National Academies Press: OpenBook

Valuing Health for Regulatory Cost-Effectiveness Analysis (2006)

Chapter: 4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions

« Previous: 3 Measures and Strategies for Obtaining Health Benefit Values for Regulatory Analysis
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

4
Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions

Benefit–cost analysis (BCA) and cost-effectiveness analysis (CEA) provide summary measures of the economic efficiency of health and safety regulations—of the net benefits they deliver and of the cost per life year or quality-adjusted life year (QALY) saved. In measuring net impacts on social welfare, both BCA and CEA implicitly contain normative assumptions regarding the relative value of different contributors to well-being. It is important that we understand the ethical assumptions implicit in BCA and CEA and consider the implications of these assumptions when using the resulting information to make decisions about regulating risks. In this chapter the Committee discusses ethical and other unquantified considerations in regulatory analysis and decisions, particularly with respect to QALY-based CEA.

Normative assumptions are implicit in how the benefits measures are constructed in BCA and CEA. In CEA, for example, effectiveness measures such as life years or QALYs weight lives saved by considering remaining life expectancy. They thereby assign a greater weight to saving the life of a younger person than an older one, if other factors are equal. In BCA, willingness-to-pay measures in theory can be designed to address a wide range of factors, but in practice may not address important dimensions of the population affected or the nature of the risks.

Other normative issues arise due to factors that are excluded because of the focus on efficiency or because of data or methodological limitations. Such considerations relate to:

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
  • The distribution of the effects across different population subgroups;

  • Impacts that cannot be quantified easily; and

  • Features of the risks that are not easily captured in the benefits measures.

Economic analysis is only one of many kinds of information that contribute to decisions related to regulation of health and safety risks. Regulatory decisions should and do reflect a number of considerations in addition to aggregate estimates of costs and benefits.1 The goal of this chapter is to discuss the assumptions and methodological limitations inherent in such analysis that, from the Committee’s perspective, are most important to consider in making decisions.

More specifically, the aggregate nature of net benefits or a cost-effectiveness ratio means that these measures by themselves cannot capture the distribution of benefits or of costs in a population. Aggregate estimates of QALY gains or cost-effectiveness ratios do not indicate the distribution of impacts over time or the magnitude of individual gains. Summed QALYs do not distinguish between health gains made within the course of a single life or across generations. Nor do they indicate whether the QALY gains represent small health improvements widely dispersed throughout a population or larger gains allocated among relatively few people.

Summary benefit–cost and cost-effectiveness measures also omit benefits that are difficult to quantify. Such benefits include health and nonhealth effects for which numerical estimates are not available, for example, because the scientific research base is inadequate to support quantified estimates of impacts or because relevant monetary values or effectiveness measures have not been developed. Policy makers and the general public may also care about characteristics that are not captured in QALYs nor by many of the other valuation measures used in CEA or BCA, such as the degree to which the risk is observable or controllable, and whether the risk is especially dreaded.

In this chapter, we first examine the ethical and normative2 assumptions implicit in the calculation of the cost-effectiveness ratio, including the

1  

This position is reflected in the recommendations of previous expert panels and current Executive Office of the President guidance (U.S. Panel on Cost-Effectiveness in Health and Medicine, Gold et al., 1996b; Institute of Medicine Committee on Summary Measures of Population Health, IOM, 1998; Executive Order 12866, EOP, 1993; and Circular A-4, OMB, 2003a).

2  

In this chapter, “normative” refers to a variety of value-based judgments and beliefs, including some that are not ethical or moral in nature. For example, the fact that some people consider death from cancer worse than death from other causes is by itself not an ethical concern, though it involves a value-based judgment that guides their behavior.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

construction of the metric most commonly used in CEA to value health outcomes, the QALY. In the second and third sections of the chapter, we identify important normative and distributional concerns that are not reflected in cost-effectiveness ratios and that should be taken into account in regulatory decisions. In the fourth section, we discuss the importance of an accountable, public deliberative process to bring together information from economic analyses with information about the ethical, qualitative, and distributive aspects to craft regulatory policies. The final section summarizes the Committee’s conclusions.

ETHICAL ASSUMPTIONS IN QALY-BASED CEA

The QALY’s strengths as the effectiveness metric in CEA are largely practical ones. The QALY is well established; it has been applied in hundreds of studies over several decades, is supported by generic health assessment survey instruments, and allows morbidity and mortality information to be readily combined. However, the QALY incorporates certain ethical commitments and ignores others. This section identifies some of the ethical implications of using the QALY as a unit of measurement for valuing health outcomes in CEA.

As discussed in Chapter 3, a QALY can be thought of in several different ways. Most simply, it is an index with an intuitive meaning, namely, an index that relates a particular state of impaired health (of a given duration) to some number of years in optimal health. More complex interpretations of the QALY, such as an index derived from utility theory or even as a direct measure of utility, are debatable, and are valid only under certain restrictive assumptions. When used in CEA for regulatory analysis, the QALY is probably best interpreted in its intuitive sense, as a measure of health improvement or production that facilitates comparisons with other opportunities for health gains. This pragmatic interpretation of the measure avoids the need to demonstrate that the QALY has particular properties consistent with the utility theory that underpins BCA and welfare economics.

Valuing Life Years Compared with Valuing Lives

Perhaps the most basic normative commitment entailed by using QALYs as an outcome measure in CEA is valuing some form of life years, rather than whole lives or preventable deaths. This move from treating all deaths equivalently to denominating losses and gains in terms of the extent of changes in longevity is illustrated by Table 4-1. Using lives as an impact measure assigns the same value to a preventable death regardless of whether the person is young, middle aged, or elderly, while the use of life years

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

TABLE 4-1 Lives, Life Years (LYs), and Quality-Adjusted Life Years (QALYs)

 

Preventable Deaths

LYsa

LYs Discounted at 3%a

LYs Discounted at 7%a

QALYsb

QALYs Discounted at 3%b

QALYs Discounted at 7%b

Age (in years)

5

1

73

29

14

65

27

13

35

1

44

24

14

37

21

12

75

1

12

10

7.9

9.1

7.6

6.1

Ratio of values by age

5/35

1

1.7

1.2

1.0

1.8

1.3

1.1

5/75

1

6.1

2.9

1.8

7.1

3.6

2.1

35/75

1

3.7

2.4

1.8

4.1

2.7

2.0

aBased on age-specific life expectancy for 2002 (NCHS, 2005).

bBased on EQ-5D norms for the adult U.S. population (Hanmer et al., 2006); assumes HRQL is 1.0 for individuals through age 9, and midway between 1.0 and the value for persons age 20 for individuals ages 10 through 19.

shows the difference in impact of preventable mortality on younger and older individuals. Furthermore, adjusting life years for health-related quality of life (HRQL) in the QALY calculation increases the difference between the impact estimates for a younger as compared with older person.

Using QALYs gained, rather than deaths averted, as the measure of effectiveness in CEA has analogous implications in the BCA context. As discussed in Box 4-1, analyses in which monetized estimates of the value of preventable deaths vary by age have been highly controversial. Similarly, CEA using life years or QALYs gained as the effectiveness measure also appears to disadvantage older people, who have shorter average remaining life expectancies during which they can benefit from interventions. Some argue that shifting from valuing whole lives to any form of life years unfairly discriminates against older people, who may value the remainder of their lives as highly as do younger people. Similar arguments can be put forward for people with life expectancies shortened by their socioeconomic status or preexisting health conditions or disabilities.

