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Objectives, Budgets, Thresholds, and Opportunity Costs—A Health Economics Approach: An ISPOR Special Task Force Report [4]

      Abstract

      The fourth section of our Special Task Force report focuses on a health plan or payer’s technology adoption or reimbursement decision, given the array of technologies, on the basis of their different values and costs. We discuss the role of budgets, thresholds, opportunity costs, and affordability in making decisions. First, we discuss the use of budgets and thresholds in private and public health plans, their interdependence, and connection to opportunity cost. Essentially, each payer should adopt a decision rule about what is good value for money given their budget; consistent use of a cost-per-quality-adjusted life-year threshold will ensure the maximum health gain for the budget. In the United States, different public and private insurance programs could use different thresholds, reflecting the differing generosity of their budgets and implying different levels of access to technologies. In addition, different insurance plans could consider different additional elements to the quality-adjusted life-year metric discussed elsewhere in our Special Task Force report. We then define affordability and discuss approaches to deal with it, including consideration of disinvestment and related adjustment costs, the impact of delaying new technologies, and comparative cost effectiveness of technologies. Over time, the availability of new technologies may increase the amount that populations want to spend on health care. We then discuss potential modifiers to thresholds, including uncertainty about the evidence used in the decision-making process. This article concludes by discussing the application of these concepts in the context of the pluralistic US health care system, as well as the “excess burden” of tax-financed public programs versus private programs.

      Keywords

      Introduction

      The previous section considered the elements of value at the individual and population levels. In this section, we focus on a health plan or payer’s technology adoption or reimbursement decision, given the array of technologies, with their different values and costs. Assuming a payer or population perspective, what are the objectives and constraints? We follow the Second Panel in recommending the cost per quality-adjusted life-year (QALY) gained (i.e., cost effectiveness) as the central measure for most of these decisions [
      • Neumann P.J.
      • Sanders G.D.
      • Russell L.B.
      • et al.
      Cost-Effectiveness in Health and Medicine.
      ]. Our main focus here is on the use of thresholds, opportunity costs, and budgets as constraints in relation to decisions about technology adoption and reimbursement. We briefly discuss the incorporation of a broader range of elements of value, particularly those related to equity, and this is then discussed more extensively in the article by Phelps et al. [
      • Phelps C.E.
      • Lakdawalla D.N.
      • Basu A.
      • Drummond M.F.
      • Towse A.
      • Danzon P.M.
      Approaches to aggregation and decision making—a health economics approach: an ISPOR Special Task Force report [5].
      ].
      In the article by Garrison et al. [
      • Garrison L.P.
      • Pauly M.V.
      • Willke R.J.
      • Neumann P.J.
      An overview of value, perspective, and decision context—a health economics approach: an ISPOR Special Task Force report [2].
      ], we noted that two microeconomic approaches—welfare economics and extra-welfarism—can each be used to justify a cost-per-QALY threshold for the inclusion of new technologies in the benefit package. In a welfare economics approach, the “budget” for each health plan is determined through market interactions of the buyers and sellers of health care insurance policies. The buyers seek to maximize their utility allocating their resources (including any subsidies) between insurance to cover health care in the event of illness and to protect against catastrophic financial or health loss, and other non–health-related goods. In a typical extra-welfarist approach, the size of the health budget of a public payer is determined through a political process in which taxpayers allocate funds to health versus other services. Public payer health budgets tend to be fixed in the short run and the primary aim is to maximize population health gain, subject to other modifiers, such as equity considerations. In both private and public insurance contexts, the choices have opportunity costs—some in the short run and some in the long run—and short-term decision making should take into account the longer term options and constraints.
      In this article, we discuss the general application of these principles. Nevertheless, because this Task Force report is focusing on US value frameworks, we will discuss more in later sections about specific implementation in the US health care system, which is a pluralistic system with 1) some public programs that are expected to operate within fixed annual budgets and 2) many private plans that, to varying degrees, view their annual premium revenue as a target annual budget. Hence, although implementation in the US health care system raises some specific issues, there will be some commonality in implementation with single-payer public health insurance systems such as the United Kingdom and Canada where budgets are fixed.
      Applying cost-effectiveness analysis (CEA) for health sector decision making requires a decision rule. The most commonly recommended approach is for the decision maker to adopt an explicit or implicit “threshold” of cost effectiveness representing the maximum level of cost effectiveness deemed acceptable for technology adoption and reimbursement within a given plan. The rationale for this approach is that consistent use of a threshold ensures that health gain is maximized for the covered population, given the payer’s budget. For example, in England, the National Institute for Health and Care Excellence (NICE) has a threshold of £20,000/QALY gained, with a range up to £30,000, but also up to £50,000 in the case of end-of-life treatments. As discussed earlier, health sector decision making typically considers more than just cost per QALY. In this article, we discuss the role of budgets, thresholds, opportunity costs, and affordability in making decisions. The first section discusses the role of budgets and thresholds in private and public health plans, their interdependence, and connection to opportunity cost. The second section defines affordability and discusses approaches to deal with it. The third section discusses potential modifiers to thresholds, including uncertainty about the evidence used in the decision-making process. The fourth section discusses application of these concepts in the context of the pluralistic US health care system, and the last section discusses “excess burden” (extra-implicit costs) of tax-financed public programs versus private programs. The article by Phelps et al. [
      • Phelps C.E.
      • Lakdawalla D.N.
      • Basu A.
      • Drummond M.F.
      • Towse A.
      • Danzon P.M.
      Approaches to aggregation and decision making—a health economics approach: an ISPOR Special Task Force report [5].
      ] discusses how a larger set of value elements might be weighted and aggregated into a more comprehensive, augmented CEA and how these elements could be considered as part of a structured deliberation, for example, using a form of multicriteria decision analysis.

