Quantifying Value of Hope

Multistakeholder Perceptions of Additional Value Elements for United States Value Assessment of Health Interventions

OBJECTIVES

Limitations in conventional cost-effectiveness methods have led to calls for incorporation of additional value elements in assessments of health technologies. However, gaps remain in how additional value elements may inform decision making. This study aimed to prioritize additional value elements from the perspective of healthy individuals without a specific condition or indicated for a specific treatment in the United States among a multistakeholder panel and compare the importance of perspective-specific value elements.

METHODS

Additional value elements were prioritized in 2 phases: (1) we identified and categorized additional value elements in a targeted literature review, and (2) we convened a multistakeholder group-based preference elicitation study (N = 28) to evaluate the description of each value element and rank and generate normalized weights of each value element for its significance in value assessment. The importance of additional value elements was also weighted relative to patient-centric value elements.

RESULTS

The rank and weight of contextual value elements among 28 stakeholders were "severity of the disease" (26.2%), "disadvantaged and vulnerable target populations highly represented" (21.8%), "broader economic impact" (17.3%), "risk protection" (13.8%), "rarity of the disease" (11.3%), and "novel mechanism of action" (9.7%). Relative weight of the additional value elements versus patient-centric value elements was 52% and 48%, respectively.

CONCLUSIONS

Study findings may inform priority setting for value frameworks and emerging US government assessments. The group-based elicitation method is repeatable and useful for structured deliberative processes in value assessment and may help improve the consistency and predictability of what is important to stakeholders.

A Preference-Based Value Assessment of the Fear of COVID-19 Contagion

Purpose

To assess the preference-based value of the fear of COVID-19 contagion.

Patients and Methods

We conducted a web-based, cross-sectional discrete choice experiment among 544 US adults. We used a Bayesian efficient design to generate choice sets. Each choice set comprised two hypothetical COVID-19 vaccine options characterized by seven attributes: chance of COVID-19 infection, chance of having severe symptoms from COVID-19 infection, vaccine protection duration, chance of mild to moderate adverse events from vaccination, chance of serious adverse events from vaccination, chance of future exposure to COVID-19 after vaccination, and out-of-pocket cost. We used mixed logit (ML) and latent class (LC) models to analyze data. Furthermore, we calculated the willingness-to-pay for eliminating the chance of future exposure to COVID-19, shedding light on the value attributed to the fear of contagion.

Results

The ML model demonstrated all attributes, including the chance of future exposure to COVID-19, were statistically significant. The participants were willing to pay approximately $13,046 to eliminate the chance of future exposure to COVID-19 or their fear of contagion when COVID-19 was still pandemic. The LC model unveiled two participant classes with distinct preference weights for the chance of future exposure to COVID-19 and out-of-pocket cost attributes. Nevertheless, the chance of future exposure to COVID-19 exposure held a significant degree of importance in both classes.

Conclusion

The chance of future exposure to COVID-19 exposure or fear of contagion was a significant element in the value assessment of COVID-19 vaccines. Further studies should be conducted to verify the value of fear of contagion and include it in the value assessment of healthcare technologies for infectious diseases.

Public preferences in healthcare resource allocation: A discrete choice experiment in South Korea

OBJECTIVES

This study aimed to explore the public view on priority-setting criteria for healthcare resource allocation. Specifically, it investigates how the value of a quality-adjusted life year (QALY) varies depending on patient characteristics.

METHODS

A discrete choice experiment was conducted using an online sample of the general South Korean population. Respondents were presented with two competing treatment scenarios. The attributes of the scenarios were age at disease onset, life expectancy without treatment, life-years gain with treatment, health-related quality of life (HRQoL) without treatment, and HRQoL gains with treatment. Two hundred choice sets were generated and randomly allocated into 20 blocks. A conditional logit model was used to estimate the factors affecting the respondents' choices.

RESULTS

A total of 3,482 respondents completed the survey. The larger the QALY gain, the more likely it was that the scenario would be chosen but with a diminishing marginal value. Respondents prioritized 40-year-old patients over 5-year-olds and 5-year-olds over 70-year-olds and prioritized baseline HRQoL of 40% and 60% over 20%. Patients at the end of life were not preferred to those with a longer life expectancy.

CONCLUSION

Overall, respondents preferred health-maximizing options without explicit consideration for end-of-life patients or those with poor health. In addition, they revealed a kinked preference for patient age, prioritizing middle-aged patients over children and older people.

Value elements and methods of value-based pricing for drugs in Japan: a systematic review

INTRODUCTION

Value-based pricing (VBP) can be a promising tool for optimizing drug prices. However, there is no consensus on the specific value elements and pricing method that should be used for VBP.