A countering perspective is provided by those who hold that everyone should be given an equal chance to have a “normal” or full lifespan and that averting deaths among those who have achieved a normal lifespan should not count for as much as averting deaths among much younger persons. One implication of this view is that measuring life-preserving gains in terms of years of life does not unfairly disadvantage older people relative to younger people (Harris, 1987; Williams, 1997). In addition to this nor-

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

BOX 4-1
The “Senior Discount” Controversy

Analytic approaches that assign a lower value to premature mortality among the elderly have been the subject of heated debate in the context of BCA. In particular, the Environmental Protection Agency’s use of estimates that reflected the value of remaining life years in a sensitivity analysis of air pollution-related policies led to a significant public outcry (Skrzycki, 2003). Based on a survey of older adults’ willingness to pay for remaining life years, the analysis placed a lower value on premature mortality among the elderly (referred to as the “senior discount” in the subsequent policy debates). The controversy led the Office of Management and Budget (OMB) to issue a memorandum requiring agencies to avoid age adjustments (Graham, 2003a). OMB Circular A-4, which extends the guidance to CEA, amends the instructions regarding age adjustments (OMB, 2003a). The Circular notes that population averages, rather than values reflecting differences among subgroups, should be used in assessing both health-related quality of life and life expectancy to support the perceived fairness of the analytic approach.

mative argument, survey results suggest that, in the abstract, people judge saving the lives of younger as compared with older persons more important (Cropper et al., 1994).

Presenting the results of a CEA in several forms, using deaths averted, life years extended, and QALYs gained as alternatives, is one way to broaden perspectives on gains in life expectancy. In addition, reporting disaggregated estimates of regulatory impacts by key age and population characteristics—such as income, race, gender, or other factors relevant to the particular intervention—also increases the transparency of the justification for and implications of the regulatory action. Both strategies facilitate ethical deliberation.

A QALY Is a QALY Is a QALY

In contrast with the willingness-to-pay measures used in BCA, which may be affected by wealth and hence may vary depending on individual financial resources, by construction the value of a QALY is assumed not to vary with income. Although the relationship between willingness to pay and wealth is complex and depends on the characteristics of the good or service (see Freeman, 2003), the fact of this relationship can lead to concerns that the BCA results will be weighted toward the interests of wealthier members of society. In practice, regulatory analysts generally use willingness-to-pay values or ranges of values that reflect averages from the

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

relevant research, rather than assigning different values to health risk reductions affecting richer and poorer people.

QALYs value an improvement in health of a given magnitude the same regardless of the characteristics of the person experiencing the improvement. They ignore the relative economic standing of affected populations in representing the value of health gains and reflect an ethical commitment to the income-independence of health as a societal value.

In addition, each QALY unit is of equal value in all contexts. Regardless of the individual to whom a QALY accrues, the states of health preceding or following the period in question, how widely health gains are distributed within a population, how impaired one beneficiary of a health gain is relative to another, or how a given impairment affects the lives of different persons, a QALY always carries the same value. Other health metrics, such as the healthy year equivalent, the saved young life equivalent, and the age-weighted disability-adjusted life year, each convey a different aspect of the distribution of health gains that the QALY omits.3 However, none of these alternative HALY metrics are superior to the QALY in practice. No single metric can reflect all significant aspects of particular sorts of gains in health and longevity. The QALY, like any construct, imperfectly captures all aspects of what we value in good health. We know of no weighting scheme that is able to accurately reflect the full range of societal values relevant to regulatory decisions; in reality, these weights may vary depending on the particular decision-making context. Presenting supplementary information about the size and characteristics of the exposed population, the per capita magnitude of the risk, and the distribution of expected benefits will help respond to these concerns.

The Source of HRQL Values

The question of perspective in valuing HRQL has several dimensions. One has to do with the source of relative health state values, that is, whether they come from the general population, patients or persons experienced with the health state in question, or experts such as clinicians. The other dimension concerns the method for eliciting HRQL values and, more specifically, whether those values reflect individual preferences for one’s own health or preferences for societal investments in health more broadly.

Whose Values Count?

The appropriate evaluative standpoint from which to determine the relative values of different health states, conditions, and disabilities in CEA

3  

These HALY measures are discussed in Chapter 3.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

depends on the context of the decisions that the analysis is intended to inform. In clinical studies to compare the effectiveness of alternative treatments, for example, the values of patients may be most appropriate. In contrast, for societal decisions about resource allocation in health care settings, community values (i.e., the aggregated and averaged judgments of a representative sample of individuals in the general population) regarding the relative desirability of different states of health should be used (Gold et al., 1996b).

Because most economically significant regulations for which CEA is required affect all segments of society in terms of their costs and/or benefits, valuations (both for directly elicited values for specific health outcomes and valuation surveys underlying generic HRQL indexes) generally should be based on representative samples of the general U.S. population. Analysts will need to consider this issue in the context of individual regulations, however, because some rules disproportionately affect certain subgroups. For example, a regulation might impose costs and provide benefits primarily for elderly people or for residents of a single geographic area. In this case, values based on the affected subpopulation would be preferable.

If obtaining subpopulation values is not feasible, it would be important to conduct uncertainty analysis on the possible differences in valuation. Little is known about the differences in health state valuation across sociodemographic subpopulations in the United States with the notable exception of the recent U.S. EuroQoL-5D (EQ-5D) valuation survey (Shaw et al., 2005). This survey oversampled the two largest minority populations, Hispanics and non-Hispanic blacks, so that reliable subpopulation estimates could be calculated.

A related analysis that compared U.K. and U.S. results for these two large and methodologically consistent EQ-5D valuation surveys found significant differences in the values for particular health states (Johnson et al., 2005). These differences were not constant or systematic across health states; those characterized by severe problems had the largest discrepancies, with U.S. valuations exceeding the U.K. valuations. Although these findings suggest that it is important that the health state index values be derived from a population comparable to the one of interest, it may turn out to be less of an issue in practice than in the abstract. As illustrated by the case studies, regulatory analysis involves comparing health status with and without the condition of interest. More research would be needed to determine whether such estimates of changes in health status are as dependent on the population surveyed as are the estimates for particular conditions (Franks et al., 2006).

Some research shows that preferences for particular health states are quite similar for different groups of people, when patient valuations are compared with those of nonpatients, and when the valuations of different

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

socioeconomic and ethnic groups are compared (Kaplan and Bush, 1982; Llewellyn-Thomas et al., 1982, 1993; Balaban et al., 1986). Other studies, however, suggest that people who have experienced a disease or disabling condition will tend to value that state more highly than those with no experience (Sackett and Torrance, 1978; Najman and Levine, 1981; Slevin et al., 1990).4 One possible explanation for this latter finding is that those with the condition or impairment have made adjustments or adaptations that result in lesser losses in HRQL than are anticipated prior to any illness or disability.5

Discrepancies in valuations of impaired or disabled health states between a general population and those with experience of the condition have led some to challenge the validity of general population valuations, arguing that they are uninformed and potentially discriminatory. Recent research findings in psychology and behavioral economics suggest that people incorrectly predict the impact of changes in their circumstances on their sense of well-being (Kahneman et al., 1997; Wilson et al., 2001; Gilbert and Ebert, 2002; Riis et al., 2005). If health state index values are intended to represent the relative effects of different conditions on people’s lives rather than reflecting apprehensions and prejudices about those conditions, then values elicited from people lacking knowledge about the conditions may be biased.

