Estimating the Economically Justifiable Price of Limited-Duration Treatment with Donanemab for Early Symptomatic Alzheimer's Disease in the United States.

INTRODUCTION: The goal of this economic model is to estimate an economically justifiable price (EJP) for using donanemab for the treatment of early symptomatic Alzheimer's disease (AD) in the United States based on clinical data from the phase 3 TRAILBLAZER-ALZ 2 trial (NCT04437511). METHODS: We adapted an AD Markov state-transition model developed by the Institute for Clinical and Economic Review to estimate the EJP for donanemab at different willingness-to-pay (WTP) thresholds from the health care system perspective and the societal perspective as co-base cases. RESULTS: Assuming a WTP threshold of $150,000 per quality-adjusted life-year (QALY) gained, the model estimates a 1-year (13-dose) EJP for donanemab of $80,538 from the health care system perspective and $91,126 from the societal perspective; at a WTP threshold of $100,000 per QALY gained, the model estimates a 1-year (13-dose) EJP for donanemab of $44,691 from the health care system perspective and $55,419 from the societal perspective. Mean total treatment costs per patient at the $150,000 per QALY gained EJP derived from the health care system perspective were estimated at $77,812 based on the average number of doses of donanemab patients received in the co-base case analysis. One-way sensitivity analysis (OWSA) indicated that treatment efficacy, disease severity at the time of treatment initiation, and duration of treatment effect were the main drivers of the potential EJP. CONCLUSIONS: Results from this modeling simulation informed by the TRAILBLAZER-ALZ 2 study support an EJP for limited-duration treatment with donanemab that exceeds per-dose list prices for currently available amyloid-targeting therapies, implying potentially lower lifetime costs and better value for money.

Does Real Option Value Influence Oncologists' Treatment Recommendations? A Survey of US Oncologists.

OBJECTIVES: Survival benefit from anticancer treatments, even if modest, improves a patient's chances of accessing future innovations, thereby creating real option value. There is no empirical evidence on the impact of potential future innovations on oncologists' treatment recommendations. METHODS: We conducted a national online survey of practicing medical and hematological oncologists. We presented a hypothetical metastatic cancer patient with median survival of 6 months under 4 decision-making scenarios with varying expected efficacy and time to arrival of future innovations. We assessed the likelihood of discussing future innovations with their patients and the likelihood that future innovations would influence their current treatment recommendation, as well as factors associated with these 2 outcomes using multivariate logistic regressions. RESULTS: A total of 201 oncologists completed the survey. When future innovations were expected to improve survival by 6 months and be available in 6 months, 76% of oncologists were likely or very likely to discuss the innovations with their patients, and 68% reported they would influence their current treatment recommendations. A 1-month increase in the expected survival improvement of future innovation was associated with a 1.17 greater odds (95% CI 1.1-1.25) of reporting likely or very likely to discuss future innovations with their patients, whereas a 1-month increase in the expected time to arrival was associated with a 0.91 lower odds (95% CI 0.88-0.94). CONCLUSIONS: Given that potential future innovations seem to influence oncologists' treatments recommendations, evidence to inform clinical guidelines and value assessments should consider data on real option value impacts to support informed treatment decision making.

Capturing the Value of Vaccination within Health Technology Assessment and Health Economics-Practical Considerations for Expanding Valuation by Including Key Concepts.

