECTIVE

To estimate the long-term cost-effectiveness of an obesity prevention nutrition education curriculum (Food, Health, & Choices) as delivered to all New York City fifth-grade public school students over 1 year.

METHODS

This study is a standard cost-effectiveness analysis from a societal perspective, with a 3% discount rate and a no-intervention comparator, as recommended by the US Panel on Cost-effectiveness in Health and Medicine. Costs of implementation, administration, and future obesity-related medical costs were included. Effectiveness was based on a cluster-randomized, controlled trial in 20 public schools during the 2012-2013 school year and linked to published estimates of childhood-to-adulthood body mass index trajectories using a decision analytic model.

RESULTS

The Food, Health, & Choices intervention was estimated to cost $8,537,900 and result in 289 fewer males and 350 fewer females becoming obese (0.8% of New York City fifth-grade public school students), saving 1,599 quality-adjusted life-years (QALYs) and $8,098,600 in direct medical costs. Food, Health, & Choices is predicted to be cost-effective at $275/QALY (95% confidence interval, -$2,576/QALY to $2,084/QALY) with estimates up to $6,029/QALY in sensitivity analyses.

CONCLUSIONS AND IMPLICATIONS

This cost-effectiveness model suggests that a nutrition education curriculum in public schools is effective and cost-effective in reducing childhood obesity, consistent with the authors' hypothesis and previous literature. Future research should assess the feasibility and sustainability of scale-up.

Public health impact of the Pfizer-BioNTech COVID-19 vaccine (BNT162b2) in the first year of rollout in the United States

BACKGROUND

As the body of evidence on COVID-19 and post-vaccination outcomes continues to expand, this analysis sought to evaluate the public health impact of the Pfizer-BioNTech COVID-19 Vaccine, BNT162b2, during the first year of its rollout in the US.

METHODS

A combined Markov decision tree model compared clinical and economic outcomes of the Pfizer-BioNTech COVID-19 Vaccine (BNT162b2) versus no vaccination in individuals aged ≥12 years. Age-stratified epidemiological, clinical, economic, and humanistic parameters were derived from existing data and published literature. Scenario analysis explored the impact of using lower and upper bounds of parameters on the results. The health benefits were estimated as the number of COVID-19 symptomatic cases, hospitalizations and deaths averted, and Quality Adjusted Life Years (QALYs) saved. The economic benefits were estimated as the amount of healthcare and societal cost savings associated with the vaccine-preventable health outcomes.

RESULTS

It was estimated that, in 2021, the Pfizer-BioNTech COVID-19 Vaccine (BNT162b2) contributed to averting almost 9 million symptomatic cases, close to 700,000 hospitalizations, and over 110,000 deaths, resulting in an estimated $30.4 billion direct healthcare cost savings, $43.7 billion indirect cost savings related to productivity loss, as well as discounted gains of 1.1 million QALYs. Scenario analyses showed that these results were robust; the use of alternative plausible ranges of parameters did not change the interpretation of the findings.

CONCLUSIONS

The Pfizer-BioNTech COVID-19 Vaccine (BNT162b2) contributed to generate substantial public health impact and vaccine-preventable cost savings in the first year of its rollout in the US. The vaccine was estimated to prevent millions of COVID-19 symptomatic cases and thousands of hospitalizations and deaths, and these averted outcomes translated into cost-savings in the billions of US dollars and thousands of QALYs saved. As only direct impacts of vaccination were considered, these estimates may be conservative.

Development of a Conceptual Model of Disease Progression for Use in Economic Modeling of Chronic Obstructive Pulmonary Disease

BACKGROUND

To develop and validate a new conceptual model (CM) of chronic obstructive pulmonary disease (COPD) for use in disease progression and economic modeling. The CM identifies and describes qualitative associations between disease attributes, progression and outcomes.

METHODS

A literature review was performed to identify any published CMs or literature reporting the impact and association of COPD disease attributes with outcomes. After critical analysis of the literature, a Steering Group of experts from the disciplines of health economics, epidemiology and clinical medicine was convened to develop a draft CM, which was refined using a Delphi process. The refined CM was validated by testing for associations between attributes using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE).