Furthermore, people with disabilities and disability advocacy groups have objected to being “assigned” lower HRQL values than are those without disability, on the grounds that the practice leads to the devaluation of persons living with disabilities and to perpetuation of stigma associated with particular conditions (Wang, 1992; Silvers, 1996). If a health condition or disability—human immunodeficiency virus disease or paraplegia, for example—is valued lower by the general public because it is stigmatizing, using this valuation in a public policy analysis may reinforce, and be taken as condoning, such prejudice.

Wasserman and Asch (2004) have suggested an alternative way to establish the relative values of preventing particular injuries and impairments. They propose that relative values should be based on the costs of restoring capacities and improving various aspects of quality of life for those who are impaired. For example, facilitative and adaptive technologies for persons with speech or writing disabilities can restore communications

4  

This valuation question must be distinguished from the task of characterizing the experience of a particular health condition or disability according to a multidimensional generic survey instrument. The descriptive task is always best carried out by those who are familiar with the condition, as discussed in Chapter 3.

5  

Such adaptation is not only psychological; it can involve substantial investments in rehabilitation, personal assistance, assistive technologies, and physical accommodations in the built environment (IOM, 1997).

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

abilities. The cost of providing someone who has lost capabilities through injury with the equipment and services that restore functioning could be used to establish an upper bound on the cost of that injury or impairment, relative to unimpaired health. Such investments could well exceed what is now spent on rehabilitative services for some conditions. Thus this approach to valuation is more demanding than a cost-of-illness estimate based on historical spending. Initial estimates (for the United Kingdom) of the costs of restoring capacities have been made for some conditions (Smith et al., 2004). We recognize that this strategy is not practicable in the near term, and would likely be feasible only for some kinds of disabling conditions. In concept, however, it offers an alternative to preference-based measures that avoids the apparent devaluing of lives spent with impairments.

The use of general population valuations does not necessarily result in material disadvantage for those with impairments or disabilities (Gold et al., 1996b). Because the perspective is ex ante in regulatory analysis and it cannot be known with certainty who ultimately will be affected, the values of those potentially affected (represented by the general population for most economically significant health and safety regulations) are appropriate in this context. This perspective takes account of the loss of capacities and opportunities that attend illness and injury. It reflects the societal value accorded having greater rather than lesser capacities and more rather than fewer opportunities.

If a subset of the general population receives the benefits and pays the costs of the regulation, then the values of this subpopulation should be used. In particular, there may be instances where the costs and benefits of a rule predominantly affect people with a preexisting illness or disability addressed by the regulation. In this case, the affected population is the same as the patient population, and patient values would be appropriate. Later in the chapter we consider the circumstances under which the lesser values placed on health improvements among those with impaired health or disabilities can be ethically problematic.

Individual Preferences and Societal Values

As noted in Chapter 3, empirical research suggests that each elicitation technique—standard gamble, time trade-off, category rating, and person trade-off (PTO)—produces somewhat different relative values for states of health. One distinction among these four elicitation methods is that the first three techniques query individual preferences, while the PTO method is socially oriented. PTO exercises ask for judgments about the equivalence of health improvements and life extensions for groups of people who differ in their states of health, age, and other relevant characteristics (Richardson and Nord, 1997; Nord, 1999). Respondents are asked “to compare the

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

relative benefits of treating different conditions in a context of comparing equivalent numbers needing to be treated to produce equal social benefits” (Ubel et al., 1998, p. 43).

The results of PTO exercises suggest that values other than the maximization of potential aggregate health benefits, as measured by conventional QALYs, affect decisions to allocate health improvements among groups. Allocation choices using PTO tend to give greater weight to improving the health of more severely impaired groups relative to those with lesser problems (Nord, 1999). PTO elicitations also tend to distribute potential health gains more widely among groups able to benefit (Menzel et al., 1999).

Because of the broad and essentially social nature of health and safety regulation, the PTO method may be particularly appropriate for valuing health outcomes in this context. As noted in Chapter 3, much work remains to be done, however, to develop the PTO technique and the empirical base from which to estimate values. The Committee concludes that research to develop better approaches to societal valuation for regulatory CEA is warranted.

Combining Morbidity and Mortality in a Single Measure

As detailed in Chapter 3, QALYs combine information about changes in survival and morbidity in a way that reflects individuals’ preferences for trade-offs between longevity and quality of life. This fundamental property of the QALY mirrors the actual situation of patients who face medical treatment choices that involve a risk of death. However, when QALYs are also used to compare very different health-related interventions, this framework may not mirror the actual choice as closely. Analyses of regulatory interventions are likely to encompass broader arrays of health-related effects for large population groups. CEA will at times involve the aggregation and synthesis of many health outcomes and of impacts across diverse groups of people, as illustrated in the examples in Chapter 2. In addition, evaluating the health impacts of regulatory interventions requires combining the benefits of increased length of life and improved quality of life for a population, rather than trading off longevity against improved quality of life for a given individual.

When health outcomes are aggregated and averaged across diverse conditions and populations, a single summary measure will mask disparities in impacts among age or other population groups. For example, in the Environmental Protection Agency (EPA) analysis that was the subject of the air quality case study, the summary measure masks the range of impacts on the very old, the very young, and those with preexisting conditions. Thus EPA presents disaggregated results for mortality and morbidity and for different age groups (see Table 2-4). The Committee’s recommendations,

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

presented in the final chapter, address the need for reporting disaggregated analytic results in regulatory analyses.

Summary

This section briefly reviewed the ethical assumptions embedded in QALY-based CEA. Using QALYs in regulatory analysis widens the application of this analytic tool and introduces a complex normative construct to a new audience. Understanding what the QALY does and does not reflect in the measurement of health effects should help regulatory analysts and policy makers interpret and communicate their analytic results. In particular, analysts should keep in mind the need to present information on the nature of the individual health effects and the characteristics of affected population groups because QALYs subsume these distinctions. The societal perspective of regulatory analysis is best reflected by valuation of health states and conditions by people affected by the regulation. At the same time, it is important to keep in mind the potential biases in the valuation of some health states due to unfamiliarity, lack of experience, or because the states carry stigma. The rationale for using health state values elicited from community-based sample surveys in regulatory analysis is to reflect the preferences and values of the population likely to receive the benefits and/or bear the costs of the intervention.

ETHICAL AND OTHER IMPLICATIONS OF RISKS AND OF INTERVENTIONS TO ADDRESS RISKS

In this section we consider the ethical, distributional, and other factors relevant to decisions about regulating health and safety risks that are not captured in CEA.