      The Relationship among Budget Constraints, Thresholds, and Opportunity Costs

      The approach for determining the budget and threshold for a given year (or whatever the decision period) depends on the context. The most straightforward case is a jurisdiction operating its health care system efficiently with a firm budget constraint on one or more parts of the health system that is fixed in the short run. In this context, the most appropriate short-run approach to defining the threshold is the opportunity cost of displacing existing covered technologies, because if a technology with a cost-per-QALY gained higher than the threshold were to be adopted, then there would be a net loss in total health within the budget period [
      • McCabe C.K.
      • Claxton K.
      • Culyer A.J.
      The NICE cost-effectiveness threshold: what it is and what it means.
      ]. In the longer run, evidence on individuals’ willingness to pay (WTP) for improved health would be relevant, to inform the discussion of whether the budget for health care should be changed over time. In this context, the forgone benefit of cutting back on non–health-related goods and services is the opportunity cost of increasing the budget for health or raising the threshold. Important to note is that the threshold, the budget, and the measure of health gain cannot be set independently of one another.
      If novel elements of value are added to the QALY measure of health gain, with no change in the budget, the threshold would need to be reduced because the average measured benefit of technologies would increase. Although it might seem that using such an expanded QALY measure of health gain would argue for increasing the health budget, because certain indirect benefits of health care technologies have been recognized, it is important to consider whether some of these types of attributes also apply to non–health-related spending. Investing in housing and education, for example, can create option value and can bring additional value to risk-averse people. Consideration of other attributes to augment the health QALY measure may require expanding the measure of the opportunity cost of health-related spending. The impact on consumer or taxpayer preferences about health budgets is uncertain a priori. There may also be a dynamic aspect to consider. If the budget and/or the threshold is expected to change significantly over time, then some account needs to be taken of the long-term cost effectiveness of a technology to ensure that health and related benefits are maximized over time. Furthermore, over time, as incomes rise, and/or technological changes occur in health care, and/or non–health-related opportunity sets change, consumers’ WTP for health and related benefits, and consequently the size of health budgets and threshold levels, will change, as discussed hereafter.
      In a US private market context in which private plans (both employer-sponsored and not) compete by offering different levels of coverage, more generous coverage implies a higher threshold and a higher premium and budget. Thus, the threshold could be a convenient summary of coverage generosity that could be informative for consumers seeking to choose between plans. In this private market context, enrollees’ WTP premiums would reflect the WTP for health gain (and other health-related attributes) and define the payer’s budget for the year. In theory, market sorting would result in consumers (or employees) enrolling into plans that best match their preferences and WTP for health. In practice, such sorting may be imperfect because of adverse selection risk, fixed costs of operating plans, and social preferences (e.g., as mandated or imposed by the federal or state government) for some minimum level of coverage for all.
      For public plans, the budget may be fixed in the short run but in the longer run it can be changed by Congress. The threshold could be a way of eliciting taxpayers’ WTP for different levels of tax funding or health care budgets that enable different levels of coverage generosity. As noted earlier, in the short run (within a budget period), the threshold could reflect the value (i.e., opportunity cost) of the marginal technology displaced if a new technology were to be adopted in the context of a fixed budget: this is, in technical terms, the “shadow price” of the relevant budget constraint in the jurisdiction concerned. It is a measure of the health gain forgone if an established technology is displaced. In the longer run, use of either a WTP or an opportunity cost approach should yield the same threshold if the system has been implemented to perfectly match population preferences, income, and other determinants of taxpayers’/beneficiaries’ WTP for health within this public program. An expansion of the set of available technologies may change the opportunity cost in the short run, as discussed in the next section on “affordability.”
      It is sometimes suggested that the health budget and/or threshold be set in some relation to the gross domestic product per capita in the jurisdiction concerned, reflecting the evidence that richer countries typically devote more of their wealth to health care, or reflecting an aspiration of the amount that countries should spend on health care [
      • Tan-Torres Edejer T.
      • Baltussen R.M.
      • Adam T.
      • et al.
      Making Choices in Health: WHO Guide to Cost-Effectiveness Analysis.
      ]. This approach based on the gross domestic product may be a useful rough guideline for broad comparisons across countries. Nevertheless, actual decisions in individual countries reflect citizens’ WTP for health for themselves and others, which depends on many factors besides income, including tastes, politics, and the efficiency of tax-financed spending.
      In a setting in which health budgets can be easily increased, the approach for determining the threshold is more complex, especially in situations in which there is considerable patient co-payment with no stop-loss on patient cost-sharing and in which payers may stipulate limits on coverage for certain services. In theory, information on enrollees’/taxpayers’ WTP is relevant because one option when considering whether to adopt a technology would be to consider immediately increasing the budget for health care, by raising insurance premiums and/or patient co-payments. An opportunity cost of adopting a new technology still exists, but instead of falling in the health care sector, it would fall on other private consumption or on non–health-related public services or on future generations through public budget deficits, depending on how the funds to pay for the new technology are ultimately raised. Such a context is potentially problematic if the interests of those parties who end up bearing at least part of the cost are ignored in the decision making with regard to setting (or ignoring) thresholds and spending constraints, as occurs if budgets are poorly defined.

