Traditional Cost-effectiveness Analysis Research Articles

Levodopa-based device-aided therapies for the treatment of advanced Parkinson's disease: a social return on investment analysis.

Parkinson's disease (PD) is an incurable, progressive, neurodegenerative disorder. As PD advances and symptoms progress, patients become increasingly dependent on family and carers. Traditional cost-effectiveness analyses (CEA) only consider patient and payer-related outcomes, failing to acknowledge impacts on families, carers, and broader society. This novel Social Return on Investment (SROI) analysis aimed to evaluate the broader impact created by improving access to levodopa (LD) device-aided therapies (DATs) for people living with advanced PD (aPD) in Australia. A forecast SROI analysis over a three-year time horizon was conducted. People living with aPD and their families were recruited for qualitative interviews or a quantitative survey. Secondary research and clinical trial data was used to supplement the primary research. Outcomes were valued and assessed in a SROI value map in Microsoft Excel™. Financial proxies were assigned to each final outcome based on willingness-to-pay, economic valuation, and replacement value. Treatment cost inputs were sourced from Pharmaceutical Benefits Schedule (PBS) and Medicare Benefits Scheme (MBS) published prices. Twenty-four interviews were conducted, and 55 survey responses were received. For every $1 invested in access to LD-based DATs in Australia, an estimated $1.79 of social value is created. Over 3 years, it was estimated $277.16 million will be invested and $406.77 million of social return will be created. This value is shared between people living with aPD (27%), their partners (22%), children (36%), and the Australian Government (15%). Most of the value created is social and emotional in nature, including reduced worry, increased connection to family and friends, and increased hope for the future. Investment in LD-based DATs is expected to generate a positive social return. Over 50% of the value is created for the partners and children of people living with aPD. This value would not be captured in traditional CEA. The SROI methodology highlights the importance of investing in aPD treatment, capturing the social value created by improved access to LD-based DATs.

Use of Efficiency Frontiers to Align Prices and Clinical Benefits of Biologic Therapies for Plaque Psoriasis

The US lacks a systematic approach for aligning drug prices with clinical benefit, and traditional cost-effectiveness analysis (CEA) faces political obstacles. The efficiency frontier (EF) method offers policymakers an alternative approach. To assess how the EF approach could align prices and clinical benefits of biologic medications for plaque psoriasis and estimate price reductions in the US vs 4 peer countries: Australia, Canada, France, and Germany. This health economic evaluation used the EF approach to compare the prices and clinical benefits of 11 biologics and 2 biosimilars for plaque psoriasis in the US, Australia, Canada, France, and Germany. Data were collected from February to March 2023 and analyzed from March to June 2023. EFs were constructed based on each biologic's efficacy, measured using the Psoriasis Area and Severity Index (PASI) 90 response rate, and annual treatment cost as of January 2023; US costs were net of estimated manufacturer rebates. Prices based on the EF were compared with traditional CEA-based prices calculated by the Institute for Clinical and Economic Review at a threshold of $150 000 per quality-adjusted life-year gained. Among 13 biologics, PASI 90 response rates ranged from 17.9% (etanercept) to 71.6% (risankizumab); US net annual treatment costs ranged from $1664 (infliximab-dyyb) to $79 277 (risankizumab). The median (IQR) net annual treatment cost was higher in the US ($34 965 [$20 493-$48 942]) than prerebate costs in Australia ($9179 [$6691-$12 688]), Canada ($15 556 [$13 017-$16 112]), France ($9478 [$6637-$11 678]), and Germany ($13 829 [$13 231-$15 837]). The US EF included infliximab-dyyb (PASI 90: 57.4%; annual cost: $1664), ixekizumab (PASI 90: 70.8%; annual cost: $33 004), and risankizumab (PASI 90: 71.6%; annual cost: $79 277). US prices for psoriasis biologics would need to be reduced by a median (IQR) of 71% (31%-95%) to align with those estimated using the EF; the same approach would yield smaller price reductions in Canada (41% [6%-57%]), Australia (36% [0%-65%]), France (19% [0%-67%]), and Germany (11% [8%-26%]). Except for risankizumab, the EF-based prices were lower than the prices based on traditional CEA. This economic evaluation showed that for plaque psoriasis biologics, using an EF approach to negotiate prices could lead to substantial price reductions and better align prices with clinical benefits. US policymakers might consider using EFs to achieve prices commensurate with comparative clinical benefits, particularly for drug classes with multiple therapeutic alternatives for which differences can be adequately summarized by a single outcome measurement.