Dimensions of Value Affecting the Acceptability of Risks

Not all kinds of risks are the same. Risks may differ in ways that can affect their acceptability for individuals and for society as a whole, as well as their assessment from an ethical point of view. How government agencies should address risks that differ in kind and in acceptability (both to individuals and the larger community) is a question that can be addressed only as part of broad, public, and deliberative discussions.

Regardless of whether the value of risk reductions is measured by cases averted, willingness to pay for health improvements, or QALY gains, the measure is likely to exclude some aspects of the risk reductions that are valued by society. For example, a 1-in-100,000 reduction in the risk of death may be valued differently depending on the source of the risk; society

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

may place a higher value on reducing risks associated with unpleasant sources (e.g., hazardous waste sites) than on risks associated with enjoyable activities (e.g., riding a motorcycle). This difference in valuation will not be reflected in single-dimension measures of benefit, such as cases avoided or years of life extension, nor will it be reflected in QALY measures focused on health-related impacts on quality of life.6

Because QALY-based CEA does not and cannot account for the nature of the risk itself and societal perceptions and values related to it, some features of risks must be considered explicitly by decision makers alongside the summary results of economic analyses. The psychological aspects of risk perception and risk assessment have been well studied (Slovic et al., 2000, 2004). At the same time, the normative significance of the public’s perceptions of risks has been challenged (Margolis, 1996). Without joining this debate, the Committee proposes that the following characteristics be considered in regulatory impact analyses along with the presentation of quantified results:

  • Knowledge about or understanding of risks,

  • Degree of personal control, and

  • Source or nature of risks.

These dimensions may affect the justification for regulatory action as well as the value placed on the resulting risk reductions. For example, as discussed in Chapter 1, regulation may be justified in cases where there is an externality, such as in the case of pollution that imposes health risks that are not controllable by the individual affected. Regulation may also be justified where information is lacking; for example, certain pathogens in food may not be easily detectable by consumers. However, this section focuses more specifically on the need to incorporate the value placed on these risk dimensions in the regulatory decision-making process, rather than on the initial justification for considering regulatory action.

Three aspects of risks bear on our knowledge or comprehension of them: To what extent are they easily detectable by the senses? Are their effects delayed or more immediate? Are they relatively well understood? Although these features of risks do not have direct ethical implications, they can affect the personal, social, or moral acceptability of certain risks or at least raise issues that should be discussed concerning the value placed on reducing them (Cranor, 1995).

If risks can be avoided because they are easily detectable, as in some traffic-related situations, we can use our basic human sensory capabilities

6  

Although willingness-to-pay estimates could, in theory, incorporate the values associated with features of particular risks, in reality such estimates rarely address all aspects of the risks.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

to provide some protection against possible harm. At the very least, we may believe that we will have some opportunities for self-protection. These kinds of risk exposures may be more acceptable to us than risks for which we cannot provide any degree of self-protection by exercising normal human capacities, such as in the case of an undetectable toxicant in the air. As a result, we may value reduction in undetectable risks more than detectable risks.

Risks with delayed effects often lack an immediate feedback mechanism that would allow individuals or a community to implement timely protections. A pesticide released into the environment that immediately killed all exposed frogs would alert us to a problem meriting attention. By contrast, release of a pesticide with long-delayed but potentially devastating effects may receive less attention, and could lead a community to value precautionary measures more highly. Although the timing and duration of the risks, including related latency periods, are captured to some extent in the QALY measure, such measures may not fully incorporate the different values placed on reducing immediate versus delayed risks.

Some risks allow us a degree of personal control; for example, the care one takes in operating chainsaws or other kinds of equipment will obviously affect the likely degree of harm. Other risks are not subject to significant personal control by those facing the risk, such as toxic air pollutants. The degree to which one can control exposure to a hazard, and whether or not the hazard results in harm, can affect acceptability of the hazard and the value placed on risk reductions. Many risks are regulated because they are not subject to significant personal control and individuals can do little or nothing to protect themselves.

A third aspect of risks that bears on their acceptability includes intrinsic or contextual features of special concern, such as risks that are particularly dreaded (Slovic, 2000). Dreaded risks may reflect concerns about particularly unpleasant diseases or ways of dying (e.g., from cancer) or risks that could materialize as especially catastrophic harms, such as failure of nuclear power plant containment measures. Certain risks or outcomes may be dreaded because of stigma attached to them, such as HIV-positive status or paraplegia, as mentioned earlier.

These features point to important aspects of risks that could affect people’s assessment of their acceptability and the degree of care with which they are approached. The above list is not exhaustive; rather, it is designed to suggest a variety of considerations that are likely to affect personal, social, or moral judgments regarding the value of risk reductions. Individuals’ judgments about the acceptability of risks may also be affected by considerations such as whether the risk activity provides significant benefits; the degree, if any, of participation in decisions that have created the risk or the exposure; and how reliable a governmental agency is in provid-

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

ing protections from risks (Cranor, 1995; HM Treasury, 2005). Such dimensions of risk merit public deliberation and input.

Nonquantifiable Impacts

The economically significant health and safety regulations subject to OMB’s requirements for CEA will have some risks that can be quantified (e.g., in terms of cases averted) and valued (e.g., in terms of QALY gains or willingness to pay for risk reductions). In addition, some of these regulations will have quantified nonhealth benefits. When these regulations provide additional health and/or nonhealth benefits that cannot be measured in numerical terms, care should be taken to ensure that these impacts are considered in the decision-making process. As discussed in Chapter 1, the existing guidance for regulatory decision making emphasizes the need to consider these nonquantifiable impacts.

In some cases, these nonquantifiable effects result from the limitations of the underlying health research. For some risks, a link to clinical disease has not been established definitively. For example, research shows that ozone changes the structure of lung tissue, but the implications of these changes for long-term health are not yet well described (Gilliland et al., 1999; Hubbell et al., 2005). Such “precursor” or intermediate biological conditions that might lead to adverse clinical effects in the future are not included in the quantitative measures used in CEA or BCA.

There are other risks, unrelated to human health, that may be reduced or prevented by regulations. Because they are not related, CEA based on single-dimension health measures or on QALYs will not capture them. For example, not only may dioxins released into surface water threaten the public’s health, they may also have substantial environmental effects because they accumulate in many organisms, are persistent, and disrupt endocrine systems. The visibility improvements associated with the air pollution rule considered in the Committee’s EPA case study are another example. Such consequences will not be captured in the effectiveness measure of a CEA that focuses only on human health protection. If quantified, however, such impacts could be included as an offset to costs.

Summary

This brief discussion provides some background on the particular features of risks that may affect the value placed on regulations designed to reduce or eliminate them. Three points emerge from this discussion. First, insofar as CEA aims to provide objective assessments of population health as measured by clinical disease, it may miss or undervalue other considerations, including nonquantified and nonhealth impacts, that should enter

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

into public decisions concerning risk regulation. If such considerations cannot be incorporated into the cost-effectiveness calculus, they must be reintroduced into the decision-making process as an adjunct to summary economic information.

Second, the failure to account for the distinctive features of risks may in some circumstances lead to misinterpretation when cost-effectiveness ratios for different regulations are compared. Because CEA is a tool for comparing different interventions aimed at the same end, ignoring the different value dimensions of the risks involved or the contexts of the risks may well result in misleading comparisons and ultimately to poor regulatory decisions.