RESULTS

Disease progression attributes included in the final CM were history and occurrence of exacerbations, lung function, exercise capacity, signs and symptoms (cough, sputum, dyspnea), cardiovascular disease comorbidities, 'other' comorbidities (including depression), body composition (body mass index), fibrinogen as a biomarker, smoking and demographic characteristics (age, gender). Mortality and health-related quality of life were determined to be the most relevant final outcome measures for this model, intended to be the foundation of an economic model of COPD.

CONCLUSION

The CM is being used as the foundation for developing a new COPD model of disease progression and to provide a framework for the analysis of patient-level data. The CM is available as a reference for the implementation of further disease progression and economic models.

A US cost-minimization model comparing ravulizumab versus eculizumab for the treatment of atypical hemolytic uremic syndrome

AIMS

Ravulizumab, engineered from eculizumab, provides sustained C5 inhibition in atypical hemolytic uremic syndrome (aHUS) while reducing dosing frequency (every 8 vs 2 weeks, respectively). Treatment choice often carries significant financial implications. This study compared the economic consequences of ravulizumab and eculizumab for treating aHUS.

MATERIALS AND METHODS

A cost-minimization model compared direct medical costs for ravulizumab and eculizumab in treating aHUS, assuming equivalent efficacy and safety, and took a US payer perspective, a lifetime horizon, and a 3.0% cost discount rate. The base case modeled adult and pediatric treatment-naïve populations, with characteristics based on clinical trials, and treatment patterns (duration, discontinuation, re-initiation) derived from eculizumab studies with long-term follow-up. Treatment costs (2019 US$) were based on wholesale drug acquisition costs, Centers for Medicare & Medicaid fee schedules, and published disease management studies. Sensitivity analyses were conducted by adjusting relevant variables.

RESULTS

Ravulizumab provided lifetime per-patient cost reductions (discounted) of 32.4% and 35.5% vs eculizumab in adult and pediatric base cases, respectively. Total costs for ravulizumab vs eculizumab were $12,148,748 and $17,979,007, respectively, for adults, and $11,587,832 and $17,959,814, respectively, for children. Pre-discontinuation treatment contributed the largest proportion of total costs for ravulizumab (94.8% and 88.0%) and eculizumab (94.8% and 87.8%) in adults and children, respectively. Across sensitivity analyses, ravulizumab provided cost reductions vs eculizumab.

LIMITATIONS

The model included several typical assumptions. Base case patients with more severe stages of chronic kidney disease were assumed not to discontinue treatment, nor to experience an excess mortality risk in either treatment arm, which may not reflect real-world clinical observations. Additionally, rebates and discounts on medication acquisition or administration were not considered.

CONCLUSIONS

In US patients with aHUS, ravulizumab provided cost reductions of 32.4-35.5% vs eculizumab, with a reduced dosing frequency for ravulizumab. The magnitude of reductions was consistent across sensitivity analyses.

An economic evaluation of management strategies to mitigate the negative effect of twinning in dairy herds

Our objectives were to develop an economic model to estimate the economic impact of twinning in dairy cows and to evaluate management strategies to mitigate the negative economic impact of twinning in dairy herds. A probabilistic tree considering spontaneous embryo reduction, early pregnancy loss, abortion, metritis, retained placenta, and culling rate at 120 d of the second, at the end of the second, and at the end of the third lactation was developed for a single pregnancy; we also developed 3 management options upon diagnosis of a twin pregnancy: (1) do nothing, (2) induce abortion using PGF_2α, or (3) attempt manual embryo reduction. A value was given to each branch of the tree by simulating cow states on a farm for 1,400 d to encompass 4 consecutive lactations. The incomes considered in the simulations included milk income over feed cost, income from calves, and slaughter value upon culling. The expenses taken into account depending on each branch included additional inseminations and synchronization protocols, embryo reduction, induction of abortion, replacement heifers, and costs due to metritis and retained placenta. The gross value for a singleton pregnancy and the 3 management options upon diagnosis of a twin pregnancy were calculated by adding the value of all braches multiplied by their probability. The costs for the 3 management options were calculated by subtracting its gross value minus the gross value of a singleton pregnancy. The negative economic impact of a twin pregnancy ranged from $97 to $225 depending on the type of twin pregnancy (unilateral vs. bilateral), parity, and DIM when the twin pregnancy occurred. The overall negative economic impact of twinning on dairy farm profitability in the United States was estimated to be $96 million per year. Attempting manual embryo reduction early during gestation upon diagnosis of a twin pregnancy was the optimal management strategy for mitigating the negative economic impact of twinning under a wide variety of scenarios.