      Affordability

      Whether we are examining 1) individuals’ budget constraints for purchasing treatments or third-party insurance or 2) third-party (whether private, social, or tax-based) insurers’ budget constraints, plan members in practice choose to place a rough limit or budget on their spending on medical care during a given year. This reflects their preferences for medical care versus other non–health-related goods and services, which may of course change as the range of health care and non–health care technologies changes over time. The budget is expressed in the premiums they are willing to pay for private insurance or the taxes they are willing to pay for public or social insurance in a given year. The budget may in part depend on the ability or cost to the individual or third-party payer of borrowing across time periods and, in the case of public payers, any intergenerational implications of unfunded liabilities.
      As discussed in the previous section, in theory, the payer’s health care budget, WTP threshold, and services reimbursed are simultaneously determined and are adjusted over time, because changes occur in consumer incomes, health care technologies, and non–health-related consumption opportunities. Most new value-creating medical technologies can be accommodated by the displacement of older, inferior technologies and/or by growth of health budgets with income. Some new services may, however, meet the cost-effectiveness threshold but have a sufficiently large budget impact that they raise issues of affordability.
      Formally, we define affordability as being relevant if paying for all patients potentially eligible for a new treatment would force either an overrun of the payer’s planned budget or a displacement of other treatments regarded as being cost-effective. (This discussion thus does not address cases in which affordability is primarily a strategic argument in negotiations between payers and providers over price.) Such “unaffordability” is most likely to occur if a new drug or drug class is highly effective such that it can justify a relatively high value-based price and also benefit a large patient population. Recently, affordability has, for example, been a concern for drugs to treat hepatitis C. It has also been raised as a potential concern for cardiovascular disease or Alzheimer disease, and could also be a concern if a large number of high-priced orphan drugs came to market in quick succession, as could occur given the current pipeline of compounds with orphan status targeting cancer.
      If the payer’s budget is fixed in the short run, being spent efficiently, and, by assumption, cannot accommodate all existing services and the new service meets the current threshold, then in principle the threshold should be adjusted; this is sometimes called an “inframarginal adjustment.” This would call for elimination of those treatments that are no longer cost-effective at the new lower threshold. (Of course, if lower prices can be negotiated with suppliers of these services, this would mitigate the need for quantity adjustments.) Nevertheless, an important consideration may be the adjustment costs of disinvesting and switching resources into new uses, which could include changing protocols, withdrawing services, or switching patients to alternative regimens, which may entail budget, time, and health adjustment costs.
      The optimal short-run adjustment would thus weigh the benefits and costs, including adjustment costs, of either discontinuing some existing treatments or deferring the treatment of some patients with the new drug. In practice, such budget challenges can often be handled at the margin by stratifying patients eligible for the new drug, focusing immediate treatment on those at significant risk of disease progression, while deferring treatment of those at early stages and at low risk of disease progression in the short run. Such delay in treating diseases that progress slowly may incur minimal health loss or adjustment costs, compared with the alternative of discontinuing other existing