Last and most importantly, the multiple value dimensions of risks deserve public and deliberative consideration as regulatory options are devised and considered; these aspects of risk are as relevant for the decision as the results of economic analyses. Although in theory monetized estimates of the benefits of regulations could capture some of these characteristics, in practice they may not be fully captured by either BCA or CEA. The information conveyed by a cost-effectiveness ratio may be of interest because it presents costs and health-related effects in isolation from other pieces of information about the risk and the intervention. However, the cost-effectiveness ratio is, by itself, not an adequate basis for decision making and must be supplemented by other information. Even if not all stakeholders agree on the normative implications of a particular risk or intervention (and it seems unlikely that there will be unanimity), invoking these implications and discussing them ensures that qualitative information is not ignored in the decision. Disagreements about the relevance and importance of the different aspects of risks create an even greater need for public debate, both in preregulatory priority setting and in the development of and public comment on the regulation itself. Box 4-2 illustrates how these concerns might be summarized in the presentation of the results of economic analysis.

DISTRIBUTIONAL CONCERNS ABOUT RISKS AND REGULATORY INTERVENTIONS

By itself, a QALY-based CEA cannot address an important and difficult set of distributional questions and choices, including how much priority we should give to the sickest or the worst off in valuing health effects; when we should allow modest benefits to many people to outweigh significant benefits to fewer; when we should allocate resources to produce “best outcomes” as compared with giving more people fair chances at some benefit; and how the costs and benefits of regulatory interventions are distributed within the overall population. Both CEA and BCA can provide

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

BOX 4-2
Risk-Related Considerations for Regulatory Decisions

Characteristics of Risks: Do the risks averted by the rule have characteristics that affect the value society places on reducing them but that are not reflected in the quantified effectiveness measures used to assess the policy? For example:

  • Are the risks not subject to significant personal control?

  • Are the risks particularly dreaded?

  • Are the risks undetectable by the senses?

  • Are the effects of the risks delayed, rather than immediate?

  • Are the risks not well understood?

We use the three case studies—on food safety, air quality, and child restraints anchoring—to provide examples of how risk-related concerns might be summarized in a regulatory impact analysis.


Food safety. Personal control and detection: In the absence of regulation, consumers generally lack the ability to determine whether a particular batch of juice contains pathogens. Understanding: Information about these risks emerges gradually as outbreaks occur, and the probability of individual exposure is relatively slight. Thus consumers may not fully understand the potential consequences.


Air quality. Personal control and detection: Air emissions from nonroad engines and sulfur in diesel fuel can severely affect many individuals whose ability to detect and avoid exposures in the course of daily life may be very limited. Dread: The associated risks include a relatively high rate of premature death and may include forms of cardiac and respiratory illness (e.g., congestive heart failure, emphysema) that are particularly dreaded.


Child restraints anchoring. Dread: Not only are children’s lives and well-being highly valued in general, but severe injuries from motor vehicle crashes, such as traumatic brain injury, are particularly dreaded by parents and others. Understanding: The high rate of improper installation of child restraints in the absence of the rule suggests that attachment requirements were not well understood.

disaggregate information on impacts, if the underlying research on risks and effects supports separate estimates. However, standard analytic practices in BCA and CEA generally do not weight the results to reflect societal values across these dimensions. For example, a QALY decrement of 0.2 is not adjusted to reflect a preference for averting illnesses among particularly vulnerable groups. Similarly, values assigned to risk reductions of a given magnitude in a BCA generally do not depend on the distribution of impacts.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

Although for both CEA and BCA values could, in theory, be adjusted to reflect distributive concerns, a consensus on how to weight across such dimensions does not exist. Thus distributive considerations must be explicitly discussed as part of the process of developing and issuing regulations along with the summary analytic results.

As noted in Chapters 1 and 2, regulatory agencies are required to conduct analyses of the distributional impacts of regulations. As discussed below, society may particularly value regulations that address subpopulations that are vulnerable or already disadvantaged, such as those who are physically susceptible to environmental or other health risks, are less than fully capable of representing their own interests, or are economically disadvantaged or vulnerable. Children, elderly people, those who are chronically ill or especially susceptible to a particular risk, low-income or minority communities, and local populations affected by a geographically concentrated risk or intervention are relevant subpopulations that may merit special consideration. Box 4-3 refers to the case studies to illustrate how information about populations disproportionately affected by a risk or an intervention might be presented in a regulatory analysis.

Children

Current Presidential guidance to federal agencies directs that particular consideration be given to the assessment of health and safety risks that disproportionately affect children. Each agency must, with respect to its rules, “to the extent permitted by law and appropriate, and consistent with the agency’s mission … address disproportionate risks to children that result from environmental health risks or safety risks” (EOP, 1997, Section 1). OMB Circular A-4 further instructs that, for any rulemaking action expected to result in an economically significant health or safety rule that may disproportionately affect children, the agency must evaluate the health or safety effects on children. This account should address why the proposed regulatory intervention was selected over other potential and reasonably feasible alternatives that the agency considered. The focus of these instructions, however, is more on avoiding disproportionate harms than on providing a greater degree of protection.

Circular A-4 also directs that agencies use CEA as the primary analytic framework when children are the predominantly affected group. Secondarily, a BCA may be conducted. However, whenever a BCA is conducted and benefits accrue to both children and adults, “the monetary values for children should be at least as large as the values for adults (for the same probabilities and outcomes) unless there is specific and compelling evidence to suggest otherwise” (OMB, 2003a, p. 31).

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

BOX 4-3
Distributional Considerations in Regulatory Decisions

Distribution of Impacts: Do the baseline (preregulatory) or postregulatory costs or risks disproportionately affect certain segments of the population?

  • The unborn or future generations

  • Infants and young children

  • Elderly people

  • Persons with disabilities or preexisting health conditions

  • Those particularly vulnerable to the risks of concern

  • Members of minority groups

  • Members of low-income groups

  • Those residing in particular geographic locations

Below are some brief examples of distributional considerations in the cases of food safety, air quality, and child restraints anchoring, based on information provided in the agencies’ regulatory analyses.


Food Safety: The juice processing regulation prevents foodborne illnesses, which can be especially severe for persons with poor immune system function, including people with human immunodeficiency virus, people receiving chemotherapy, and organ transplant recipients. Young children and elderly people are also likely to be more susceptible to more severe forms of these illnesses. Compliance costs are likely to be passed on to consumers of fresh juices, through very small but widely distributed increases in prices to cover production cost increases. Elderly people and young children consume somewhat more juice than the overall population on average.


Air Quality: Reductions in particulate matter due to cleaner exhaust from nonroad diesel engines and reduced sulfur in diesel fuel will disproportionately benefit elderly people, young children, and individuals with preexisting conditions. Reductions in premature mortality will accrue largely among elderly persons; infant deaths also will decrease. Cardiovascular disease will be reduced among older adults, as will acute episodes among those with preexisting cardiac disease. Acute respiratory episodes and hospitalizations will be reduced among persons with chronic respiratory conditions, such as asthma. Individuals who work in industries that rely on nonroad engines (e.g., construction, agriculture, industry, mining, and airports) may be disproportionately affected. Compliance costs are likely to be passed on to consumers of products in related markets. The EPA estimates that related price increases are likely to be less than 0.1 percent, however.