Health-Related Quality of Life in People Living with Psychotic Illness and Factors Associated with Its Variation

OBJECTIVES

To establish whether the four-dimensional Assessment of Quality of Life (AQoL-4D) produces robust utility values in adults with psychotic illness, and identify health inequalities compared with the general population.

METHODS

The AQoL-4D was completed by 1613 individuals with an International Classification of Diseases, Tenth Revision, psychotic illness in the 2010 Australian National Survey of Psychosis. Utilities were assessed for this sample and 20 subgroups, and were compared with general population norms. Modified Cohen d was used as an index of effect size. Utilities were collapsed into 10 health-related quality-of-life (HRQOL) bands or decades.

RESULTS

HRQOL in people with psychotic illness was half of the maximum achievable utility (half-"full health") with a mean utility of 0.49 (95% confidence interval [CI] 0.48-0.51), and showing substantial variability across subgroups. Participants with essentially normal functioning had the highest mean utility (0.72; 95% CI 0.68-0.77), and those with very poor perceived mental health had the lowest (0.22; 95% CI 0.18-0.26). These subgroups showed the most variability. Negative symptoms also gave rise to substantial variation. Among diagnostic categories, only depressive psychosis had a large effect relative to delusional disorders. The distribution of utilities in people with psychotic illness differed markedly from that in the general population, with 6.8% versus 47.2% having values in the highest decade (>0.90-1.00). Utilities were lower in every age group in people with psychosis.

CONCLUSIONS

Profound HRQOL impacts are revealed by the AQoL-4D in people with psychotic illness, and marked variations in utilities were observed for key subjective and objective measures. We provide a suite of utility values for economic modeling studies and recommend the AQoL-4D for assessing HRQOL in people with psychotic illness.

Guidance on the use of complex systems models for economic evaluations of public health interventions

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Cost-effectiveness of telaprevir in patients with genotype 1 hepatitis C in Australia

BACKGROUND

Protease inhibitors such as telaprevir (Incivo) are reimbursed in Australia for the treatment of patients with genotype 1 hepatitis C virus (HCV) infection in combination with pegylated interferon and ribavirin (PR).

OBJECTIVES

To assess the cost-effectiveness of telaprevir plus PR compared with PR alone in 1) previously untreated patients and 2) patients who had received treatment with PR earlier.

METHODS

Sustained virological response rates and average treatment durations of telaprevir and PR (given with or without telaprevir) were taken from the telaprevir ADVANCE and REALIZE clinical trials but were modified to take account of differences in prescribing rules between the trials and Australian clinical practice. The probability of transitioning between Markov disease states was based on data from the Australian Kirby Institute where possible and supplemented using data from the published literature. Utility values obtained from the EuroQol five-dimensional questionnaire data collected in the ADVANCE and REALIZE trials were used to represent the utility during HCV treatment. Utility values for Markov health states were taken from the published literature. Unit costs (2014 AU $) were taken from Australian sources.

RESULTS

In treatment-naive patients, the discounted cost per life-years gained was AU $37,706 and the discounted cost per quality-adjusted life-year was AU $19,283. In treatment-experienced patients, the discounted cost per life-year gained was AU $23,855 and the discounted cost per quality-adjusted life-year was AU $14,948.

CONCLUSION

Telaprevir plus PR in the Australian setting is cost-effective when compared with PR alone in patients infected with genotype 1 HCV.