Reconstructing the value puzzle in health technology assessment: a pragmatic review to determine which modelling methods can account for additional value elements.

Health technology assessment (HTA) has traditionally relied on cost-effectiveness analysis (CEA) as a cornerstone of evaluation of new therapies, assessing the clinical validity and utility, the efficacy, and the cost-effectiveness of new interventions. The current format of cost-effectiveness analysis, however, does not allow for inclusion of more holistic aspects of health and, therefore, value elements for new technologies such as the impact on patients and society beyond its pure clinical and economic value. This study aimed to review the recent modelling attempts to expand the traditional cost-effectiveness analysis approach by incorporating additional elements of value in health technology assessment. A pragmatic literature review was conducted for articles published between 2012 and 2022 reporting cost-effectiveness analysis including value aspects beyond the clinical and cost-effectiveness estimates; searches identified 13 articles that were eligible for inclusion. These expanded modelling approaches mainly focused on integrating the impact of societal values and health equity in cost-effectiveness analysis, both of which were championed as important aspects of health technology assessment that should be incorporated into future technology assessments. The reviewed cost-effectiveness analysis methods included modification of the current cost-effectiveness analysis methodology (distributional cost-effectiveness analysis, augmented cost-effectiveness analysis, extended cost-effectiveness analysis) or the use of multi-criteria decision analysis. Of these approaches, augmented cost-effectiveness analysis appears to have the most potential by expanding traditional aspects of value, as it uses techniques already familiar to health technology assessment agencies but also allows space for incorporation of qualitative aspects of a product's value. This review showcases that methods to unravel additional value elements for technology assessment exist, therefore, patient access to promising technologies can be improved by moving the discussion from "if" to "how" additional value elements can inform decision-making.

EE217 Efficiency-Equity Trade-Offs in Cost-Effectiveness Analyses: An Umbrella Review of Previous Systematic Literature Reviews

Cost-effectiveness analyses (CEA) are important in healthcare decision-making and resource allocation for assessing costs and benefits of new treatments in terms of clinical efficiency. Expanding value elements, such as health equity, for new technologies in traditional CEAs has attracted interest. This study synthesized evidence on how equity concepts were considered in modified CEAs by conducting an umbrella review of systematic literature reviews (SLR).

EE216 Which Modelling Methods Can Account for Additional Value Elements in HTAs? Results from a Pragmatic Review

Health technology assessment (HTA) has traditionally relied on cost-effectiveness analysis (CEA) as a cornerstone to evaluate new therapies. The current approach to CEA, however, does not allow for inclusion of more holistic aspects of health; therefore, value elements for new technologies beyond basic clinical and economic value, such as a technology’s impact on patients and society, are largely overlooked. This study aimed to review the recent modelling attempts to expand the traditional CEA approach by incorporating additional elements of value in HTA.

The Broader Opportunity Costs in the Broader Cost-Effectiveness Analysis Framework.

The traditional cost-effectiveness analysis framework usually takes a healthcare system perspective, where the aim is to maximise population health from a fixed budget allocated to healthcare. Extensions to this framework have been suggested, including: (i) incorporating impacts that fall outside the healthcare sector; (ii) accounting for outcomes beyond health; and (iii) assessing equity considerations. Several alternatives have been proposed that serve these purposes, for example, the extended "impact inventory", the "beyond-the-QALY" approach and the distributional cost-effectiveness analysis. This paper aims to develop a comprehensive framework that incorporates into the cost-effectiveness analysis framework some of its most advocated extensions and provides a means of arriving at a unidimensional cost-effectiveness analysis result measure. Building on previous work, I proposed a framework that explicitly incorporates the full extent of the opportunity costs that arise when new dimensions and distributional concerns are included in cost-effectiveness analyses. A hypothetical example is provided as a way of illustration. Operationalising the proposed framework requires system-wide representative values and/or robust estimates concerning: (i) selecting dimensions; (ii) measuring opportunity costs associated with each dimension; (iii) quantifying equity weights and percentages of beneficiaries and losers meeting equity considerations; and (iv) attaching monetary values to dimensions measured using a non-monetary metric. Extending the cost-effectiveness analysis framework entails extending the measurement of the opportunity costs of funding decisions. This implies populating an ambitious puzzle that in some cases poses fundamental conceptual and empirical questions. Potential routes of further research that might facilitate such undertaking are proposed.