Following the development of a value of vaccination (VoV) framework for health technology assessment/cost-effectiveness analysis (HTA/CEA), and identification of three vaccination benefits for near-term inclusion in HTA/CEA, this final paper provides decision makers with methods and examples to consider benefits of health systems strengthening (HSS), equity, and macroeconomic gains. Expert working groups, targeted literature reviews, and case studies were used. Opportunity cost methods were applied for HSS benefits of rotavirus vaccination. Vaccination, with HSS benefits included, reduced the incremental cost-effectiveness ratio (ICER) by 1.4-50.5% (to GBP 11,552-GBP 23,016) depending on alternative conditions considered. Distributional CEA was applied for health equity benefits of meningococcal vaccination. Nearly 80% of prevented cases were among the three most deprived groups. Vaccination, with equity benefits included, reduced the ICER by 22-56% (to GBP 7014-GBP 12,460), depending on equity parameters. Macroeconomic models may inform HTA deliberative processes (e.g., disease impact on the labour force and the wider economy), or macroeconomic outcomes may be assessed for individuals in CEAs (e.g., impact on non-health consumption, leisure time, and income). These case studies show how to assess broader vaccination benefits in current HTA/CEA, providing decision makers with more accurate and complete VoV assessments. More work is needed to refine inputs and methods, especially for macroeconomic gains.

Estimating the Allocation of the Economic Value Generated by Utilization of All-Oral Direct-Acting Antivirals for Hepatitis C in the United States, 2015 to 2019.

OBJECTIVES: Between 2013 to 2019, several all-oral direct-acting antivirals (DAAs) were launched with the potential to cure patients with hepatitis C virus (HCV). They generated economic value in terms of the health gains for patients and cost-savings for the US healthcare system. We estimated the share of this value allocated to 4 manufacturers vs society. METHODS: For 2015 to 2019, we estimated the incremental impact of DAAs on HCV health outcomes and costs. We used the Center for Disease Analysis Foundation Polaris Observatory database to estimate utilization. Per-patient projections of lifetime quality-adjusted life-years (QALYs) gained and medical costs avoided were based on a standard 9-state HCV disease-progression model for DAA treatment vs alternatives. Annual QALY gains were valued at $114 000 per QALY. Outcomes and costs were discounted at 3%. Estimated revenues were based on reported sales. RESULTS: An estimated 1 080 000 patients received DAAs: 81.5% would not have received the pre-DAA standard of care. On average, these patients were projected to gain 4.4 QALYs and save $104 400 in lifetime healthcare costs, generating $531.8 billion in value. Those who would have received treatment gained 1.7 QALYs and saved $41 500 in lifetime costs, generating $47.4 billion in economic value. As treatment costs fell nearly 75%, the 4 manufacturers reported $37.4 billion from DAA sales-an allocation of 6.5% of the total value. CONCLUSIONS: The significant majority (∼90%) of the economic value of curing HCV with DAAs were health benefits to patients and net cost-savings to society. DAA manufacturers received a minority share (6.5%) of the aggregate economic value generated.

New Vaccine Platforms-Novel Dimensions of Economic and Societal Value and Their Measurement.

The COVID-19 pandemic's dramatic impact has been a vivid reminder that vaccines-especially in the context of infectious respiratory viruses-provide enormous societal value, well beyond the healthcare system perspective which anchors most Health Technology Assessment (HTA) and National Immunization Technical Advisory Group (NITAG) evaluation frameworks. Furthermore, the development of modified ribonucleic acid-based (mRNA-based) and nanoparticle vaccine technologies has brought into focus several new value drivers previously absent from the discourse on vaccines as public health interventions such as increased vaccine adaptation capabilities, the improved ability to develop combination vaccines, and more efficient vaccine manufacturing and production processes. We review these novel value dimensions and discuss how they might be measured and incorporated within existing value frameworks using existing methods. To realize the full potential of next-generation vaccine platforms and ensure their widespread availability across populations and health systems, it is important that value frameworks utilized by HTAs and NITAGs properly reflect the full range of benefits for population health and well-being and cost efficiencies that these new vaccines platforms provide.

The evolving value assessment of cancer therapies: Results from a modified Delphi study.