Modeling Economic Effects of Vaccination Against Porcine Reproductive and Respiratory Syndrome: Impact of Vaccination Effectiveness, Vaccine Price, and Vaccination Coverage

Porcine reproductive and respiratory syndrome (PRRS) causes substantial financial losses in pig farms and economic losses to societies worldwide. Vaccination against PRRS virus (PRRSV) is a common intervention in affected farms. The aim of this study was to assess the economic impact and profitability of potential new PRRS vaccines with improved efficacy at animal, herd, and national level. Two vaccination strategies were modeled; (i) mass vaccination of sows only (MS) and (ii) mass vaccination of sows and vaccination of piglets (MSP), comprising different scenarios of vaccine effectiveness, vaccine price, and vaccination coverage. A farrow-to-finish farm with 1,000 working sows from a pig-dense region in Germany served as an example farm. Financial benefits were obtained from gross margin analyses and were defined as difference in gross margin between a PRRSV-infected farm without vaccination (baseline) and with vaccination (intervention). Financial benefits were highest if both sows and piglets (MSP) were vaccinated. In these scenarios, median annual net benefits per working sow ranged from €170 to 340. If sows only were vaccinated (MS), estimated benefits attributable to vaccination were between €148 and 270. Decisive variables for the estimation of national level benefits were the number of farmers switching from existing to a better protecting vaccine, the number of previously non-vaccinating herds adopting the new vaccine, and the effectiveness of the new vaccine relative to those already available. Benefits were greatest when the new vaccine was adopted by previously non-vaccinating herds. The analyses showed that vaccination against PRRS was beneficial for all modeled scenarios. The magnitude of benefits derived from vaccination was more susceptible to changes in vaccination effectiveness than to vaccine price changes. This study provides evidence to support future vaccine development. The estimates indicate that the introduction of more efficient vaccines might lead to substantial financial benefits, is of socio-economic importance and that new vaccines might significantly contribute to the reduction of disease burden.

Estimated global public health and economic impact of COVID-19 vaccines in the pre-omicron era using real-world empirical data

BACKGROUND

Limited data are available describing the global impact of COVID-19 vaccines. This study estimated the global public health and economic impact of COVID-19 vaccines before the emergence of the Omicron variant.

METHODS

A static model covering 215 countries/territories compared the direct effects of COVID-19 vaccination to no vaccination during 13 December 2020-30 September 2021. After adjusting for underreporting of cases and deaths, base case analyses estimated total cases and deaths averted, and direct outpatient and productivity costs saved through averted health outcomes. Sensitivity analyses applied alternative model assumptions.

RESULTS

COVID-19 vaccines prevented an estimated median (IQR) of 151.7 (133.7-226.1) million cases and 620.5 (411.1-698.1) thousand deaths globally through September 2021. In sensitivity analysis applying an alternative underreporting assumption, median deaths averted were 2.1 million. Estimated direct outpatient cost savings were $21.2 ($18.9-30.9) billion and indirect savings of avoided productivity loss were $135.1 ($121.1-206.4) billion, yielding a total cost savings of $155 billion globally through averted infections.

CONCLUSIONS

Using a conservative modeling approach that considered direct effects only, we estimated that COVID-19 vaccines have averted millions of infections and deaths, generating billions of cost savings worldwide, which underscore the continued importance of vaccination in public health response to COVID-19.

The Potential Cost and Cost-Effectiveness Impact of Using a Machine Learning Algorithm for Early Detection of Sepsis in Intensive Care Units in Sweden

Background: Early diagnosis of sepsis has been shown to reduce treatment delays, increase appropriate care, and reduce mortality. The sepsis machine learning algorithm NAVOY® Sepsis, based on variables routinely collected at intensive care units (ICUs), has shown excellent predictive properties. However, the economic consequences of forecasting the onset of sepsis are unknown. Objectives: The potential cost and cost-effectiveness impact of a machine learning algorithm forecasting the onset of sepsis was estimated in an ICU setting. Methods: A health economic model has been developed to capture short-term and long-term consequences of sepsis. The model is based on findings from a randomized, prospective clinical evaluation of NAVOY® Sepsis and from literature sources. Modeling the relationship between time from sepsis onset to treatment and prevalence of septic shock and in-hospital mortality were of particular interest. The model base case assumes that the time to treatment coincides with the time to detection and that the algorithm predicts sepsis 3 hours prior to onset. Total costs include the costs of the prediction algorithm, days spent at the ICU and hospital ward, and long-term consequences. Costs are estimated for an average patient admitted to the ICU and for the healthcare system. The reference method is sepsis diagnosis in accordance with clinical practice. Results: In Sweden, the total cost per patient amounts to €16 436 and €16 512 for the algorithm and current practice arms, respectively, implying a potential cost saving per patient of €76. The largest cost saving is for the ICU stay, which is reduced by 0.16 days per patient (5860 ICU days for the healthcare sector) resulting in a cost saving of €1009 per ICU patient. Stochastic scenario analysis showed that NAVOY® Sepsis was a dominant treatment option in most scenarios and well below an established threshold of €20 000 per quality-adjusted life-year. A 3-hour faster detection implies a reduction in in-hospital mortality, resulting in 356 lives saved per year. Conclusions: A sepsis prediction algorithm such as NAVOY® Sepsis reduces the cost per ICU patient and will potentially have a substantial cost-saving and life-saving impact for ICU departments and the healthcare system.