Child Restraints Anchoring: This regulation provides additional protection from the risk of injury or death for young children restrained in car seats. Compliance costs are likely to be passed on to consumers in the form of higher prices. The National Highway Traffic Safety Administration estimates that these costs will average $6 per vehicle and $17 per child restraint.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

These guidance documents reflect the exceptional value society places on children’s lives and well-being, as well as recognizing their particular susceptibility to serious and long-lasting harm from health and safety risks. Table 4-1 illustrates how the use of life years or QALYs, instead of preventable deaths, weights the health impacts for children more heavily, relative to impacts on older persons. As discussed in Chapter 3, the difficulties of valuing children’s health outcomes are both empirical and conceptual. Setting aside the practical problems of measuring HRQL for children, the concern remains that an individually based HRQL metric does not fully capture the high value placed on children’s well-being and health by parents and society. Although some have suggested that HRQL measurement should encompass the effects of an illness, injury, or disability on the entire family in which it occurs, this demanding approach has not been implemented.

Population Health Data and Subgroups

Another potential problem for valuation is that the major population health surveys exclude some subpopulations of concern. As discussed in Chapter 3, the National Health Interview Survey and the Medical Expenditure Panel Survey are household surveys, limited to noninstitutionalized, civilian populations. By design, excluded populations are homeless people; those who are migrant or have no fixed residence; and persons in prisons, group homes, nursing homes, and other institutions (Meyers and Andresen, 2000). Undocumented aliens, migrant farm workers, and others with reasons to avoid contact with government officials or data collection activities are unlikely to be represented in survey samples. In addition, members of these groups may be particularly susceptible to certain kinds of risks targeted by regulations, such as pesticide controls and workplace safety practices.

The exclusion of the groups just mentioned from routine population health surveys is also a problem for the valuation surveys underlying generic HRQL indexes, and calls into question the extent to which they can be assumed to represent accurately the values of the general population. The significance of this omission depends on whether the excluded groups represent a large enough percentage of the population to affect the survey results, and whether the values of excluded groups differ to a significant degree from the values held by those included in the survey. Although the recently conducted U.S. valuation survey for the EQ-5D used a stratified sample designed to include the three largest racial/ethnic groups in sufficient numbers to provide disaggregate results for whites, Hispanics, and non-Hispanic blacks, disaggregated results were not presented in the initial publications from this survey (Luo et al., 2005; Shaw et al., 2005).

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

Another issue with respect to low-income populations and some minority populations, such as blacks and Native Americans, is that their life expectancy is lower and their HRQL worse than that of others in the population (NCHS, 2004). If health gains are calculated for such subgroups based on subgroup population health status and longevity norms, then the potential to benefit from life extensions will be proportionately lower for these subgroups.

Calculation of Health Gains

Some health risks subject to regulation disproportionately affect those whose health is impaired already. In the case of air quality interventions, for example, the elderly and those with preexisting cardiac or pulmonary conditions are more likely to suffer adverse health effects. One of the most difficult issues to address is whether and how to disaggregate the general population in calculating gains in health due to a regulatory intervention. Both OMB guidance and the PCEHM’s recommendations for the reference case CEA direct the use of general population averages rather than health state index value estimates for subpopulations. (These requirements are discussed in more detail in Chapters 1 and 2; see Appendix C for the relevant text of Circular A-4.) The implications of these requirements for regulatory analysis depend on whether the general population is in fact representative of the population that achieves the health gains. For the types of economically significant health and safety regulations addressed by this report, the population affected will often reflect the same distribution of preexisting disabilities or health impairments as the general population. In such cases, using general population averages is analytically correct and will not disadvantage those who are disabled or in impaired health.

The OMB and PCEHM requirements are more problematic in a case where the affected population does not reflect the same distribution of preexisting disabilities or health impairments as the general population. For example, if individuals with heart disease represent 10 percent of the general population but 50 percent of the population affected by the regulation, using population averages may not accurately capture the QALY gains attributable to the rule.

In the air pollution example, reductions in preventable mortality may predominantly affect individuals with preexisting heart or respiratory conditions. Such deaths occur primarily among elderly people, and population averages for the affected age groups include a relatively high rate of heart and respiratory disease. EPA concluded that, because both the general population and the affected population in these age groups have comparably high rates of these preexisting conditions, the use of population averages

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

may provide a reasonable best estimate of the impacts of its rule. However, this conclusion is the subject of debate and scientific uncertainty.

It is also important to remember that the population affected undergoes changes in health status over time. Rules tend to remain in place for extended periods, however. Thus people who are not affected at the outset may develop conditions later such that a regulatory intervention is especially beneficial.

In cases where the health impairment or disability is related to the risk or intervention of interest, QALYs could unfairly value life-extending interventions for people with chronic illness or disability. For example, suppose decision makers are comparing two regulations that are equally costly, one of which affects only individuals with preexisting disabilities and another that affects individuals in better health. Also assume that the first intervention, which extends for 10 years the lives of 100 people with a chronic condition or disability valued at 0.75 (on a scale where 1.0 corresponds to optimal health and 0 corresponds to death), would produce 750 QALYs. If the second intervention extends for 10 years the lives of 100 people in near optimal health—0.95, for example—the gain would be 950 QALYs. In this case, focusing solely on the QALY gains would lead decision makers to select the second intervention, even though it extends the same number of lives as the first. Hence the use of QALYs for evaluating and prioritizing life-saving interventions appears to discriminate against people with impaired health or disabilities by assigning less value to extending their lives simply because of their disability. The reduction of average HRQL that occurs with increasing age produces the same general effect in comparisons between life extensions among 20-year-olds and 70-year-olds.

An alternative to assessing QALY gains based on comparison to actual health status is an approach that assumes that affected individuals would be in optimal health as a result of the intervention. As discussed in Chapter 2 (see Box 2-5), EPA recently presented QALY-based results that do not adjust life years gained to reflect the less-than-optimal HRQL that would be expected during those additional years of life (EPA, 2005a, Appendix G). Instead, EPA calculated health gains due to averted mortality as life years spent in optimal health.

In our case study of air quality improvements, we followed a different practice. We estimated the gain in QALYs due to increased life expectancy based on average health state values for the general population in each age group assessed. This approach assumes that, in the absence of the regulation-related risks, individuals would face the same degree of impairment as the average member of the U.S. population of the same age. The Committee concludes that EPA’s practice—which essentially gives greater weight to QALY gains from life extensions than from HRQL improvements—was less transparent than the alternative, namely to calculate all

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

QALY gains the same way regardless of whether morbidity or mortality is affected and to present those gains in disaggregated form so that the differences in the types of impacts are apparent. Appendix A provides additional discussion and presents the results of the Committee’s case study analysis.

The Treatment of Future Generations in CEA

Although many regulations have the potential to affect future generations, those where the costs are incurred primarily in the near term but the benefits occur largely in the future (or vice versa) pose particular ethical issues, especially if the effects of the policy are not easily reversible. Such is the case, for example, with regulations governing the construction of nuclear waste repositories. Construction may impose costs on the current generation, whereas future generations may be affected by the release of radiation if safeguards fail. Contaminants with reproductive or developmental effects provide other examples; controlling exposures among members of the current generation will benefit the subsequent generation. Assessing the impacts of these types of regulations poses analytic as well as ethical challenges regardless of whether BCA or CEA is used to estimate costs and benefits.