treatments that meet the cost-effectiveness threshold but whose treatment interruption would incur significant adjustment costs. Delay in treating early-stage patients with the new technology also allows time for the entry of alternative, competing technologies, which may offer additional benefits and/or compete on price (as occurred recently with new hepatitis C medicines). In the long run, new technologies that meet cost-effectiveness thresholds are optimally absorbed by some combination of expansion of budgets if necessary (but note that some “curative” technologies that create budget pressure in the short run, such as hepatitis C treatment, may reduce long-term expenditures), possible threshold adjustment, and/or discontinuance of existing treatments that are rendered less cost-effective by the launch of superior new technologies.
      Because affordability can cause significant adjustment and other costs, some payers estimate the expected budget impact of a new technology, along with its value, as part of the coverage decision process. Estimating and planning for budget impact can be prudent and can facilitate some of the adjustments to minimize disruptions mentioned earlier, such as staging the adoption of a new technology with a large potential budget impact. We, however, do not recommend considering budget impact as an integral part of value assessment itself or structuring/requiring an automatic discount linked to budget impact, or introducing an inverse relationship between value and budget impact. Even if the potential level of investment requires considering an inframarginal adjustment of the threshold, such an adjustment in the threshold should be considered separately, and not as an integral part of value assessment. Although it might seem logical that a lower threshold should be used for drugs to treat very large populations, such an inverse relationship between threshold (and implicitly, reimbursed price) and target population would make sense only if WTP thresholds were designed mainly to pay for research and development and these costs were invariant across drugs. Nevertheless, in general, we have argued that thresholds should reflect value and WTP of consumers, not costs to producers. Whether producers can develop drugs that meet payer and consumer WTP thresholds is a matter for them. This argues against structuring an inverse relationship between thresholds and budget impact.

      Potential Threshold and Decision Modifiers

      Even in cases in which decision makers operate with an explicit threshold, a deliberative process (see the article by Phelps et al. [
      • Phelps C.E.
      • Lakdawalla D.N.
      • Basu A.
      • Drummond M.F.
      • Towse A.
      • Danzon P.M.
      Approaches to aggregation and decision making—a health economics approach: an ISPOR Special Task Force report [5].
      ]) is typically followed, in which other modifying factors may be applied. Many of these factors mirror the elements of value discussed in the article by Lakdawalla et al. [
      • Lakdawalla D.N.
      • Doshi J.A.
      • Garrison L.P.
      • Phelps C.E.
      • Basu A.
      • Danzon P.M.
      Defining elements of value in health care—a health economics approach: an ISPOR Special Task Force report [3].
      ]. The objective is not to maximize health alone, but to consider other health-related elements of value and to consider who might be getting the health gain. For example, as mentioned earlier, NICE operates with an end-of-life criterion, whereby the expert committee can increase the value of the QALYs gained, hence raising the effective threshold for adoption of the technology to £50,000/QALY to reflect society’s view that, in some circumstances, health gain at the end of life is worth more to individuals than at other points in their lives [

      National Institute for Health and Clinical Excellence. Appraising life-extending, end of life treatments. Available from: https://www.nice.org.uk/guidance/gid-tag387/resources/appraising-life-extending-end-of-life-treatments-paper2. [Accessed April 29, 2017].