Assessing the impact of single or short-term administration on a therapy’s cost-effectiveness: a hypothetical disease-agnostic model

AimsAssessing the value of single or short-term therapies (SSTs) within traditional cost-effectiveness analyses (CEAs) has been a topic of discussion as the number of SSTs increases, particularly regarding the effect of discounting on valuation. To quantify the impact of discounting in economic evaluations, a CEA of a hypothetical SST and equivalent chronic therapy was conducted using standard methods.Materials and methodsA lifetime Markov model was developed for a hypothetical chronic, progressive disease that could be treated with an SST, chronic therapy, or no novel treatment, termed standard of care (SoC). Incremental cost-effectiveness ratios (ICERs) with quality-adjusted life years (QALYs) comparing SST vs. SoC and an equivalent chronic therapy vs. SoC were assessed from a payer perspective. Both treatments had equal benefits and undiscounted lifetime costs; 3% discounting was applied to costs/benefits in the base case, and the impact of discounting was assessed.ResultsIn the base case example, both the SST and equivalent chronic therapy vs. SoC had ICERs of $86,000/QALY without discounting. With 3% discounting, the ICER for the SST increased by 116% ($186,000/QALY) while the ICER for the chronic therapy increased by 10% ($95,000/QALY) despite equal clinical benefit. In scenario analyses, the ICER of the SST was consistently higher than the equivalent chronic therapy across a range of assumptions/inputs. Varying the cost/benefit discount rates had a greater impact on the SST. Differences in the ICERs between the therapies increased with increasing life expectancy/time horizon.LimitationsThe simple model structure may not be reflective of acute or more complex diseases. Also, the scenario of perfect equivalency in efficacy and lifetime costs is hypothetical.ConclusionsThis quantitative assessment showed the extent to which SST CEAs are highly sensitive to discounting, resulting in worse value assessments for SSTs than equivalent chronic therapies.

How to do (or not to do)… health resource allocations using constrained mathematical optimization.

Despite the push towards evidence-based health policy, decisions about how to allocate health resources are all too often made on the basis of political forces or a continuation of the status quo. This results in wastage in health systems and loss of potential population health. However, if health systems are to serve people best, then they must operate efficiently and equitably, and appropriate valuation methods are needed to determine how to do this. With the advances in computing power over the past few decades, advanced mathematical optimization algorithms can now be run on personal computers and can be used to provide comprehensive, evidence-based recommendations for policymakers on how to prioritize health spending considering policy objectives, interactions of interventions, real-world system constraints and budget envelopes. Such methods provide an invaluable complement to traditional or extended cost-effectiveness analyses or league tables. In this paper, we describe how such methods work, how policymakers and programme managers can access them and implement their recommendations and how they have changed health spending in the world to date.

Measurement and valuation of the attributes of innovation of healthcare technologies: a systematic review

Objective Innovative technologies (e.g. treatments) play a pivotal role in improving patient’s well-being and in consequence population health outcomes. However, there is lack of consensus and comprehensive summary what constitutes innovation. Additionally, valuing them using traditional cost-effectiveness analysis is unlikely to capture the full range of benefits of these innovative technologies. This review aims to understand how innovation attributes were measured and/or valued in healthcare. Materials and methods We systemically searched four databases, PubMed, Embase, PsycINFO, and Econlit, from inception to April 2021. Studies were included if they measured and/or valued the attributes of innovation for healthcare identified in our previous systematic review. Any other potential recommended methods to measure and/or value the innovation attributes were also extracted. Results Of 546 articles, a total of 17 articles were finally included in this review. If attributes were measured and traded-off relative to costs, then it was considered as valuation of those attributes. Two specific attributes of innovation, i.e. substantial benefits and convenience and/or adherence were measured using adherence rate and life year or QALY gain. When innovation attribute was non-specific it was described as “overall innovation” and measured using overall innovativeness scale (e.g. point/binary scale). QALY-based cost-effectiveness analysis (CEA) was commonly used to assess and value substantial benefit attribute. Other valuation approaches were (i) rating, (ii) the economic value of life year gain, (iii) multiple criteria decision analysis (MCDA), (iv) incremental net health benefit (INHB), and (v) quality-adjusted cost of care (QACC). ICER threshold adjustment and multiple-criteria decision analysis (MCDA) are two common recommended approaches to capture the innovation comprehensively. We found that MCDA approaches often promoted and discussed but were sub-optimally used to incorporate different value attributes into decision-making. Conclusions Existing methods used by payers to measure and value the innovation component of a new product do not reflect the full range of health and cost impacts. They generally do not consider the alternative perspectives of patients, providers, caregivers, and society. Key challenges remain to appropriately measure and value innovation attributes and incorporate them into HTA decision making.