"Pay for Success" Financing and Home-Based Multicomponent Childhood Asthma Interventions: Modeling Results From the Detroit Medicaid Population

Policy Points: The Pay for Success (PFS) financing approach has potential for scaling the implementation of evidence-based prevention interventions in Medicaid populations, including a range of multicomponent interventions for childhood asthma that combine home environment risk mitigation with medical case management. Even though this type of intervention is efficacious and cost-saving among high-risk children with asthma, the main challenges for implementation in a PFS context include legal and regulatory barriers to capturing federal Medicaid savings and using them as a source of private investor repayment. Federal-level policy change and guidance are needed to support PFS financing of evidence-based interventions that would reduce expensive acute care among Medicaid enrollees.

CONTEXT

Pay for Success has emerged as a potential financing mechanism for innovative and cost-effective prevention programs. In the PFS model, interventions that provide value to the public sector are implemented with financing from private investors who receive a payout from the government only if the metrics identified in a performance-based contract are met. In this nascent field, little has been written about the potential for and challenges of PFS initiatives that produce savings and/or value for Medicaid.

METHODS

In order to elucidate the basic economics of a PFS intervention in a Medicaid population, we modeled the potential impact of an evidence-based multicomponent childhood asthma intervention among low-income children enrolled in Medicaid in Detroit. We modeled outcomes and a comparative benefit-cost analysis in 3 risk-based target groups: (1) all children with an asthma diagnosis; (2) children with an asthma-related emergency department visit in the past year; and (3) children with an asthma-related hospitalization in the past year. Modeling scenarios for each group produced estimates of potential state and federal Medicaid savings for different types or levels of investment, the time frames for savings, and some overarching challenges.

FINDINGS

The PFS economics of a home-based asthma intervention are most viable if it targets children who have already experienced an expensive episode of asthma-related care. In a 7-year demonstration, the overall (undiscounted) modeled potential savings for Group 2 were $1.4 million for the federal Medicaid and $634,000 for the state Medicaid programs, respectively. Targeting children with at least 1 hospitalization in the past year (Group 3) produced estimated potential savings of $2.8 million to federal Medicaid and $1.3 million to state Medicaid. However, current Medicaid rules and regulations pose significant challenges for capturing federal Medicaid savings for PFS payouts.

CONCLUSIONS

A multicomponent intervention that provides home remediation and medical case management to high-risk children with asthma has significant potential for PFS financing in urban Medicaid populations. However, there are significant administrative and payment challenges, including the limited ability to capture federal Medicaid savings and to use them as a source of investor repayment. Without some policy reform and clear guidance from the federal government, the financing burden of PFS outcome payments will be on the state Medicaid program or some other state-level funding source.

Uptake Rates of Risk-Reducing Surgeries for Women at Increased Risk of Hereditary Breast and Ovarian Cancer Applied to Cost-Effectiveness Analyses: A Scoping Systematic Review

The cost-effectiveness of genetic screen-and-treat strategies for women at increased risk for breast and ovarian cancer often depends on the women's willingness to make use of risk-reducing mastectomy (RRM) or salpingo-oophorectomy (RRSO). To explore the uptake rates of RRM and RRSO applied in health economic modeling studies and the impact of uptake rates on the incremental cost-effectiveness ratios (ICER), we conducted a scoping literature review. In addition, using our own model, we conducted a value of information (VOI) analysis. Among the 19 models included in the review, the uptake rates of RRM ranged from 6% to 47% (RRSO: 10% to 88%). Fifty-seven percent of the models applied retrospective data obtained from registries, hospital records, or questionnaires. According to the models' deterministic sensitivity analyses, there is a clear trend that a lower uptake rate increased the ICER and vice versa. Our VOI analysis showed high decision uncertainty associated with the uptake rates. In the future, uptake rates should be given more attention in the conceptualization of health economic modeling studies. Prospective studies are recommended to reflect regional and national variations in women's preferences for preventive surgery.