      ]. The Scottish Medicines Consortium identifies several “modifiers” that may justify accepting a higher cost per QALY gained [

      Scottish Medicines Consortium. SMC modifiers used in appraising new medicines. Available from: http://www.scottishmedicines.org.uk/About_SMC/Policy_statements/SMC_Modifiers_used_in_Appraising_New_Medicines. [Accessed January 3, 2018].

      ]. These include, but are not limited to, evidence of a substantial improvement in life expectancy or quality of life (reflecting possible “step-change” innovations), evidence that the medicine can be targeted at a subgroup of patients who may derive specific or extra benefit (possibly reflecting severity of disease), absence of other therapeutic options of proven benefit (e.g., at end of life), or possible bridging to another definitive therapy (possibly reflecting “real option value”).

      Evidentiary Uncertainty as a Modifier

      When assessing a new medical technology, decision makers struggle with uncertainty and with how much evidence to collect. Evidence collection costs money and takes time, during which a medicine may not be given to patients, some of whom could benefit, whereas others may avoid risks. Thus, in general, additional evidence should be sought as part of a value assessment only if the expected benefit of evidence collection, in terms of the value of reduced uncertainty, exceeds the costs.
      It is important to separate whether decision makers are concerned about uncertainty because 1) it means the health system may adopt a technology that turns out to be poor value for money on average, or alternatively, not adopt one that looked to be poor value for money but actually provided a lot of benefit at a cost-effective price; or 2) there is real risk to health, that some patients may have been harmed by being treated. These are both valid but have different implications for value assessment. In relation to achieving value for money, we might expect decision makers to be risk-neutral, and look for a positive expected net benefit over cost, taking account of the threshold. Nevertheless, in relation to uncertainty about the incremental health effect (including any downside risks to health from adverse events), decision makers may then be expected to be risk-averse on behalf of patients. Hence, the common use of a P value of 0.05 for evidence of expected positive health effect, rather than a much higher P value of 0.5, which is implicit in our assumption of risk neutrality in payer assessment of value for money. Thus, payers (and health technology assessment bodies operating as their agents) typically use a two-stage approach, using one hurdle for evidence of clinical benefit and the other for evidence of value for money.
      In the context of the value-for-money assessment, the issue of a price adjustment for uncertainty arises. Any price adjustment for uncertainty in a value assessment should meet the requirement that, in the absence of the price adjustment, the expected benefit of evidence collection (in terms of the value of reduced uncertainty) must exceed the costs. Thus, if uncertainty cannot be reduced at an acceptable cost, it becomes irrelevant to value-for-money decision making. If uncertainty can be reduced by further evidence collection or simply with the passage of time, then the decision maker could require evidence collection or make the price contingent on the actual outcomes observed over time. The appropriate decision will depend on the institutional context and on costs of administering such contingent contracts [
      • Eckermann S.
      • Willan A.R.
      Expected value of information and decision making in HTA.
      ].
      We note that there may be separate issues of uncertainty about the budget constraint, optimal threshold, and/or opportunity cost estimate that should be used in decision making. So we have, in principle, uncertainty about our estimate of the incremental effectiveness and value of the technology and uncertainty about our estimate of the value for money or budget hurdle. This second issue has begun to be discussed in the literature, but we do not pursue it here [
      • Hines J.R.
      Three sides of the Harberger triangles.
      ,
      • Claxton K.
      • Martin S.
      • Soares M.
      • et al.
      Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold.
      ,
      • Barnsley P.
      • Towse A.
      • Karlsberg Schaffer S.
      • Sussex J.
      Critique of CHE Research Paper 81: Methods for the Estimation of the NICE Cost Effectiveness Threshold.
      ].

