Achieving dynamic efficiency in pharmaceutical innovation: Identifying the optimal share of value and payments required.

It has been argued that cost-effectiveness analysis of branded pharmaceuticals only considers static efficiency, neglects dynamic effects and undermines incentives for socially valuable innovation. We present a framework for designing pharmaceutical pricing policy to achieve dynamic efficiency. We develop a coherent framework that identifies the long-term static and dynamic benefits and costs of offering manufacturers different levels of reward. The share of value that would maximise long-term population health depends on how the quantity and quality of innovation responds to payment. Using evidence of the response of innovation to payment, the optimal share of value of new pharmaceuticals to offer to manufacturers is roughly 20% (range: 6%-51%). Reanalysis of a sample of NICE technology appraisals suggests that, in most cases, the share of value offered to manufacturers and the price premium paid by the English NHS were too high. In the UK, application of optimal shares would offer considerable benefits under both a public health objective and a broader view of social welfare. We illustrate how an optimal share of value can be delivered through a range of payment mechanisms including indirect price regulation via the use of different approval norms by an HTA body.

A qualitative study on the feasibility and acceptability of institutionalizing health technology assessment in Malawi.

OBJECTIVE: The objective of this study was to assess the feasibility and acceptability of institutionalizing Health Technology Assessment (HTA) in Malawi. METHODS: This study employed a document review and qualitative research methods, to understand the status of HTA in Malawi. This was complemented by a review of the status and nature of HTA institutionalization in selected countries.Qualitative research employed a Focus Group Discussion (FGD ) with 7 participants, and Key Informant Interviews (KIIs) with12 informants selected based on their knowledge and expertise in policy processes related to HTA in Malawi.Data extracted from the literature was organized in Microsoft Excel, categorized according to thematic areas and analyzed using a literature review framework. Qualitative data from KIIs and the FGD was analyzed using a thematic content analysis approach. RESULTS: Some HTA processes exist and are executed through three structures namely: Ministry of Health Senior Management Team, Technical Working Groups, and Pharmacy and Medicines Regulatory Authority (PMRA) with varyingdegrees of effectiveness.The main limitations of current HTA mechanisms include limited evidence use, lack of a standardized framework for technology adoption, donor pressure, lack of resources for the HTA process and technology acquisition, laws and practices that undermine cost-effectiveness considerations. KII and FGD results showed overwhelming demand for strengthening HTA in Malawi, with a stronger preference for strengthening coordination and capacity of existing entities and structures. CONCLUSION: The study has shown that HTA institutionalization is acceptable and feasible in Malawi. However, the current committee based processes are suboptimal to improve efficiency due to lack of a structured framework. A structured HTA framework has the potential to improve processes in pharmaceuticals and medical technologies decision-making.In the short to medium term, HTA capacity building should focus on generating demand and increasing capacity in cost-effectiveness assessments. Country-specific assessments should precede HTA institutionalization as well as recommendations for new technology adoptions.

Ideas About Resourcing Health Care in the United States: Can Economic Evaluation Achieve Meaningful Use?

The United States is one of the few high-income countries not to apply economic evaluation routinely to health care decision making on a national level, yet it excels at spending least efficiently on health care. In the interest of continuing to develop new solutions to curb spending on health care and reduce waste in the United States, perhaps now is an important moment to reconsider the benefits of economic evaluation and the barriers that must be overcome to have it emerge as a solution for health care institutions and the patients they serve. This article offers several distinct considerations to make economic evaluation methods (such as cost-effectiveness analysis) an effective component of value-based decision making in the United States. These considerations include overcoming the barriers presented by opportunity costs, spending on health care services versus biomedical technologies, phasing out low-value care, using value of information to prioritize resources, and determining what to do with the quality-adjusted life-year. These issues need to be addressed to achieve a collective purpose for economic evaluation at state and national levels.

Using Economic Evaluation to Inform Responses to the Opioid Epidemic in the United States: Challenges and Suggestions for Future Research.