Valuing treatment in oncology: embracing a broader notion of value.

Over the past decade, we have witnessed unprecedented, groundbreaking innovation in pharmaceuticals. This has been particularly true in oncology, where new therapies have increased survival and at times offered clinical cure. However, the impact of these promising treatments has been attenuated by persistent access and cost challenges that may limit their effect. A narrative has emerged that many of these so-called breakthroughs are not priced according to the value they provide. Traditional cost-effectiveness analyses would appear to support these doubts, often suggesting that innovative therapies do not represent value for money. However, there is a case to be made that innovative therapies require equally innovative value assessments. To explore this emerging viewpoint, this article provides a brief introduction to the current value debate and oncology-specific considerations when assessing elements of value. We offer a brief background on the nature and development of quality-adjusted life-years as a part of cost-effectiveness analyses and some of their key limitations; a primer on "novel" elements of value, which capture specific aspects of patient and societal preferences not included in quality-adjusted life-years; and their applicability to oncology including discussion on areas where further thought and research might be needed. We conclude with a potential checklist of novel elements of value that should be considered. DISCLOSURES: This Viewpoints article was funded by Novartis, Inc., which also provided funding to COVIA Health Solutions for manuscript development. The sponsor was involved in developing the manuscript. Kamal-Bahl and Puckett are employees of COVIA Health Solutions, a consulting firm that provides services to biopharmaceutical clients, trade organizations, and foundations. Kamal-Bahl holds stock in Merck and Pfizer. Singh is an employee of Novartis Pharmaceuticals. Willke received personal fees from COVIA Health Solutions for work on the manuscript.

Novel elements of value in the context of oncology.

e18823 Background: Over the past decade, perhaps no single area of the health sector has seen as much groundbreaking innovation as pharmaceuticals. This has been especially true in oncology, where promising curative treatments have been initially celebrated by the media only for access and cost challenges to limit their impact. A narrative has emerged that many of these breakthroughs are not priced according to the value they provide. This thinking has been reinforced by traditional approaches to cost-effectiveness analysis (CEA) that fail to incorporate critically relevant dimensions of value for innovative oncology therapies. What might a broader conception of value in oncology look like? To answer that question, this study reviews oncology-specific considerations when assessing elements of value. Methods: We first review the background on the nature and development of quality-adjusted life years (QALYs) as a part of cost-effectiveness analyses and some of their key limitations. This is followed by a review of “novel” elements of value, which capture specific aspects of patient and societal preferences not included in QALYs, and their applicability to oncology, including discussion on areas where further thought and research might be needed. We conclude with a potential checklist of novel elements of value that should be considered when designing value assessment strategies for products in oncology. Results: Key novel value elements not captured in QALYs under traditional CEA that can be relevant for oncology include value of hope (for a cure), value of insurance (reducing health and financial risk), value of treating very severe diseases, and, real option value (for treatments extending survival enough to allow the option of future cures). The novel value elements of reduced diagnostic uncertainty and the value of knowing are also directly relevant for oncology products with companion diagnostics. Other relevant novel value elements within the context of oncology include scientific spillovers and equity. Few studies have measured these value elements with applications in oncology. Conclusions: Our key takeaways include: (1) since cancer is often a severe disease that is expensive to treat, the potential for novel value elements to be important in economic evaluations of oncology products is high; (2) while some elements of value have been explored in specific economic evaluations, there has been limited adoption of novel elements of value in oncology; (3) the conceptual justification for use of novel value elements in oncology is strong, but standards for their measurement are evolving and further experience with their use would be beneficial; and (4) given the lower prioritization of many of them from the payer perspective, barriers to payer acceptance also seem significant, implying attention must also be paid to establishing the relevance of those elements to payer decision-making.