Economic modeling for improved prediction of saving estimates in healthcare costs from consumption of healthy foods: the Mediterranean-style diet case study

Background

By design, existing scenario-based nutrition economics studies on the financial benefits of healthy dietary behaviors generally report uncertainty in inputs and wide ranges of outcome estimates.

Objectives

This modeling exercise aimed to establish precision in prediction of the potential healthcare cost savings that would follow a reduction in the incidence of cardiovascular disease (CVD) consistent with an increase in adherence to a Mediterranean-style diet (MedDiet).

Design

Using a Monte Carlo simulation model on a cost-of-illness analysis assessing MedDiet adherence, CVD incidence reduction, and healthcare cost savings in the United States and Canada, short- and long-term cost savings that are likely to accrue to the American and Canadian healthcare systems were estimated using 20 and 80% increases in MedDiet adherence scenarios.

Results

Increasing percentage of population adhering to a MedDiet by 20% beyond the current adherence level produced annual savings in CVD-related costs of US$8.2 billion (95% confidence interval [CI], $7.5-$8.8 billion) in the United States and Can$0.32 billion (95% CI, $0.29-$0.34 billion) in Canada. An 80% increase in adherence resulted in savings equal to US$31 billion (95% CI, $28.6-$33.3 billion) and Can$1.2 billion (95% CI, $1.11-$1.30 billion) in each respective country.

Conclusion

Computational techniques with stochastic parameter inputs, such as the Monte Carlo simulation, could be an effective way of incorporating variability of modeling parameters in nutrition economics studies for improved precision in estimating the monetary value of healthy eating habits.

Development of an Initial Conceptual Model of Multiple Myeloma to Support Clinical and Health Economics Decision Making

Background. We aimed to develop and validate a conceptual model of multiple myeloma (MM) that characterizes the attributes affecting disease progression and patient outcomes, and the relationships between them. Methods. Systematic and targeted literature reviews identified disease- and patient-specific attributes of MM that affect disease progression and outcomes. These attributes were validated by a Delphi panel of four international MM experts, and a physician-validated model was constructed. Real-world clinical data from the Czech Registry of Monoclonal Gammopathies (RMG) was used to confirm the relationships between attributes using pairwise correlations and multiple Cox regression analysis. Results. The Delphi panel reached consensus that most cytogenetic abnormalities influenced disease activity, which results in symptoms and complications and affects overall survival (OS). Comorbidities and complications also affect OS. The entire panel agreed that quality of life was influenced by comorbidities, age, complications, and symptoms. Consensus was not reached in some cases, in particular, the influence of del(17p) on complications. The relationships between attributes were confirmed using pairwise analysis of real-world data from the Czech RMG; most of the correlations identified were statistically significant and the strength of the correlations changed with successive relapses. Czech RMG data were also used to confirm significant predictors of OS included in the model, such as age, Eastern Cooperative Oncology Group performance status, and extramedullary disease. Conclusions. This validated conceptual model can be used for economic modeling and clinical decision making. It could also inform the development of disease-based models to explore the impact of disease progression and treatment on outcomes in patients with MM.

Development of a health economic model to evaluate the potential benefits of optimal serum potassium management in patients with heart failure

AIMS

Patients with heart failure are at increased risk of hyperkalemia, particularly when treated with renin-angiotensin-aldosterone system inhibitor (RAASi) agents. This study developed a model to quantify the potential health and economic value associated with sustained potassium management and optimal RAASi therapy in heart failure patients.

MATERIALS AND METHODS

A patient-level, fixed-time increment stochastic simulation model was designed to characterize the progression of heart failure through New York Heart Association functional classes, and predict associations between serum potassium levels, RAASi use, and consequent long-term outcomes. Following internal and external validation exercises, model analyses sought to quantify the health and economic benefits of optimizing both serum potassium levels and RAASi therapy in heart failure patients. Analyses were conducted using a UK payer perspective, independent of costs and utilities related to pharmacological potassium management.