AREAS COVERED

We performed a systematic review and narrative synthesis to investigate the value elements and pricing method for VBP. The main inclusion criterion was that value elements, VBP method, and estimated prices for actual drugs were reported. We performed a search in MEDLINE and ICHUSHI Web. Eight articles met the selection criteria. Four studies adopted the cost-effectiveness analysis (CEA) approach and the others used different approaches. The CEA approach included the value elements of productivity, value of hope, real option value, disease severity, insurance value in addition to costs and quality-adjusted life years. The other approaches used efficacy, toxicity, novelty, rarity, research and development costs, prognosis, population health burden, unmet needs, and effectiveness. Each study used individual methods to quantify these broader value elements.

EXPERT OPINION

Both conventional and broader value elements are used for VBP. To allow VBP to be widely applied to various diseases, a simple, versatile method is preferable. Further research is needed to establish VBP method which enables to incorporate broader values.

Monetary values of increasing life expectancy: Sensitivity to shifts of the survival curve

Individuals' monetary values of decreases in mortality risk depend on the magnitude and timing of the risk reduction. We elicited stated preferences among three time paths of risk reduction yielding the same increase in life expectancy (decreasing risk for the next decade, subtracting a constant from or multiplying risk by a constant in all future years) and willingness to pay (WTP) for risk reductions differing in timing and life-expectancy gain. Respondents exhibited heterogeneous preferences over the alternative time paths, with almost 90 percent reporting transitive orderings. WTP is statistically significantly associated with life-expectancy gain (between about 7 and 28 days) and with respondents' stated preferences over the alternative time paths. Estimated value per statistical life year (VSLY) can differ by time path and averages about $500,000, roughly consistent with conventional estimates obtained by dividing estimated value per statistical life by discounted life expectancy.

Expanding health technology assessment towards broader value: Ireland as a case study

Healthcare innovations often represent important improvements in population welfare, but at what cost, and to whom? Health technology assessment (HTA) is a multidisciplinary process to inform resource allocation. HTA is conventionally anchored on health maximization as the only relevant output of health services. If we accept the proposition that health technologies can generate value outside the healthcare system, resource allocation decisions could be suboptimal from a societal perspective. Incorporating "broader value" in HTA as derived from social values and patient experience could provide a richer evaluative space for informing resource allocation decisions. This article considers how HTA is practiced and what its current context implies for adopting "broader value" to evaluating health technologies. Methodological challenges are highlighted, as is a future research agenda. Ireland serves as an example of a healthcare system that both has an explicit role for HTA and is evolving under a current program of reform to offer universal, single-tier access to public services. There are various ways in which HTA processes could move beyond health, including considering the processes of care delivery and/or expanding the evaluative space to some broader concept of well-being. Methods to facilitate the latter exist, but their adaptation to HTA is still emerging. We recommend a multi-stakeholder working group to develop and advance an international agenda for HTA that captures welfare/benefit beyond health.

Incorporating risk preferences of patients in the valuation of immune checkpoint inhibitors for non-small cell lung cancer

Immunotherapy offers a distinctive mechanism of action compared to traditional treatments, arising from additional value dimensions that may not be captured in standard health technology assessments. Cancer patients may have the expectation that immunotherapy provides durable, long-term survival gains. Moreover, some patients may be willing to take a 'risk' to undergo immunotherapy to achieve better survival outcomes. We reviewed quantitative methods that explored patients' risk preferences in their non-small cell lung cancer (NSCLC) treatment choices, in PubMed (MEDLINE), from January 1, 2015, until July 1, 2022. The consideration of a value dimension ('hope') based on patients' risk-seeking preferences is specifically addressed for the valuation of immune checkpoint inhibitors in NSCLC. We reported that the quantitative methods that aim to measure patients' risk preferences or 'hope' empirically are emerging. Value assessments should not only comprise survival improvements for the mean or median patient but also consider methods that reflect durable, long-term overall survival gains for risk-seeking patients. However, the published evidence for incorporating 'hope' based on patients' stated preferences for uncertain treatment profiles is not strong, and future research could strengthen this evidence base. We encourage further research on the development and validation of quantification methods to incorporate 'hope' and risk preferences of patients treated with immunotherapy for NSCLC and beyond.

Should We Consider Including a Value for "Hope" as an Additional Benefit Within Health Technology Assessment?

Health technology assessment (HTA) typically uses average health-related quality of life gain as its main measure of benefit used in economic evaluation. Nevertheless, there have been calls to consider novel aspects of benefit including the "value of hope," defined as a patients' potential preferences for a wider distribution of treatment benefit with a positive skew, in the hope that they will be one of the lucky ones. The value of hope may also derive from feeling hopeful as a positive mental state, which may be missing from current measures of health-related quality of life. The value attributed to feeling hopeful could be related to, or additional to, the value derived from possible risk-seeking preferences. Here, we reflect upon the strength of the case for the inclusion of the "value of hope" taking a critical look at the commonly referenced evidence for including the "value of hope" as risk-seeking preferences. We also draw attention to other conceptions of hope-as an emotion, a cognitive process, or a combination of both-and reflect upon the potential of including these broader notions of hope into HTA. The case for the inclusion of the "value of hope" based on risk-seeking preferences is weak. We suggest research questions that could give further evidence on whether hope is an important missing value from HTA.