      Application in the United States

      In this section, we further elaborate on how these concepts might be applied in the United States, which has a pluralistic health care system with multiple private and public health plans. Different health plans could choose different thresholds, reflecting the differing WTP of their enrollees and, to the extent that the plan benefits from tax-financing, the WTP of taxpayers. Payers—both private and public—are thus agents for their enrollees or taxpayers. In making coverage decisions, a payer perspective is used, which reflects the average preferences of their enrollees/taxpayers. The individual patient perspective becomes relevant for patients and their doctors when making choices between covered technologies or between treatment options.

      Private Sector Employer-Sponsored Plans

      These plans can in theory freely choose their threshold WTP and implied premium cost as elements of competitive plan design. The threshold and premium in theory depend on the WTP for health (relative to other goods) of their employees. But the fact that workforce composition can change over time (and sometimes is purposely changed by owners by altering the type of benefits) makes these relationships difficult to measure in practice. Nevertheless, because the open-ended tax subsidy means that part of the cost of choosing a more generous threshold is shifted to taxpayers, either a cap on the tax exclusion or a tax on insured health expenditures that exceed some threshold is appropriate.
      In the treatment decisions of individual patients, plan administrators and providers should take into account individual patient preferences among alternative technologies that meet the collectively determined threshold. If a patient wants a technology that does not meet the plan threshold, it would not be reimbursed. He or she could pay wholly out of pocket—but is unlikely to do so unless the patient’s WTP is greater than the threshold. A variation of this would be for the threshold value to be paid for by the plan with the balance required to be paid for by the patient, that is, “balance billing.”

      Medicaid and Other Fully Tax-Subsidized Programs

      We assume that such programs are funded by federal and state taxpayers out of altruistic and equity concerns of taxpayers for program recipients. Taxpayer equity concerns may also include a Rawlsian approach as to what provision for the most disadvantaged people (in terms of both health needs and income) they would want to have provided. If so, program budgets reflect taxpayers’ WTP for such programs and to pay higher taxes for better health outcomes for people on low incomes or otherwise disadvantaged in access to health care. Thresholds are defined by the opportunity cost of resource use within the program. In treatment decisions of individual patients, their preferences among approved treatment options should be taken into account.

      Medicare

      Medicare is a hybrid that is financed largely by current taxpayers, with some contributions from current beneficiaries (current payments for parts B and D and past contributions to part A) and some shifting of unfunded liabilities to undefined future taxpayers. In theory, the budget and threshold should reflect some average of the WTP of taxpayers and beneficiaries. In treatment decisions of individual patients, the patient’s preferences between technologies that meet the threshold should be taken into account.