The move toward early detection and treatment of cancer presents challenges for value assessment using traditional endpoints. Current cancer management rarely considers the full economic and societal benefits of therapies. Our study used a modified Delphi process to develop principles for defining and assessing value of cancer therapies that aligns with the current trajectory of oncology research and reflects broader notions of value. 24 experts participated in consensus-building activities across 5 months (16 took part in structured interactions, including a survey, plenary sessions, interviews, and off-line discussions, while 8 participated in interviews). Discussion focused on: 1) which oncology-relevant endpoints should be used for assessing treatments for early-stage cancer and access decisions for early-stage treatments, and 2) the importance of additional value components and how these can be integrated in value assessments. The expert group reached consensus on 4 principles in relation to the first area (consider oncology-relevant endpoints other than overall survival; build evidence for endpoints that provide earlier indication of efficacy; develop evidence for the next generation of predictive measures; use managed entry agreements supported by ongoing evidence collection to address decision-maker evidence needs) and 3 principles in relation to the second (routinely use patient reported outcomes in value assessments; assess broad economic impact of new medicines; consider other value aspects of relevance to patients and society).

Evidence Synthesis and Linkage for Modelling the Cost-Effectiveness of Diagnostic Tests: Preliminary Good Practice Recommendations.

OBJECTIVES: To develop preliminary good practice recommendations for synthesising and linking evidence of treatment effectiveness when modelling the cost-effectiveness of diagnostic tests. METHODS: We conducted a targeted review of guidance from key Health Technology Assessment (HTA) bodies to summarise current recommendations on synthesis and linkage of treatment effectiveness evidence within economic evaluations of diagnostic tests. We then focused on a specific case study, the cost-effectiveness of troponin for the diagnosis of myocardial infarction, and reviewed the approach taken to synthesise and link treatment effectiveness evidence in different modelling studies. RESULTS: The Australian and UK HTA bodies provided advice for synthesising and linking treatment effectiveness in diagnostic models, acknowledging that linking test results to treatment options and their outcomes is common. Across all reviewed models for the case study, uniform test-directed treatment decision making was assumed, i.e., all those who tested positive were treated. Treatment outcome data from a variety of sources, including expert opinion, were utilised for linked clinical outcomes. Preliminary good practice recommendations for data identification, integration and description are proposed. CONCLUSION: Modelling the cost-effectiveness of diagnostic tests poses unique challenges in linking evidence on test accuracy to treatment effectiveness data to understand how a test impacts patient outcomes and costs. Upfront consideration of how a test and its results will likely be incorporated into patient diagnostic pathways is key to exploring the optimal design of such models. We propose some preliminary good practice recommendations to improve the quality of cost-effectiveness evaluations of diagnostics tests going forward.

Incorporating Real Option Value in Valuing Innovation: A Way Forward.

BACKGROUND: Considerable progress has been made in defining and measuring the real option value (ROV) of medical technologies. However, questions remain on how to estimate (1) ROV outside of life-extending oncology interventions; (2) the impact of ROV on costs and cost effectiveness; and (3) potential interactions between ROV and other elements of value. METHODS: We developed a 'minimal modeling' approach for estimating the size of ROV that does not require constructing a full, formal cost-effectiveness model. We proposed a qualitative approach to assessing the level of uncertainty in the ROV estimate. We examined the potential impact of ROV on the incremental cost-effectiveness ratio as well as on the potential interactions between ROV and other elements of value. Lastly, we developed and presented a 15-item checklist for reporting ROV in value assessment. RESULTS: The minimal modeling approach uses estimates on the efficacy of current treatment and potential future innovation, as well as success rate and length of new treatment development, and can be applied to all types of ROV across disease areas. ROV may interact with the conventional value, value of hope, productivity effects, and insurance value. The impact of ROV on cost effectiveness can be evaluated via threshold analysis. CONCLUSION: The minimal modeling approach and the checklist developed in this paper simplifies and standardizes the estimation and reporting of ROV in value assessment. Systematically including and reporting ROV in value assessment will minimize bias and improve transparency, which will help improve the credibility of ROV research and acceptance by stakeholders.

Evaluating Policies of Expanding Versus Restricting First-Line Treatment Choices: A Cost-Effectiveness Analysis Framework.