The Net Benefit of Personalized Medicine: A Systematic Literature Review and Regression Analysis

OBJECTIVES

Amidst conflicting expectations about the benefits of personalized medicine (PM) and the potentially high implementation costs, we reviewed the available evidence on the cost-effectiveness of PM relative to non-PM.

METHODS

We conducted a systematic literature review of economic evaluations of PM and extracted data, including incremental quality-adjusted life-years (ΔQALYs) and incremental costs (Δcosts). ΔQALYs and Δcosts were combined with estimates of national cost-effectiveness thresholds to calculate incremental net monetary benefit (ΔNMB). Regression analyses were performed with these variables as dependent variables and PM intervention characteristics as independent variables. Random intercepts were used to cluster studies according to country.

RESULTS

Of 4774 studies reviewed, 128 were selected, providing cost-effectiveness data for 279 PM interventions. Most studies were set in the United States (48%) and the United Kingdom (16%) and adopted a healthcare perspective (82%). Cancer treatments (60%) and pharmaceutical interventions (72%) occurred frequently. Prognostic tests (19%) and tests to identify (non)responders (37%) were least and most common, respectively. Industry sponsorship occurred in 32%. Median ΔQALYs, Δcosts, and ΔNMB per individual were 0.03, Int$575, and Int$18, respectively. We found large heterogeneity in cost-effectiveness. Regression analysis showed that gene therapies were associated with higher ΔQALYs than other interventions. PM interventions for neoplasms brought higher ΔNMB than PM interventions for other conditions. Nonetheless, average ΔNMB in the 'neoplasm' group was found to be negative.

CONCLUSIONS

PM brings improvements in health but often at a high cost, resulting in 0 to negative ΔNMB on average. Pricing policies may be needed to reduce the costs of interventions with negative ΔNMB.

Capturing the value of vaccination within health technology assessment and health economics: Literature review and novel conceptual framework

BACKGROUND

Vaccination provides significant health gains to individuals and society and can potentially improve health equity, healthcare systems and national economies. Policy decisions, however, are rarely informed by comprehensive economic evaluations (EE) including vaccination's wide-ranging value. The objective of this analysis was to focus on health technology assessment systems to identify relevant value concepts in order to improve current EE of non-pandemic vaccines.

METHODS

Following a literature review, a novel Value of Vaccination (VoV) framework was developed with experts in vaccine EE from developed countries with established health technology assessment systems.

RESULTS

Forty-four studies presenting value frameworks or concepts applicable to vaccination were included. Eighteen unique value concepts relevant to EE were identified and defined. These were categorised within the VoV framework using three dimensions, moving from a narrow payer perspective to a more expansive and societal perspective. The dimensions were: (I) conventional payer perspective concepts (e.g., health gains in vaccinees, direct medical costs); (II) conventional societal perspective concepts (e.g., indirect health/economic gains to caregivers/households, productivity in vaccinees); and (III) novel societal concepts (e.g., financial risk protection, peace of mind, societal health gains, healthcare systems security, political stability, social equity and macroeconomic gains). While good quality evidence and methods are available to support concepts in Dimensions I and II, further work is needed to generate the required evidence for vaccination impact on Dimension III concepts.

CONCLUSIONS

The devastating effect on nations of the COVID-19 pandemic has helped to highlight the potential far-reaching benefits that many vaccination programmes can offer. This VoV framework is particularly relevant to policy decisions considering EE, and the potential future expansion of non-pandemic vaccination value considerations. The framework helps to understand and compare current value considerations across countries and payer versus societal perspectives. It provides decision-makers with a transparent and logical path to broaden consideration of VoV in EE.

The History and Future of the "ISPOR Value Flower": Addressing Limitations of Conventional Cost-Effectiveness Analysis

OBJECTIVES

Since its publication as part of the 2018 ISPOR Special Task Force (STF) on US Value Assessments, the "ISPOR value flower," with its petals highlighting elements that may be overlooked or underappreciated in conventional drug value assessments, has been discussed and debated. We review the history of the value flower, describe recent developments, and consider implications for future value assessments.

METHODS

We discuss various antecedents to the value flower, as well as conceptual and empirical articles published in the past 4 years.

RESULTS

Since the publication of the ISPOR STF report, researchers have provided more rigorous theoretical and mathematical foundations for certain novel value elements (eg, severity of illness, value of insurance, value of hope) through "generalized risk-adjusted cost-effectiveness analysis," which incorporates risk aversion in people's preferences and uncertainty in treatment outcomes. Empirical estimates are also emerging to support key elements, such as insurance value, real option value, value of hope, and value of knowing. Although health technology assessment bodies have applied or are considering certain elements (eg, severity modifiers to cost-effectiveness thresholds), other elements have yet to gain traction.

CONCLUSIONS

Five years after the STF began its work, the development of novel value measures continues to evolve. Although it is encouraging to see supporting empirical studies emerging, more are needed. Additional efforts are also needed to illustrate how the estimates can be used in the deliberative processes that are integral to health technology assessments.

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.