Lower Drug Cost of Successfully Treating Patients with Type 2 Diabetes to Targets with Once-Weekly Semaglutide versus Once-weeklyDulaglutide in Japan: A Short-Term Cost-Effectiveness Analysis.

In the head-to-head trial (SUSTAIN 7), the novel, injectable, once-weekly GLP-1 analogue semaglutide showed superiority in both glycemic outcomes and body weight reduction, compared with once-weeklydulaglutide in the treatment of type 2 diabetes (T2D). However, no economic evaluation using these data has yet been conducted in the Japanese setting. The objective of this analysis was to assess the short-term cost-effectiveness in Japan of once-weekly semaglutide 0.5mg (the approved maintenance dose in Japan) compared withonce-weekly dulaglutide 0.75mg (the only licensed dose in Japan) over a 1-year period using Japanese cost data. Responder endpoints were obtained from the SUSTAIN 7 trial to assess the cost of successfully treating patients to these targets ("cost of control"). Responder endpoint definitions consisted of single, dual, and triple composite endpoints related to glycemic control, body weight, and hypoglycemia outcomes. The cost of treatment was accounted from a healthcare payer perspective, capturing drug costs only. Treatment with once-weekly semaglutide 0.5mg was associated with a lower cost and a lower cost per patient treated to target for all endpoints, compared with once-weeklydulaglutide 0.75mg. For each JPY1 spent on bringing patients to target with once-weekly semaglutide 0.5mg, JPY1.58, JPY1.44, JPY1.60, JPY2.10, and JPY2.33 would need to be spent on once-weeklydulaglutide 0.75mg to achieve an equivalent outcome for endpoints of HbA1c ≤ 6.5%, HbA1c < 7.0%, HbA1c < 7.0% without hypoglycemia, and no weight gain, weight loss ≥ 5%, and ≥ 1.0% HbA1c reduction and ≥ 3.0% weight loss, respectively. These findings suggest that once-weekly semaglutide is a cost-effective treatment option compared withonce-weekly dulaglutide for patients with T2D in Japan. In the future, this finding should be extrapolated to traditional long-term cost-effectiveness analysis, using common outcomes such as quality-adjusted life years.

Economic Value of Greater Access to Bariatric Procedures for Patients With Severe Obesity and Diabetes.

Designing optimal insurance is important to ensure access to care for individuals that are most likely to benefit. We examined the potential impact of lowering patient cost-sharing for bariatric procedures. After defining 10 subgroups by body mass index (BMI) and type 2 diabetes mellitus (T2DM), we analyzed the National Health and Nutrition Examination Survey datasets to estimate the prevalence of each subgroup. The MarketScan claims database provided utilization rates and costs of bariatric procedures. Using an existing cost-effectiveness model, we estimated the economic value of bariatric procedures under various cost-sharing levels (0%-25%) with 2 frameworks: (1) a traditional cost-effectiveness analysis and (2) a new approach that incorporates utilization effects across subgroups. The utilization rate was higher among individuals with T2DM than those without T2DM (90.4 vs. 59.1 cases per 100,000) for bariatric procedures, which were more cost-effective for those with T2DM and a higher BMI. After accounting for utilization effects, the economic value of bariatric surgery was $177 and $63 per individual from a lifetime and a 5-year time horizon, respectively. Under no patient cost-sharing for individuals with BMI≥40 and T2DM, utilization rates were expected to increase by 21 cases per 100,000, resulting in additional $2 realized value per patient and $7.07 million in returns at the US population level. Cost-sharing is a barrier to uptake of a clinical and cost-effective treatment for severe obesity. Reducing cost-sharing for patients with severe obesity and T2DM could potentially increase the utilization of bariatric procedures and result in greater economic value to payers.

Health-system-adapted data envelopment analysis for decision-making in universal health coverage.