OBJECTIVES: Healthcare payers often implement coverage policies that restrict the utilization of costly new first-line treatments. Cost-effectiveness analysis can be conducted to inform these decisions by comparing the new treatment with an existing one. However, this approach may overlook important factors such as treatment effect heterogeneity and endogenous treatment selection, policy implementation costs, and diverse patient preferences across multiple treatment options. We aimed to develop a cost-effectiveness analysis framework that considers these real-world factors, facilitating the evaluation of alternative policies related to expanding or restricting first-line treatment choices. METHODS: We introduced a metric of incremental cost-effectiveness ratio (ICER) that compares an expanded choice set (CS) including the new first-line treatment with a restricted CS excluding the new treatment. ICER(CS) accounts for treatment selection influenced by heterogeneous treatment effects and policy implementation costs. We examined a basic scenario with 2 standard first-line treatment choices and a more realistic scenario involving diverse preferences toward multiple choices. To illustrate the framework, we conducted a retrospective evaluation of including versus excluding abiraterone acetate plus prednisone (AAP) (androgen deprivation therapy [ADT] + AAP) as a first-line treatment for metastatic hormone-sensitive prostate cancer. RESULTS: The traditional ICERs for ADT + AAP versus ADT alone and ADT+ docetaxel were $104 269 and $206 324/quality-adjusted life-year, respectively. The ICER(CS) for comparing an expanded CS with ADT + AAP with a restricted CS without ADT + AAP was $123 179/quality-adjusted life-year. CONCLUSIONS: The proposed framework provides decision makers with policy-relevant tools, enabling them to assess the cost-effectiveness of alternative policies of expanding versus restricting patients' and physicians' first-line treatment choices.

Is the price right? Paying for value today to get more value tomorrow.

BACKGROUND: Contemporary debates about drug pricing feature several widely held misconceptions, including the relationship between incentives and innovation, the proportion of total healthcare spending on pharmaceuticals, and whether the economic evaluation of a medicine can be influenced by things other than clinical efficacy. MAIN BODY: All citizens should have access to timely, equitable, and cost-effective care covered by public funds, private insurance, or a combination of both. Better managing the collective burden of diseases borne by today's and future generations depends in part on developing better technologies, including better medicines. As in any innovative industry, the expectation of adequate financial returns incentivizes innovators and their investors to develop new medicines. Estimating expected returns requires that they forecast revenues, based on the future price trajectory and volume of use over time. How market participants decide what price to set or accept can be complicated, and some observers and stakeholders want to confirm whether the net prices society pays for novel medicines, whether as a reward for past innovation or an incentive for future innovation, are commensurate with those medicines' incremental value. But we must also ask "value to whom?"; medicines not only bring immediate clinical benefits to patients treated today, but also can provide a broad spectrum of short- and long-term benefits to patients, their families, and society. Spending across all facets of healthcare has grown over the last 25 years, but both inpatient and outpatient spending has outpaced drug spending growth even as our drug armamentarium is constantly improving with safer and more effective medicines. In large part, this is because, unlike hospitals, drugs typically go generic, thus making room in our budgets for new and better ones, even as they often keep patients out of hospitals, driving further savings. CONCLUSION: A thorough evaluation of drug spending and value can help to promote a better allocation of healthcare resources for both the healthy and the sick, both of whom must pay for healthcare. Taking a holistic approach to assessing drug value makes it clear that a branded drug's value to a patient is often only a small fraction of the drug's total value to society. Societal value merits consideration when determining whether and how to make a medicine affordable and accessible to patients: a drug that is worth its price to society should not be rendered inaccessible to ill patients by imposing high out-of-pocket costs or restricting coverage based on narrow health technology assessments (HTAs). Furthermore, recognizing the total societal cost of un- or undertreated conditions is crucial to gaining a thorough understanding of what guides the biomedical innovation ecosystem to create value for society. It would be unwise to discourage the development of new solutions without first appreciating the cost of leaving the problems unsolved.