Background: Several aspects of the opioid epidemic and of public health care organization in the United States (US) make the conduct of economic evaluation and the design of policies to respond to this crisis particularly challenging. Objectives: This commentary offers suggestions for how economic evaluation may address and overcome four key features of the opioid epidemic: 1) its magnitude and geographical distribution, 2) its intersection with multiple epidemics, 3) its rapidly changing dynamics, 4) its multi-sectoral causes and consequences. Results: We first offer pragmatic suggestions to address the difficulties in delivering a coordinated response given the fragmented nature of health care in the US. In view of the broad suite of responses required to address opioid use disorder and its associated comorbidities, we highlight the need for economic evaluations which consider interventions throughout the continuum of care (i.e. primary, secondary and tertiary levels of prevention). We examine how the use of predictive modelling alongside economic evaluation might be adopted to address the rapidly evolving situation affecting distinct populations and geographic areas and encourage investments in epidemic preparedness. Finally, we propose methods to capture the interdependence of various sectors of government affected by the opioid crisis in economic evaluations to ensure optimal levels of investment towards a comprehensive response. Conclusions: The opioid epidemic in the US represents an unprecedented public health challenge, but sound epidemiological modelling and economic analysis can help to guide use of limited resources committed to addressing it in ways that can have greatest impact in limiting its adverse consequences.

Antimicrobial Resistance: Is Health Technology Assessment Part of the Solution or Part of the Problem?

Antimicrobial resistance is a serious challenge to the success and sustainability of our healthcare systems. There has been increasing policy attention given to antimicrobial resistance in the last few years, and increased amounts of funding have been channeled into funding for research and development of antimicrobial agents. Nevertheless, manufacturers doubt whether there will be a market for new antimicrobial technologies sufficient to enable them to recoup their investment. Health technology assessment (HTA) has a critical role in creating confidence that if valuable technologies can be developed they will be reimbursed at a level that captures their true value. We identify 3 deficiencies of current HTA processes for appraising antimicrobial agents: a methods-centric approach rather than problem-centric approach for dealing with new challenges, a lack of tools for thinking about changing patterns of infection, and the absence of an approach to epidemiological risks. We argue that, to play their role more effectively, HTA agencies need to broaden their methodological tool kit, design and communicate their analysis to a wider set of users, and incorporate long-term policy goals, such as containing resistance, as part of their evaluation criteria alongside immediate health gains.

Estimating the shares of the value of branded pharmaceuticals accruing to manufacturers and to patients served by health systems.

Previous studies have estimated that patients served by health systems accrue 59-98% of the value generated by new pharmaceuticals. This has led to questions about whether sufficient returns accrue to manufacturers to incentivize socially optimal levels of R&D. These studies have not, however, fully reflected the health opportunity costs imposed by payments for branded pharmaceuticals. We present a framework for estimating how the value generated by new branded pharmaceuticals is shared. We quantify value in net health effects and account for benefits and health opportunity costs in the patent period and post-patent period when generic/biosimilar products become available. We apply the framework to 12 National Institute for Health and Care Excellence appraisals and show that realized net health effects range from losses of 160%, to gains of 94%, of the potential net health benefits available. In many cases, even in the long run, the benefits of new medicines are not sufficient to offset the opportunity costs of payments to manufacturers, and approval is expected to reduce population health. This cannot be dynamically efficient as it incentivizes future innovation at prices which will also reduce population health. Further work should consider how to reflect these findings in reimbursement policies.

Distributional cost effectiveness analysis of West Yorkshire low emission zone policies.

Alternative strategies can reduce road vehicle emissions, with differential effects on exposure across population groups. We compare alternative strategies in West Yorkshire using a framework for economic evaluation that considers multiple perspectives and that takes account of the distribution of health outcomes. Exposure to pollutants by area is converted, via dose response relationships, into disease averted. Health benefits and National Health Service costs from diseases are estimated conditional on population demographics and index of multiple deprivation. The net health benefits from alternative strategies are expressed as distributions of quality-adjusted life expectancy (QALE), which are compared using dominance criteria and societal aversion to health inequality. Net production is estimated from intervention costs and the effects of health improvement on production and consumption. Social care outcomes are estimated from health improvement among care recipients and changes in care expenditure. A switch to less polluting private vehicles is dominant in terms of the distribution of QALE and social care outcomes but not consumption. Inclusion of health inequality aversion alters the rank order compared with prioritisation on health maximisation. The results were sensitive to the magnitude of health opportunity costs, the level of inequality aversion, and the proportion of intervention cost that generates health opportunity cost.