Future Effects

Perhaps the biggest issue associated with rulemakings relates to the ability to predict future conditions with and without the regulation. This problem pervades all aspects of the analysis. For example, Harrington et al. (2000) compared the predicted and actual costs of several regulations, and found that one of the key factors leading to overestimates of future costs was the difficulty inherent in predicting technological innovation. Such innovations may affect the benefits of a rule as well as its costs.

The regulatory analyses reviewed by the Committee applied varying approaches to addressing this problem (see Robinson, 2004, and Appendix A). For example, in the Food and Drug Administration’s (FDA’s) analysis of its juice processing rule, the agency assumed that current conditions remained constant, so that both costs and benefits were the same in each future year (FDA, 1998, 2001). In addition to presenting this annual value, FDA calculated the present value of costs and benefits over an infinite time horizon. In contrast, in its analysis of emission controls for nonroad diesel engines, EPA limited the time period addressed to 20 years and presented costs and benefits on an annual basis as well as in present value terms (EPA, 2004b). These estimates took into account the phase-in of regulatory requirements as well as predicted changes over time in pollutant emissions and in the demographic characteristics of the affected population. As re-

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

quired by OMB (2003a), regulatory analyses generally also present the timing of the undiscounted impacts.

This presentation of both discounted and undiscounted results is particularly important when costs and benefits are widely separated in time. If there is a lag between the costs and the effects, the estimates of cost-effectiveness will vary depending on the length of time that elapses as well as the discount rate used, regardless of whether the benefits are measured in dollars, QALYs, life years, or cases avoided.7 For example, if both costs and benefits are discounted, two regulatory options that differ only in the year in which benefits occur will have different present values if a positive discount rate is used. The regulatory option with the nearer term benefits will appear to be more cost effective. This outcome is derived from the underlying rationale for discounting, which reflects a general preference to receive benefits soon and delay costs.8Table 4-2 presents this issue in simplified form. As indicated in the table, the option without a lag between costs and benefits will be more cost-effective in present value terms when compared to another option with equivalent, but more delayed, benefits.9 This difference in present values increases as the discount rate increases.10

Future Generations

When risks are imposed or benefits accrue in the distant future, the ethical concerns and issues related to discounting are more difficult and less satisfactorily addressed. Moral obligations to future generations should be considered separately from the question of discounting practices.11 Present-

7  

In the majority of rules considered in the Committee’s review of current practices (Robinson, 2004), costs and reduced incidence of illness, injury, or death occur in the same or relatively proximate time periods. FDA’s analysis indicates that the reduction in the incidence of illness is likely to occur in the same year as the reduction in juice contamination. EPA makes the same assumption for changes in the incidence of the nonfatal effects of nonroad engine diesel emissions, while indicating that preventable mortality is distributed over a 5-year period after exposure.

8  

For example, most individuals generally would prefer to receive money today rather than at a later date because they can invest the money and earn interest. The present (discounted) value today of $100 received in a future year (t) is the amount that one would need to invest today to yield $100 in year (t).

9  

For simplicity, Table 4-2 assumes that the QALY losses all occur in a single year. However, for most chronic illnesses and for preventable mortality, a change in incidence in the current year will have future year effects, and these future year effects will also be discounted.

10  

See Portney and Weyant (1999), especially the essay by Weitzman (1999) for discussions of the interaction of the discount rate and the time period over which the discounting occurs.

11  

See, for example, “On Discounting Regulatory Benefits: Risk, Money, and Intergenerational Equity” (Sunstein and Rowell, 2005) for a discussion of this issue.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

TABLE 4-2 Discounting and Timing of Impacts

Time Period

Regulatory Option 1

Regulatory Option 2

UNDISCOUNTED RESULTS

Year 0

Costs = $100 million; benefits = 400 QALYs

Costs = $100 million

Year 10

Year 20

Year 30

Benefits = 400 QALYs

Cost per QALY

$100 million / 400 QALYs = $250,000 per QALY

$100 million/400 QALYs = $250,000 per QALY

RESULTS DISCOUNTED AT 3 PERCENT

Present value in year 0

Costs = $100 million; benefits = 400 QALYs

Costs = $100 million; benefits = 165 QALYs

Cost per QALY

$100 million/400 QALYs = $250,000 per QALY

$100 million/165 QALYs = $610,000 per QALY

RESULTS DISCOUNTED AT 7 PERCENT

Present value in year 0

Costs = $100 million; benefits = 400 QALYs

Costs = $100 million; benefits = 53 QALYs

Cost per QALY

$100 million/400 QALYs = $250,000 per QALY

$100 million/53 QALYs = $1.9 million per QALY

NOTES: For simplicity, this example assumes all the quality-adjusted life year (QALY) impacts occur in a single year and ignores the lifetime effects of chronic illness as well as the life years lost to premature mortality. It also does not provide information on the uncertainty in the estimates. All estimates are rounded to two significant digits.

ing undiscounted impacts, and their timing, along with a discussion of impacts on future generations, as OMB (2003a) advises, allows decision makers to identify situations where concerns about long-term impacts suggest that decisions should not be based simply on the discounted present value of the results.12 Such presentation is necessary because otherwise, discounting may lead the present generation to impose extremely high costs on future generations, resulting in undesirable welfare losses as well as inequities between generations (Revesz, 1999). In addition, discounting

12  

Chapter 2 discusses other aspects of the OMB guidance on discounting, such as the selection of the appropriate discount rate and the need for sensitivity analysis. Circular A-4 also describes the rationale for discounting nonmonetary as well as monetary measures of benefits in regulatory analysis (see Appendix C). In the context of health and medicine, Gold et al. (1996b) provide a detailed discussion of discounting, and recommend discounting both costs and benefits at 3 percent in the reference case and conducting sensitivity analyses using rates ranging from 0 to 7 percent.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

could give an undesirable priority to programs that would produce benefits more rapidly, but with substantially less overall improvement in health, when compared to programs that produce benefits later, but with substantially more overall improvement.

At the same time, a failure to discount could impose significant burdens on the present generation that regulatory interventions would alleviate. If regulators discount costs at a positive rate but value lives saved now and lives saved later equally, then the analysis paradoxically indicates that lifesaving spending should be postponed indefinitely, because the net benefit becomes increasingly favorable into the future (Keeler and Cretin, 1983). Furthermore, because future generations can reasonably be expected to inherit a richer and more technologically advanced world, there may be less reason to protect future generations from present choices (Weitzman, 1999). Others have suggested that the discounting of benefits to future generations might be thought of as part of a mutually beneficial intergenerational trade or contract (Lind, 1982).

How future benefits and harms (costs) are viewed is likely to depend on the perspective adopted. For example, parents will likely take a more precautionary attitude toward protecting the world their children and grandchildren will inherit than might people unaffiliated with younger generations.