Estimating the Lifetime Medical Cost Burden of an Allogeneic Hematopoietic Cell Transplantation Patient.

Allogeneic hematopoietic cell transplantation (allo-HCT) has the potential for curative outcomes for a variety of hematologic malignancies. Current allo-HCT studies often describe the outcomes and costs in the near term; however, research on the lifetime economic burden post-allo-HCT remains limited. This study was conducted to estimate the average total lifetime direct medical costs of an allo-HCT patient and the potential net monetary savings from an alternative treatment associated with improved graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS). A disease-state model was constructed using a short-term decision tree and a long-term semi-Markov partitioned survival model to estimate the average per-patient lifetime cost and expected quality-adjusted life years (QALYs) for an allo-HCT patient from a US healthcare system perspective. Key clinical inputs included overall survival, GRFS, incidence of both acute and chronic GVHD, relapse of the primary disease, and infections. Cost results were reported as ranges based on varying the percentage of chronic GVHD patients that remained on treatment after 2 years (15% or 39%). Over a lifetime, the average per-patient medical cost of allo-HCT was estimated to range from $942,373 to $1,247,917. The majority of the costs were for chronic GVHD treatment (37% to 53%), followed by the allo-HCT procedure (15% to 19%). The expected lifetime QALYs of an allo-HCT patient were estimated as 4.7. Lifetime per-patient treatment costs often exceed $1,000,000 for allo-HCT patients. Innovative research efforts focused on the reduction or elimination of late complications, particularly chronic GVHD, may provide the greatest value to improved patient outcomes.

Distributional Cost-Effectiveness Analysis of Treatments for Non-Small Cell Lung Cancer: An Illustration of an Aggregate Analysis and its Key Drivers.

BACKGROUND AND OBJECTIVE: Distributional cost-effectiveness analysis (DCEA) facilitates quantitative assessments of how health effects and costs are distributed among population subgroups, and of potential trade-offs between health maximisation and equity. Implementation of DCEA is currently explored by the National Institute for Health and Care Excellence (NICE) in England. Recent research conducted an aggregate DCEA on a selection of NICE appraisals; however, significant questions remain regarding the impact of the characteristics of the patient population (size, distribution by the equity measure of interest) and methodologic choices on DCEA outcomes. Cancer is the indication most appraised by NICE, and the relationship between lung cancer incidence and socioeconomic status is well established. We aimed to conduct an aggregate DCEA of two non-small cell lung cancer (NSCLC) treatments recommended by NICE, and identify key drivers of the analysis. METHODS: Subgroups were defined according to socioeconomic deprivation. Data on health benefits, costs, and target populations were extracted from two NICE appraisals (atezolizumab versus docetaxel [second-line treatment following chemotherapy to represent a broad NSCLC population] and alectinib versus crizotinib [targeted first-line treatment to represent a rarer mutation-positive NSCLC population]). Data on disease incidence were derived from national statistics. Distributions of population health and health opportunity costs were taken from the literature. A societal welfare analysis was conducted to assess potential trade-offs between health maximisation and equity. Sensitivity analyses were conducted, varying a range of parameters. RESULTS: At an opportunity cost threshold of £30,000 per quality-adjusted life-year (QALY), alectinib improved both health and equity, thereby increasing societal welfare. Second-line atezolizumab involved a trade-off between improving health equity and maximising health; it improved societal welfare at an opportunity cost threshold of £50,000/QALY. Increasing the value of the opportunity cost threshold improved the equity impact. The equity impact and societal welfare impact were small, driven by the size of the patient population and per-patient net health benefit. Other key drivers were the inequality aversion parameters and the distribution of patients by socioeconomic group; skewing the distribution to the most (least) deprived quintile improved (reduced) equity gains. CONCLUSION: Using two illustrative examples and varying model parameters to simulate alternative decision problems, this study suggests that key drivers of an aggregate DCEA are the opportunity cost threshold, the characteristics of the patient population, and the level of inequality aversion. These drivers raise important questions in terms of the implications for decision making. Further research is warranted to examine the value of the opportunity cost threshold, capture the public's views on unfair differences in health, and estimate robust distributional weights incorporating the public's preferences. Finally, guidance from health technology assessment organisations, such as NICE, is needed regarding methods for DCEA construction and how they would interpret and incorporate those results in their decision making.