The Use of MCDA in HTA: Great Potential, but More Effort Needed.

The potential for multi-criteria decision analysis (MCDA) to support health technology assessment (HTA) has been much discussed, and various HTA agencies are piloting or applying MCDA. Alongside these developments, good practice guidelines for the application of MCDA in health care have been developed. An assessment of current applications of MCDA to HTA in light of good practice guidelines reveals, however, that many have methodologic flaws that undermine their usefulness. Three challenges are considered: the use of additive models, a lack of connection between criteria scales and weights, and the use of MCDA in economic evaluation. More attention needs to be paid to MCDA good practice by researchers, journal editors, and decision makers and further methodologic developments are required if MCDA is to achieve its potential to support HTA.

Decision uncertainty and value of further research: a case-study in fenestrated endovascular aneurysm repair for complex abdominal aortic aneurysms.

BACKGROUND: Fenestrated endovascular aneurysm repair (fEVAR) is a new approach for complex abdominal aortic aneurysms, limited to a few specialist centers, with limited evidence base. We developed a cost-effectiveness decision model of fEVAR compared to open surgical repair (OSR) to investigate the likely direction of costs and benefits and inform further research projects on this technology. METHODS: A systematic review with meta-analysis and a four-state Markov model were used to estimate the cost-effectiveness of fEVAR versus OSR. We used a recent coverage with evidence development framework to characterize the main sources of uncertainty and inform decisions about the type of further research that would be most worthwhile and feasible. RESULTS: Seven observational comparative studies were identified, of which four presented odds ratios adjusted for confounders. The odds ratios for operative mortality varied widely between studies. Assuming a central estimate of the odds ratio of 0.54 (95% CI 0.05-6.24), the decision model estimated that the incremental cost per quality adjusted life year (QALY) was £74,580/QALY with a probability of 9 and 16% of being cost-effective at standard cost-effectiveness thresholds of £20,000/QALY and £30,000/QALY, respectively. The Expected Value of Perfect Information over 10 years at a threshold of £20,000/QALY was £11.2 million. Operative mortality contributed to most of the uncertainty in the decision model. CONCLUSIONS: In the case of "maturing technologies", decision modelling indicates the likely direction of costs and benefits and guides the development of further research projects. In our analysis of fEVAR versus OSR, decision uncertainty, particularly around operative mortality, might be effectively resolved by a short-term RCT, or possibly a well-conducted comparative observational study. Decision makers may consider that a conditional coverage decision is warranted with assessments required to make this type of recommendation depending on local priorities and circumstances.

How to design the cost-effectiveness appraisal process of new healthcare technologies to maximise population health: A conceptual framework.

This paper presents a conceptual framework to analyse the design of the cost-effectiveness appraisal process of new healthcare technologies. The framework characterises the appraisal processes as a diagnostic test aimed at identifying cost-effective (true positive) and non-cost-effective (true negative) technologies. Using the framework, factors that influence the value of operating an appraisal process, in terms of net gain to population health, are identified. The framework is used to gain insight into current policy questions including (a) how rigorous the process should be, (b) who should have the burden of proof, and (c) how optimal design changes when allowing for appeals, price reductions, resubmissions, and re-evaluations. The paper demonstrates that there is no one optimal appraisal process and the process should be adapted over time and to the specific technology under assessment. Optimal design depends on country-specific features of (future) technologies, for example, effect, price, and size of the patient population, which might explain the difference in appraisal processes across countries. It is shown that burden of proof should be placed on the producers and that the impact of price reductions and patient access schemes on the producer's price setting should be considered when designing the appraisal process.