      The Excess Burden of Tax-Financed Public Spending

      When taxpayers provide much of the funding for a public insurance program that pays for a new technology, the full societal opportunity cost of raising that funding should ideally be taken into account, along with any benefits of using the public rather than the private sector. To date, conventional CEA of new medical technologies has not addressed this issue raised in public finance economics. One generally accepted conclusion from public finance is that all tax bases except for lump sum taxes generate “excess burden,” which is also called “deadweight loss” (DWL). Excess burden refers to the distortion that arises as an individual is discouraged from an efficient activity that would also increase his or her share of the tax base. Thus, a worker may be discouraged from working additional hours or switching to a better paid but higher productivity job, an investor may be discouraged from a profitable investment, and everyone is encouraged to hire more tax accountants. The reason why behavior is changed is because it is behavior that would otherwise increase the person’s share of the tax base and hence of taxes. The assumption is that even if the person attaches a very high value to the public activity that would be financed with the taxes, unless the person controls a very large share of the base, he or she would ordinarily think that the amount of the public good in question would be unchanged by an individual decision. Rather than increase one’s share of the taxes to finance some praiseworthy public activity but with no appreciable change in the amount of that activity, the person may decide to forgo the efficient choice. If all taxpayers try to reduce their shares at the expense of others, then all cut back and all lose.
      The size of the excess burden depends on the elasticity of response of the taxed activity to a tax. It is higher for tax bases that are more easily altered (such as investment in or purchase of specific commodities such as sugary drinks). Empirical estimates of the burden as a percentage of funds collected range from 20% to 60% (but are almost never negligible) [
      • Barnsley P.
      • Cubi-Molla P.
      • Fischer A.
      • Towse A.
      Uncertainty and Risk in HTA Decision Making.
      ]. There have been some calculations made of the excess burden of financing medical care in the United States, along with the conjecture that smaller programs will be chosen if the tax base has higher elasticity (such as the income tax compared with the payroll tax) [
      • Baicker K.
      • Skinner J.
      Health care spending growth and the future of US tax rates.
      ].
      Assuming a significant excess burden of taxes to fund health care, in theory we may need to consider whether the threshold for public spending should be adjusted downward to reflect excess burden. Such an adjustment is, however, not appropriate if there are different but offsetting distortions in providing private insurance, as discussed next.
      The usual assumption is that there is no excess burden for privately financed care, but if an employer imposed more of the cost of a group insurance benefit on workers as their earnings rose, there would be a distortion compared with a situation in which each worker’s wage is reduced by a lump sum amount to finance the employer premium share. The employee’s explicit premium share is rarely tied to wages (although occasionally it is) and so any excess burden from this source would be rare.
      Nevertheless, because employer plans reflect collective choices and each employer can offer only a limited number of plans (because of tax, fixed costs, and adverse selection concerns), the employer plan(s) on offer to individual employees may diverge significantly from each employee’s preferred plan. This divergence between their cost (in terms of forgone wages plus employee premium contribution) and their perceived value of the plan acts like a “tax” on purchasing employer-sponsored private insurance that should in theory be considered analogous to the excess burden on public insurance. To the extent that the collective choice of employer plans operates to reduce adverse selection risk, this is a mitigating factor.
      Furthermore, in the case of publicly funded programs such as Medicare and Medicaid, it could be argued that these were established as public programs specifically because taxpayers wanted to provide health care for the elderly and poor, and deemed that such coverage could be provided more cheaply and equitably by the government than by the private sector (because of adverse selection in private provision and free riding in voluntary financing of such programs). If so, they may rationally not view the taxes paid to support these programs as a DWL. Even if each taxpayer thinks their own contribution is negligibly small, everyone knows that free riding would undermine voluntary altruism, and that overcoming this effect is a benefit of using the tax system.
      These considerations at least suggest that different taxpayers may have different views of the DWL and the value of paying taxes to fund public health programs. Similarly, employees may have different views of the value to them of paying for employer-sponsored private insurance. Given the many unknowns, on balance at this stage, it is unclear what adjustments for distortions, if any, are appropriate for setting thresholds for public or for private insurance.

      Conclusions

      We have several clear recommendations on the basis of the discussion in this article. Each payer should adopt a decision rule about what is good value for money given their budget. Consistent use of a cost-per-QALY threshold will ensure the maximum health gain for the budget. In the United States, different public and private insurance programs could use different thresholds, reflecting the differing generosity of their budgets and implying different levels of access to technologies. In addition, different insurance plans could consider different additional elements to the QALY metric discussed here and in the article by Phelps et al. [
      • Phelps C.E.
      • Lakdawalla D.N.
      • Basu A.
      • Drummond M.F.
      • Towse A.
      • Danzon P.M.
      Approaches to aggregation and decision making—a health economics approach: an ISPOR Special Task Force report [5].
      ]. Issues related to the affordability of health care technology are most efficiently addressed by considering 1) the adjustment costs of reducing spending on, or replacing, existing technologies; 2) the impact of delaying or staging implementation of new technologies; and 3) the cost-effectiveness ratios of new and existing technologies. Over time, the availability of new technologies may increase the amount that populations want to spend on health care. Fundamentally, budgets and thresholds must continually be brought into alignment. Thus, as payers consider adding coverage of new technologies or new elements to the measure of benefits, implications for budgets and/or thresholds must simultaneously be considered to bring opportunity costs, thresholds, and health expenditures into alignment.
      Source of financial support: The authors did not receive any funding for this work other than reimbursement from the International Society for Pharmacoeconomics and Outcomes Research for travel expenses, as needed, for two Special Task Force meetings.

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