RESULTS

Validation against multiple datasets demonstrated the predictive capability of the model. Compared to those who discontinued RAASi to manage serum potassium, patients with normokalemia and ongoing RAASi therapy benefited from longer life expectancy (+1.38 years), per-patient quality-adjusted life year gains (+0.53 QALYs), cost savings (£110), and associated net monetary benefit (£10,679 at £20,000 per QALY gained) over a lifetime horizon. The predicted value of sustained potassium management and ongoing RAASi treatment was largely driven by reduced mortality and hospitalization risks associated with optimal RAASi therapy.

LIMITATIONS

Several modeling assumptions were made to account for a current paucity of published literature; however, ongoing refinement and validation of the model will ensure its continued accuracy as the clinical landscape of hyperkalemia evolves.

CONCLUSIONS

Predictions generated by this novel modeling approach highlight the value of sustained potassium management to avoid hyperkalemia, enable RAASi therapy, and improve long-term health economic outcomes in patients with heart failure.

The cost-effectiveness of an adjuvanted quadrivalent influenza vaccine in the United Kingdom

In the United Kingdom (UK), both the MF59-adjuvanted quadrivalent influenza vaccine (aQIV) and the high-dose QIV (QIV-HD) are preferred for persons aged 65 years and older but only aQIV is reimbursed by the National Health Service (NHS). The objective was to determine the potential cost-effectiveness of vaccinating adults aged 65 years and above with aQIV compared with QIV-HD in the UK. A dynamic transmission model, calibrated to match infection data from the UK, was used to estimate the impact of vaccination in 10 influenza seasons. Vaccine effectiveness was based on a meta-analysis that concluded the vaccines were not significantly different. Vaccine coverage, physician visits, hospitalizations, deaths, utility losses and NHS costs were estimated using published UK sources. The list price of aQIV was £11.88 while a range of prices were tested for QIV-HD. The price of the trivalent high-dose vaccine (TIV-HD) is £20.00 but a list price for QIV-HD is not yet available. The projected differences between the vaccines in terms of clinical cases and influenza treatment costs are minimal. Our analysis demonstrates that in order to be cost-effective, the price of QIV-HD must be similar to that of aQIV and may range from £7.57 to £12.94 depending on the relative effectiveness of the vaccines. The results of the analysis were most sensitive to variation in vaccine effectiveness and the rate of hospitalization due to influenza. Given the evidence, aQIV is cost-saving unless QIV-HD is priced lower than the existing list price of TIV-HD.

The Cost-Effectiveness of Expanding Vaccination with a Cell-Based Influenza Vaccine to Low Risk Adults Aged 50 to 64 Years in the United Kingdom

Background: In response to COVID-19, the UK National Health Service (NHS) extended influenza vaccination in 50- to 64-year-olds from at-risk only to all in this age group for the 2020/21 season. The objective of this research is to determine the cost-effectiveness of continuing to vaccinate all with a quadrivalent cell-based vaccine (QIVc) compared to returning to an at-risk only policy after the pandemic resolves. Methods: A dynamic transmission model, calibrated to match infection data from the UK, was used to estimate the clinical and economic impact of vaccination across 10 influenza seasons. The base case effectiveness of QIVc was 63.9% and the list price was GBP 9.94. Results: Vaccinating 50% of all 50- to 64-year-olds with QIVc reduced the average annual number of clinical infections (−682,000), hospitalizations (−5800) and deaths (−740) in the UK. The base case incremental cost per quality-adjusted life-year gained (ICER) of all compared to at-risk only was GBP6000 (NHS perspective). When the cost of lost productivity was considered, vaccinating all 50- to 64-year-olds with QIVc became cost-saving. Conclusion: Vaccinating all 50- to 64-year-olds with QIVc is likely to be cost-effective. The NHS should consider continuing this policy in future seasons.

Assessing the value of cardiac biomarkers: going beyond diagnostic accuracy?

In this era of scrutinized resource utilization, providers and payers are focused on the value of healthcare interventions more than ever. Cost-effectiveness evaluations are required by some health authorities and requested by others in order to guide budget allocation decisions. In the past, these evaluations did not methodologically consider laboratory diagnostics. We set out to explore the current requirements of health technology agencies that include laboratory diagnostics and describe, through a review of the literature, alternative methods for establishing the value of a biomarker or labroatory diagnostic beyond assay specifications and performance. The aim of this study was to evaluate the current use of a linked evidence approach in cost-effectiveness studies for cardiac laboratory tests in the last 5 years.