Social value and individual choice: The value of a choice-based decision-making process in a collectively funded health system.

Evidence about cost-effectiveness is increasingly being used to inform decisions about the funding of new technologies that are usually implemented as guidelines from centralized decision-making bodies. However, there is also an increasing recognition for the role of patients in determining their preferred treatment option. This paper presents a method to estimate the value of implementing a choice-based decision process using the cost-effectiveness analysis toolbox. This value is estimated for 3 alternative scenarios. First, it compares centralized decisions, based on population average cost-effectiveness, against a decision process based on patient choice. Second, it compares centralized decision based on patients' subgroups versus an individual choice-based decision process. Third, it compares a centralized process based on average cost-effectiveness against a choice-based process where patients choose according to a different measure of outcome to that used by the centralized decision maker. The methods are applied to a case study for the management of acute coronary syndrome. It is concluded that implementing a choice-based process of treatment allocation may be an option in collectively funded health systems. However, its value will depend on the specific health problem and the social values considered relevant to the health system.

Developing a Value Framework: The Need to Reflect the Opportunity Costs of Funding Decisions.

A growing number of health care systems internationally use formal economic evaluation methods to support health care funding decisions. Recently, a range of organizations have been advocating forms of analysis that have been termed "value frameworks." There has also been a push for analytical methods to reflect a fuller range of benefits of interventions through multicriteria decision analysis. A key principle that is invariably neglected in current and proposed frameworks is the need to reflect evidence on the opportunity costs that health systems face when making funding decisions. The mechanisms by which opportunity costs are realized vary depending on the system's financial arrangements, but they always mean that a decision to fund a specific intervention for a particular patient group has the potential to impose costs on others in terms of forgone benefits. These opportunity costs are rarely explicitly reflected in analysis to support decisions, but recent developments to quantify benefits forgone make more appropriate analyses feasible. Opportunity costs also need to be reflected in decisions if a broader range of attributes of benefit is considered, and opportunity costs are a key consideration in determining the appropriate level of total expenditure in a system. The principles by which opportunity costs can be reflected in analysis are illustrated in this article by using the example of the proposed methods for value-based pricing in the United Kingdom.

Characterising Uncertainty in the Assessment of Medical Devices and Determining Future Research Needs.

Decisions about the adoption of medical interventions are informed by evidence on their costs and effects. For a range of reasons, evidence relating to medical devices may be limited. The decision to adopt a device early in its life cycle when the evidence base is least mature may impact on the prospects of acquiring further evidence to reduce uncertainties. Equally, rejecting a device will result in no uptake in practice and hence no chance to learn about performance. Decision options such as 'only in research' or 'approval with research' can overcome these issues by allowing patients early access to promising new technologies while limiting the risks associated with making incorrect decisions until more evidence or learning is established. In this paper, we set out the issues relating to uncertainty and the value of research specific to devices: learning curve effects, incremental device innovation, investment and irrecoverable costs, and dynamic pricing. We show the circumstances under which an only in research or approval with research scheme may be an appropriate policy choice. We also consider how the value of additional research might be shared between the manufacturer and health sector to help inform who might reasonably be expected to conduct the research needed. © 2017 The Authors. Health Economics published by John Wiley & Sons, Ltd.

Identifying Key Drivers of the Impact of an HIV Cure Intervention in Sub-Saharan Africa.

BACKGROUND: It is unknown what properties would be required to make an intervention in low income countries that can eradicate or control human immunodeficiency virus (HIV) without antiretroviral therapy (ART) cost-effective. METHODS: We used a model of HIV and ART to investigate the effect of introducing an ART-free viral suppression intervention in 2022 using Zimbabwe as an example country. We assumed that the intervention (cost: $500) would be accessible for 90% of the population, be given to those receiving effective ART, have sufficient efficacy to allow ART interruption in 95%, with a rate of viral rebound of 5% per year in the first 3 months, and a 50% decline in rate with each successive year. RESULTS: An ART-free viral suppression intervention with these properties would result in >0.53 million disability-adjusted-life-years averted over 2022-2042, with a reduction in HIV program costs of $300 million (8.7% saving). An intervention of this efficacy costing anything up to $1400 is likely to be cost-effective in this setting. CONCLUSIONS: Interventions aimed at curing HIV infection have the potential to improve overall disease burden and to reduce costs. Given the effectiveness and cost of ART, such interventions would have to be inexpensive and highly effective.