ObjectiveTo develop and test a method that allows an objective assessment of the value of any health policy in multiple domains.MethodsWe developed a method to assist decision-makers with constrained resources and insufficient knowledge about a society’s preferences to choose between policies with unequal, and at times opposing, effects on multiple outcomes. Our method extends standard data envelopment analysis to address the realities of health policy, such as multiple and adverse outcomes and a lack of information about the population’s preferences over those outcomes. We made four modifications to the standard analysis: (i) treating the policy itself as the object of analysis, (ii) allowing the method to produce a rank-ordering of policies; (iii) allowing any outcome to serve as both an output and input; and (iv) allowing variable return to scale. We tested the method against three previously published analyses of health policies in low-income settings.ResultsWhen applied to previous analyses, our new method performed better than traditional cost–effectiveness analysis and standard data envelopment analysis. The adapted analysis could identify the most efficient policy interventions from among any set of evaluated policies and was able to provide a rank ordering of all interventions.ConclusionHealth-system-adapted data envelopment analysis allows any quantifiable attribute or determinant of health to be included in a calculation. It is easy to perform and, in the absence of evidence about a society’s preferences among multiple policy outcomes, can provide a comprehensive method for health-policy decision-making in the era of sustainable development.

Health care input constraints and cost effectiveness analysis decision rules

Results of cost effectiveness analyses (CEA) studies are most useful for decision makers if they face only one constraint: the health care budget. However, in practice, decision makers wishing to use the results of CEA studies may face multiple resource constraints relating to, for instance, constraints in health care inputs such as a shortage of skilled labour. The presence of multiple resource constraints influences the decision rules of CEA and limits the usefulness of traditional CEA studies for decision makers. The goal of this paper is to illustrate how results of CEA can be interpreted and used in case a decision maker faces a health care input constraint.We set up a theoretical model describing the optimal allocation of the health care budget in the presence of a health care input constraint. Insights derived from that model were used to analyse a stylized example based on a decision about a surgical robot as well as a published cost effectiveness study on eye care services in Zambia.Our theoretical model shows that applying default decision rules in the presence of a health care input constraint leads to suboptimal decisions but that there are ways of preserving the traditional decision rules of CEA by reweighing different cost categories. The examples illustrate how such adjustments can be made, and makes clear that optimal decisions depend crucially on such adjustments.We conclude that it is possible to use the results of cost effectiveness studies in the presence of health care input constraints if results are properly adjusted.

PD44 Multi-Comparator Incremental Cost-Effectiveness Ratio: A New Framework For Cost-Effectiveness Analysis

Introduction:Current practice in cost-effectiveness analysis (CEA) involves the estimation of the incremental cost-effectiveness ratio (ICER) between a new intervention and one alternative comparator reflecting the standard of care. As this focuses on pairwise comparisons, rather than considering the whole range of available alternatives at any given time, this method fails to capture the full impact of bringing the new intervention to market.Methods:A multi-comparator ICER (MC-ICER) evaluating the impact of the new technology on patients treated with all comparators used in clinical practice, rather than a theoretical ‘second-best’ alternative only, was estimated. This can be achieved by weighting the incremental costs and benefits for each comparator by its change in market share to generate an MC-ICER. This is shown using a stylized example with three comparators.Results:The traditional ICER against the second-best alternative was USD 200,000 per QALY, while the estimated multi-comparator ICER is USD 133,548 per QALY, corresponding to a 33 percent decrease. This reflects the fact that patients who switch to the new intervention are not only those who had been previously treated with one particular comparator, as is assumed in a traditional CEA. The difference between the traditional ICER and the MC-ICER depends on how the new intervention impacts on the uptake of each comparator.Conclusions:Results show that, when comparator selection was made excluding dominated and extendedly-dominated alternatives, the MC-ICER, produced using the method described above, is lower than the traditional ICER comparing the new intervention to the second-best comparator. This captures the fact that patients may switch to the new intervention not only from the second-best comparator, but from the whole range of alternative treatments. Such patient movements determine the real impact, or opportunity cost, of the new intervention on the healthcare system and, therefore, should be captured in CEA alongside traditional one-way ICERs.

Incorporating social justice and stigma in cost-effectiveness analysis: drug-resistant tuberculosis treatment.