Assessing the potential cost-effectiveness of centralised versus point-of-care testing for hepatitis C virus in Pakistan: a model-based comparison.

OBJECTIVES: Pakistan has a hepatitis C virus (HCV) infection prevalence of 6%-9% and aims to achieve World Health Organisation (WHO) targets for elimination of HCV by the year 2030. We aim to evaluate the potential cost-effectiveness of a reference laboratory-based (centralised laboratory testing; CEN) confirmatory testing approach versus a molecular near-patient point-of-care (POC) confirmatory approach to screen the general population for HCV in Pakistan. STUDY DESIGN: We used a decision tree-analytic model from a governmental (formal healthcare sector) perspective. STUDY SETTING: Individuals were assumed to be initially screened with an anti-HCV test at home, followed by POC nucleic acid test (NAT) at nearby district hospitals or followed by NAT at centralised laboratories. PARTICIPANTS: We included the general testing population for chronic HCV in Pakistan. INTERVENTION: Screening with an anti-HCV antibody test (Anti-HCV) followed by either POC NAT (Anti-HCV-POC), or reference laboratory NAT (Anti-HCV-CEN), was compared, using data from published literature and the Pakistan Ministry of Health. MEASURES: Outcome measures included: number of HCV infections identified per year, percentage of individuals correctly classified, total costs, average costs per individual tested, and cost-effectiveness (assessed as cost per additional HCV infection identified). Sensitivity analysis was also performed. RESULTS: At a national level (25 million annual screening tests), the Anti-HCV-CEN strategy would identify 142 406 more HCV infections in 1 year and increase correct classification of individuals by 0.57% compared with the Anti-HCV-POC strategy. The total annual cost of HCV testing was reduced using the Anti-HCV-CEN strategy by US$7.68 million (US$0.31/person). Thus, incrementally, the Anti-HCV-CEN strategy costs less and identifies more HCV infections than Anti-HCV-POC. The incremental difference in HCV infections identified was most sensitive to the probability of loss to follow-up (for POC confirmatory NAT). CONCLUSIONS: Anti-HCV-CEN would provide the best value for money when scaling up HCV testing in Pakistan.

A review of economic issues for gene-targeted therapies: Value, affordability, and access.

The National Center for Advancing Translational Sciences' virtual 2021 conference on gene-targeted therapies (GTTs) encouraged multidisciplinary dialogue on a wide range of GTT topic areas. Each of three parallel working groups included social scientists and clinical scientists, and the three major sessions included a presentation on economic issues related to their focus area. These experts also coordinated their efforts across the three groups. The economics-related presentations covered three areas with some overlap: (1) value assessment, uncertainty, and dynamic efficiency; (2) affordability, pricing, and financing; and (3) evidence generation, coverage, and access. This article provides a synopsis of three presentations, some of their key recommendations, and an update on related developments in the past year. The key high-level findings are that GTTs present unique data and policy challenges, and that existing regulatory, health technology assessment, as well as payment and financing systems will need to adapt. But these adjustments can build on our existing foundation of regulatory and incentive systems for innovation, and much can be done to accelerate progress in GTTs. Given the substantial unmet medical need that exists for these oft-neglected patients suffering from rare diseases, it would be a tragedy to not leverage these exciting scientific advances in GTTs.

Estimating the Potential Economic Impact of Tissue Valve Replacement for Heart Valve Disease in China: Patient-Level and Population-Level Cost-Benefit Simulation Analyses.