Country-Level Cost-Effectiveness Thresholds: Initial Estimates and the Need for Further Research.

BACKGROUND: Cost-effectiveness analysis can guide policymakers in resource allocation decisions. It assesses whether the health gains offered by an intervention are large enough relative to any additional costs to warrant adoption. When there are constraints on the health care system's budget or ability to increase expenditures, additional costs imposed by interventions have an "opportunity cost" in terms of the health foregone because other interventions cannot be provided. Cost-effectiveness thresholds (CETs) are typically used to assess whether an intervention is worthwhile and should reflect health opportunity cost. Nevertheless, CETs used by some decision makers-such as the World Health Organization that suggested CETs of 1 to 3 times the gross domestic product (GDP) per capita-do not. OBJECTIVES: To estimate CETs based on opportunity cost for a wide range of countries. METHODS: We estimated CETs based on recent empirical estimates of opportunity cost (from the English National Health Service), estimates of the relationship between country GDP per capita and the value of a statistical life, and a series of explicit assumptions. RESULTS: CETs for Malawi (the country with the lowest income in the world), Cambodia (with borderline low/low-middle income), El Salvador (with borderline low-middle/upper-middle income), and Kazakhstan (with borderline high-middle/high income) were estimated to be $3 to $116 (1%-51% GDP per capita), $44 to $518 (4%-51%), $422 to $1967 (11%-51%), and $4485 to $8018 (32%-59%), respectively. CONCLUSIONS: To date, opportunity-cost-based CETs for low-/middle-income countries have not been available. Although uncertainty exists in the underlying assumptions, these estimates can provide a useful input to inform resource allocation decisions and suggest that routinely used CETs have been too high.

The Cost-Effectiveness of Bevacizumab in Advanced Ovarian Cancer Using Evidence from the ICON7 Trial.

BACKGROUND: Bevacizumab is used extensively in the treatment of cancer, including advanced ovarian cancer, for which results of the International Collaborative Ovarian Neoplasm (ICON) 7 trial have been recently reported. The National Institute for Health and Care Excellence's (NICE's) recent decision not to recommend bevacizumab for advanced ovarian cancer was not based on evidence related to the unlicensed lower dosage (7.5 mg/kg) of the drug despite its use in the English National Health Service (NHS) and the ICON7 trial. OBJECTIVE: To report on the findings of an analysis that considered whether the lower dose is cost-effective. METHODS: Cost-effectiveness analysis is assessed from the perspective of the English NHS and health outcomes expressed in terms of quality-adjusted life-years (QALYs). The analysis focuses on a clinically predefined high-risk subgroup of the ICON7 trial. The price at which the lower dose of bevacizumab could be considered cost-effective for the English NHS is presented for a range of scenarios to inform decisions about price negotiations by international health systems. RESULTS: In the base-case analysis, bevacizumab has an incremental cost-effectiveness ratio of £48,975 per additional QALY, which is above NICE's standard cost-effectiveness threshold (£20,000-£30,000 per QALY). The official price of bevacizumab in 2013 was between £2.31 and £2.63 per milligram. A price reduction of between 46% and 67%, dependent on the NICE threshold, would be required for the product to be cost-effective in the high-risk subgroup. CONCLUSIONS: The lower dose of bevacizumab for advanced ovarian cancer is not cost-effective based on the product's list price and using NICE's cost-effectiveness thresholds. Significant price discounts would be needed to make the drug affordable to the NHS.

Estimating the Cost-Effectiveness of Implementation: Is Sufficient Evidence Available?