Challenges with Forecasting Budget Impact: A Case Study of Six ICER Reports

BACKGROUND

Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact.

OBJECTIVE

We examined how different modeling assumptions influenced the results of 6 BIMs from the Institute for Clinical and Economic Review (ICER).

STUDY DESIGN

Retrospective analysis of pharmaceutical sales data.

METHODS

From ICER reports issued before 2016, we collected estimates of 3 BIM outputs: aggregate therapy cost (ie, cost to treat the patient population with a particular therapy), therapy uptake, and price. We compared these against real-world estimates that we generated using drug sales data. We considered 2 classes of BIM estimates: those forecasting future uptake of new agents, which assumed "unmanaged uptake," and those describing the contemporaneous market state (ie, estimates of current, managed uptake and budget impact for compounds already on the market).

RESULTS

Differences between ICER's estimates and our own were largest for forecasted studies. Here, ICER's uptake estimates exceeded real-world estimates by factors ranging from 7.4 (sacubitril/valsartan) to 54 (hepatitis C treatments). The "unmanaged uptake" assumption (removed from ICER's approach in 2017) yields large deviations between BIM estimates and real-world consumption. Nevertheless, in some cases, ICER's BIMs that relied on current market estimates also deviated substantially from real-world sales data.

CONCLUSIONS

This study highlights challenges with forecasting budget impact. In particular, assumptions about uptake and data source selection can greatly influence the accuracy of results.

When does economic model type become a decisive factor in health technology appraisals? Learning from the expanding treatment options for relapsing-remitting multiple sclerosis

OBJECTIVES

Specific economic model types often become de facto standard for health technology appraisal over time. Markov and discrete event simulation (DES) models were compared to investigate the impact of innovative modeling on the cost-effectiveness of disease-modifying therapies (DMTs) in relapsing-remitting multiple sclerosis (RRMS). Fingolimod was compared to dimethyl fumarate (DMF; in highly active [HA] RRMS), alemtuzumab (in HA RRMS) and natalizumab (in rapidly evolving severe RRMS). Comparator DMTs were chosen to reflect different dosing regimens.

MATERIALS AND METHODS

Markov and DES models used have been published previously. Inputs were aligned in all relevant respects, with differences in the modeling of event-triggered attributes, such as relapse-related retreatment, which is inherently difficult with a memoryless Markov approach. Outcomes were compared, with and without different attributes.

RESULTS

All results used list prices. For fingolimod and DMF, incremental cost-effectiveness ratios (ICERs) were comparable (Markov: £4206/quality-adjusted life year [QALY] gained versus DES: £3910/QALY gained). Deviations were observed when long-term adverse events (AEs) were incorporated in the DES (Markov: £25,412 saved/QALY lost, versus DES: £34,209 saved/QALY lost, fingolimod versus natalizumab; higher ICERs indicate greater cost-effectiveness). For fingolimod versus alemtuzumab, when relapse-triggered retreatment was included in the DES, large cost differences were observed (difference between incremental cost is £35,410 and QALY is 0.10).

LIMITATIONS

UK payer perspective, therefore societal approach was not considered. Resource utilization and utilities for both models were not derived from the subpopulations; as the focus is on model type, input limitations that apply to both models are less relevant.

CONCLUSIONS

Whilst no model can fully represent a disease, a DES allows an opportunity to include features excluded in a Markov structure. A DES may be more suitable for modeling in RRMS for health technology assessment purposes given the complexity of some DMTs. This analysis highlights the capabilities of different model structures to model event-triggered attributes.

THE IMPACT OF CARBON TAXATION AND REVENUE RECYCLING ON U.S. INDUSTRIES

This paper provides a detailed, cross-model analysis and discussion of the implications of carbon tax scenarios on changes in sectoral output, energy production and consumption and the competitiveness of the United States' economy. Our analysis focuses on the broad patterns apparent across models in both qualitative and quantitative terms at the sector level, with a focus on energy-intensive, trade-exposed sectors. We identify how variations in carbon tax trajectories and different options for using the revenue from the tax drive these results.