OBJECTIVES: This study seeks to estimate the potential societal economic impact of treating patients with heart valve disease (HVD) in China with surgical tissue valve replacement versus mechanical valves. METHODS: This societal economic cost-benefit evaluation is based on an individual simulation model for subgroups of patients with HVD that is also aggregated to a macrosocietal model. The individual simulation model was developed to estimate the likely economic impact of surgical aortic valve replacement (SAVR) with tissue versus mechanical valves for different subgroups among all eligible patients with HVD over their remaining lifetimes. Clinical inputs were informed by health claims database analysis, expert clinical opinion, and published literature. Epidemiological inputs and demographic inputs were sourced from the published literature and the China Statistical Yearbook 2020. Health gains were valued at 3 times the average national income. RESULTS: Projected total lifetime economic gains were greater for patients receiving tissue valves. Costs were reported in 2021 US dollars. The average lifetime net economic gain for tissue valve patients was $51 736 (20.0% more than for mechanical valve patients). Increasing the use of tissue valves to 50% among all eligible patients with HVD would provide aggregate long-term economic gains of $167 billion during their remaining lifetimes. The economic gains from greater tissue valve use were due to avoiding anticoagulation monitoring costs, improved quality of life, and greater post-SAVR labor force participation. CONCLUSION: Increased use of tissue valves versus mechanical values in SAVR procedures in China would be likely to generate a substantial societal economic gain.

Value-Based Pricing for Patent-Protected Medicines Over the Product Life Cycle: Pricing Anomalies in the "Age of Cures" and Their Implications for Dynamic Efficiency.

OBJECTIVES: Conventional cost-effectiveness analysis (CEA) for the value-based pricing of new medicines largely ignores the implications of limited market exclusivity (ie, patent-protection periods plus any exclusivity granted by regulators). This paper explores the implications of this methodological shortcoming, which produces several pricing anomalies with potentially unintended effects on research and development (R&D) incentives. METHODS: We illustrate these implications by comparing 4 stylized examples of increasing complexity, from short-term cures for acute conditions to long-term cures for rare, health-catastrophic conditions. RESULTS: (1) Conventional-CEA will project a different result than an adjusted CEA that considers generic or biosimilar entry; (2) free and flexible pricing of long-term treatments (eg, statins for hypercholesterolemia) or repeated-dose cures (eg, insulin for type 1 diabetes) for chronic conditions will likely result in predictable price increases at the end of the exclusivity period that may be perceived as unjustified or unsupported; and (3) one-time administration "cures" (eg, gene therapy for spinal muscular atrophy) have the potential to allocate a large share of the social surplus to the manufacturer over the product lifetime, which may or may not be dynamically efficient per se, but may also inadvertently disadvantage the development of valuable long-term treatments or repeated-dose cures for chronic conditions. CONCLUSIONS: We highlight the need for additional research on long-term solutions to these issues that would aim to promote dynamically efficient global R&D. More work is needed on the following: (1) relationships between social surplus allocation and the amount and composition of global R&D, as we may be as likely to be encouraging excessive R&D in some areas as to be undersupplying it in others; and (2) relating the size of the surplus reward to R&D cost and, thus, the return on investment.

Value Insider Season 1 Episode 5: What Other Aspects of Value May Be Relevant? (Societal Impact) [Podcast].

What other aspects of value may be relevant? In this episode of the Value Insider podcast, host Mike Chambers speaks with Prof. Lou Garrison about the societal perspective on value of healthcare interventions. Prof. Garrison is Professor Emeritus in The Comparative Health Outcomes, Policy, and Economics institute (CHOICE) in the School of Pharmacy at the University of Washington. Lou is past president of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and he is currently co-chair of its Policy Outlook Committee. Going beyond the "conventional" elements of value assessment, Prof. Garrison highlights which additional impacts may be at play. He shares his concept of the "Value Flower", explaining elements such as insurance value and scientific spill-over.