Novel therapies for multidrug-resistant tuberculosis (MDR-TB) are likely to be expensive. The cost of novel drugs (e.g., bedaquiline, delamanid) may be so prohibitively high that a traditional cost-effectiveness analysis (CEA) would rate regimens containing these drugs as not cost-effective. Traditional CEA may not appropriately account for considerations of social justice, and may put the most disadvantaged populations at greater risk. Using the example of novel drug regimens for MDR-TB, we propose a novel methodology, 'justice-enhanced CEA', and demonstrate how such an approach can simultaneously assess social justice impacts alongside traditional cost-effectiveness ratios. Justice-enhanced CEA, as we envision it, is performed in three steps: 1) systematic data collection about patients' lived experiences, 2) use of empirical findings to inform social justice assessments, and 3) incorporation of data-informed social justice assessments into a decision analytic framework that includes traditional CEA. These components are organized around a core framework of social justice developed by Bailey et al. to compare impacts on disadvantage not otherwise captured by CEA. Formal social justice assessments can produce three composite levels: 'expected not to worsen…', 'may worsen…', and 'expected to worsen clustering of disadvantage'. Levels of social justice impact would be assessed for each major type of outcome under each policy scenario compared. Social justice assessments are then overlaid side-by-side with cost-effectiveness assessments corresponding to each branch pathway on the decision tree. In conclusion, we present a 'justice-enhanced' framework that enables the incorporation of social justice concerns into traditional CEA for the evaluation of new regimens for MDR-TB.

Fairness in cost-benefit analysis: A methodology for health technology assessment.

We evaluate the introduction of various forms of antihypertensive treatments in France with a distribution-sensitive cost-benefit analysis. Compared to traditional cost-benefit analysis, we implement distributional weighting based on equivalent incomes, a new concept of individual well-being that does respect individual preferences but is not subjectively welfarist. Individual preferences are estimated on the basis of a contingent valuation question, introduced into a representative survey of the French population. Compared to traditional cost-effectiveness analysis in health technology assessment, we show that it is feasible to go beyond a narrow evaluation of health outcomes while still fully exploiting the sophistication of medical information. Sensitivity analysis illustrates the relevancy of this richer welfare framework, the importance of the distinction between an ex ante and an ex post approach, and the need to consider distributional effects in a broader institutional setting.

Toward a Hedonic Value Framework in Health Care.

In well-functioning markets, a hedonic pricing scheme can reflect the marginal valuation of various attributes of a differentiated product at market equilibrium. It serves as an important tool to inform pricing of a new product with a specific combination of attributes. Because health cannot be bought and sold in a market setting, and health care markets are distorted by insurance or government subsidies, direct valuation of a health intervention as a differentiated good through observed market prices is difficult. In this article, we discuss the rationale of using stated preference methods for developing a hedonic value framework for health insurance products to inform the decision on whether a product should be covered or subsidized by insurance, given its price. This value index will not reflect marginal value at market equilibrium, as in a hedonic pricing scheme, but would capture the distribution of marginal value in the population. We discuss how affordability concerns can be integrated into the development of a hedonic valuation model. We compare this framework with traditional cost-effectiveness analysis and also the existing value frameworks put forth by various organizations. The framework can be adopted to inform other decisions such as pricing. We argue that developing such a comprehensive and decision-theoretic value framework is feasible and, if successful, can serve to inform health care resource allocation in this country for decades to come in a systematic manner.

Toward a Broader Concept of Value: Identifying and Defining Elements for an Expanded Cost-Effectiveness Analysis.

This commentary identifies and defines potentially useful expansions to traditional cost-effectiveness analysis as often used in health technology assessment. Since the seminal 1977 article by Weinstein and Stason, the recommended approach has been the use of the incremental cost-effectiveness ratio based on the metric of the cost per quality-adjusted life-year gained, allowing comparisons across different technologies. An expanded framework, incorporating a wider range of the elements of value, is proposed. In addition to the core value drivers of health gain and other health system cost savings (if any), we propose adding other less recognized elements related to the value of knowing and informational externalities. We describe each of five factors related to the value of knowing: 1) a reduction in uncertainty, reflecting the benefit of a companion diagnostic increasing the certainty of a patient׳s response to a medicine; 2) insurance value related to greater peace of mind due to protection against catastrophic health and financial loss; 3) the value of hope for a "cure," leading individuals to become risk seekers in some circumstances; 4) real option value due to life extension opening possibilities for individuals to benefit from future innovation; and 5) spillovers or externalities arising from benefits of scientific advances that cannot be entirely appropriated by those making the advances. Further thought and research are needed on how best to measure and integrate these elements into an incremental value framework and on coverage and pricing decisions.