BACKGROUND: Timely implementation of recommended interventions can provide health benefits to patients and cost savings to the health service provider. Effective approaches to increase the implementation of guidance are needed. Since investment in activities that improve implementation competes for funding against other health generating interventions, it should be assessed in term of its costs and benefits. OBJECTIVE: In 2010, the National Institute for Health and Care Excellence released a clinical guideline recommending natriuretic peptide (NP) testing in patients with suspected heart failure. However, its implementation in practice was variable across the National Health Service in England. This study demonstrates the use of multi-period analysis together with diffusion curves to estimate the value of investing in implementation activities to increase uptake of NP testing. METHODS: Diffusion curves were estimated based on historic data to produce predictions of future utilization. The value of an implementation activity (given its expected costs and effectiveness) was estimated. Both a static population and a multi-period analysis were undertaken. RESULTS: The value of implementation interventions encouraging the utilization of NP testing is shown to decrease over time as natural diffusion occurs. Sensitivity analyses indicated that the value of the implementation activity depends on its efficacy and on the population size. CONCLUSIONS: Value of implementation can help inform policy decisions of how to invest in implementation activities even in situations in which data are sparse. Multi-period analysis is essential to accurately quantify the time profile of the value of implementation given the natural diffusion of the intervention and the incidence of the disease.

The International Decision Support Initiative Reference Case for Economic Evaluation: An Aid to Thought.

BACKGROUND: Policymakers in high-, low-, and middle-income countries alike face challenging choices about resource allocation in health. Economic evaluation can be useful in providing decision makers with the best evidence of the anticipated benefits of new investments, as well as their expected opportunity costs-the benefits forgone of the options not chosen. To guide the decisions of health systems effectively, it is important that the methods of economic evaluation are founded on clear principles, are applied systematically, and are appropriate to the decision problems they seek to inform. METHODS: The Bill and Melinda Gates Foundation, a major funder of economic evaluations of health technologies in low- and middle-income countries (LMICs), commissioned a "reference case" through the International Decision Support Initiative (iDSI) to guide future evaluations, and improve both the consistency and usefulness to decision makers. RESULTS: The iDSI Reference Case draws on previous insights from the World Health Organization, the US Panel on Cost-Effectiveness in Health Care, and the UK National Institute for Health and Care Excellence. Comprising 11 key principles, each accompanied by methodological specifications and reporting standards, the iDSI Reference Case also serves as a means of identifying priorities for methods research, and can be used as a framework for capacity building and technical assistance in LMICs. CONCLUSIONS: The iDSI Reference Case is an aid to thought, not a substitute for it, and should not be followed slavishly without regard to context, culture, or history. This article presents the iDSI Reference Case and discusses the rationale, approach, components, and application in LMICs.

Methods for network meta-analysis of continuous outcomes using individual patient data: a case study in acupuncture for chronic pain.

BACKGROUND: Network meta-analysis methods, which are an extension of the standard pair-wise synthesis framework, allow for the simultaneous comparison of multiple interventions and consideration of the entire body of evidence in a single statistical model. There are well-established advantages to using individual patient data to perform network meta-analysis and methods for network meta-analysis of individual patient data have already been developed for dichotomous and time-to-event data. This paper describes appropriate methods for the network meta-analysis of individual patient data on continuous outcomes. METHODS: This paper introduces and describes network meta-analysis of individual patient data models for continuous outcomes using the analysis of covariance framework. Comparisons are made between this approach and change score and final score only approaches, which are frequently used and have been proposed in the methodological literature. A motivating example on the effectiveness of acupuncture for chronic pain is used to demonstrate the methods. Individual patient data on 28 randomised controlled trials were synthesised. Consistency of endpoints across the evidence base was obtained through standardisation and mapping exercises. RESULTS: Individual patient data availability avoided the use of non-baseline-adjusted models, allowing instead for analysis of covariance models to be applied and thus improving the precision of treatment effect estimates while adjusting for baseline imbalance. CONCLUSIONS: The network meta-analysis of individual patient data using the analysis of covariance approach is advocated to be the most appropriate modelling approach for network meta-analysis of continuous outcomes, particularly in the presence of baseline imbalance. Further methods developments are required to address the challenge of analysing aggregate level data in the presence of baseline imbalance.