Representing the interests of future generations in current policy discussions is difficult but ethically obligatory. Future generations will be affected by current decisions, particularly if the consequences are not easily reversed. As those involved in such discussions consider the future effects of their choices, they should factor in the implications of their decisions for those who will live in the future. Alternative normative frameworks—the “just savings” principle of Rawls’ social contract theory (1971, 1993), tort law, and utilitarianism—each can support a principle of compensation to guide discussion about the mix of benefits and costs that the present generation bequeaths to future ones (Sunstein and Rowell, 2005).

Comparing Cost-Effectiveness Ratios

The assumption underlying the use of CEA in regulation is that resources should be used to maximize the aggregate health status, or to minimize disease burdens, of a population. Some have suggested ranking regulatory programs from the lowest cost-per-QALY ratio to the highest, in order to identify better or more efficient investments in health production. Hahn (2005) has argued in favor of the use of such summary rankings, which he calls “regulatory scorecards” and which OMB has described as “league tables” (EOP, 2002). Although such scorecards enable compari-

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

sons across widely different interventions and provide useful information, they can mislead (Parker, 2003).

Given the many relevant features of decisions about the regulation of health and safety risks that are not part of the quantified economic analyses, and given considerable differences in the methodologies used to generate the summary results, the rankings of cost-effectiveness ratios are ambiguous. Furthermore, as discussed in Chapter 2, the legislative mandates and requirements for regulation vary across programs and agencies, making such comparisons less meaningful. Whether or not such cross-programmatic and interagency comparisons of CEAs might be helpful to decision makers, without being misleading, remains an open question. The Committee recommends against using summary rankings as the principal basis for policy decisions because the substance and methods of economic analysis do not support unqualified comparisons across widely different contexts.

IMPROVING REGULATORY DECISION MAKING

An important adjunct to the sorts of improvements in regulatory analyses discussed above is to strengthen the regulatory decision-making process itself. Such strengthening would involve greater transparency and ensuring a deliberative policy process that incorporates nonquantified information, including consideration of the distributive and ethical features of a proposed regulatory action. We discuss two fundamentally different strategies for introducing societal values and equity considerations into public policy decisions. One strategy is to incorporate information about distributive priorities directly into the CEA. This could either involve weighting health state index values to reflect priorities or stipulating values in the calculation of health-related effects. The other strategy is to pair the quantified economic analysis with qualitative information presented in a transparent and open process of regulatory development. The two approaches could also be combined.

Several approaches to societal weighting of health state index values have been proposed. First, standard index values could be modified with numerical factors or weights that convey priorities for age groups, severity of condition, or particularly vulnerable groups. These weights could be estimated by asking a representative sample of the general population to make PTOs between health improvements that are equal in terms of conventional index value gains, but different in terms of the characteristics of the people whose health is improved (Nord et al., 1999; Ubel et al., 2000). A variant on this approach would transform the health state index values into values that reflect societal values for giving priority to the worst off, which could be done by compressing the values of less severely impaired

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

health states toward the upper end of the 0-to-1 scale (Nord, 2001). By locating moderate health states closer to the upper end of the HRQL scale, the value of improvements for the moderately ill is reduced relative to improvements for the severely ill.

Another approach to building equity considerations directly into the cost-effectiveness ratio is to value all reductions in preventable mortality at 1.0, rather than at the postregulatory health state index value that is actually expected to pertain. This is the approach EPA adopted in its pilot CEA in the Clean Air Interstate rule (EPA, 2005a), as described earlier in this chapter and more fully in Box 2-5.

Despite their apparent usefulness and appeal in combining distributive concerns with health production, formula-based approaches to incorporating societal values into CEA calculations are problematic. First, there is no consensus as to how equity weights should be calculated, or even whether their use is appropriate. It is also difficult to adjust health state index values for more than one dimension; should that adjustment be for age, severity of condition, or initial health status? Second, valuing all gains in longevity as life years in optimal health, as with EPA’s Morbidity-Inclusive Life Year approach, changes the conventional relationship between morbidity and mortality effects and could lead to social choices that violate individual preferences in choices between quality and quantity of life (Johannesson, 2001). Finally, building equity considerations into the quantitative analysis in any of these forms makes the cost-effectiveness ratio less transparent, and therefore potentially more confusing and ambiguous for some.

In light of these concerns with adjusting health state index values to reflect distributional considerations, the Committee endorses a different strategy. In our view, standardizing the presentation of quantified analyses and their data inputs, assumptions, and methods offers the best chance for informed and transparent regulatory decision making. Presenting economic analyses in a common format and informing the deliberative process with alternative analyses helps to demonstrate how quantified results depend on value assumptions. Although we do not recommend that the CEA calculations be adjusted to incorporate distributional concerns quantitatively, we recognize that agencies might want to develop supplementary analyses using other measures and weighting schemes as sensitivity analyses. Such alternative quantifications could help to clarify the different implications of different regulatory strategies.

By including distributional and normative considerations in a public, transparent, and deliberative decision process, distinct concerns can remain separate. For example, how much should the fact that an auto safety requirement affects children count in judging the acceptability of its costs? A public and deliberative policy-making process permits the airing of reasonable disagreements about various priorities, rather than em-

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

bedding one version of them in the CEA calculations. A fair and transparent process can resolve open questions of value in ways that achieve and maintain legitimacy.

Daniels and Sabin (1997, 2002) have characterized a fair process for decision making about health and health care as having certain central requirements or features. In the following summary, the Committee adapts these conditions for a fair process to the regulatory context.

  • Publicity: The regulatory development process should be transparent and involve publicly available rationales for decisions affecting health and longevity. People have a basic interest in knowing the grounds for decisions that fundamentally affect their well-being.

  • Relevance: Those who are affected by regulatory decisions, including those who bear the costs of regulations as well as those who realize the benefits, must agree that the rationales rest on relevant reasons, principles, and evidence.

  • Revisability and Appeals: The regulatory process should make provisions for revisiting and revising decisions in light of new evidence and arguments.

  • Enforcement: There should be a mechanism for ensuring that the previous three conditions are met.

These conditions hold decision makers accountable for the reasonableness of their choices in regulating health and safety risks. Decisions that meet these conditions provide a form of “case law” that helps make future reasoning more coherent. Many of the issues underlying regulatory interventions, both matters of fact and of values, are points of disagreement. A fair and transparent process of this sort adds legitimacy to the results. It also contributes to societal learning about the appropriate grounds for making the kinds of trade-offs involved and thus enhances broader democratic processes over time. The demand for fair process is a fundamental part of our political system. It is embedded in the statutory and administrative requirements for regulating risks, as discussed in Chapters 1 and 2. Further progress towards the goals of fair and transparent risk regulation is possible.

CONCLUSIONS

The Committee’s key conclusions based on the discussion in this chapter follow.


CEA and BCA alike provide a useful but incomplete basis for informed societal decisions about reducing risks to human health and safety through

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

regulation. The most feasible and desirable way to account for ethical and normative considerations in regulatory policy is to include them explicitly in the deliberative policy-making process.


The choice of QALYs as the basis for measuring the production of health through regulatory interventions entails certain value commitments and ignores others, and these limitations should be made explicit in regulatory analysis. While some societal values regarding the distribution of health benefits could be incorporated through quantitative modifications of health state values, such adjustments are of questionable validity and make the quantification of health improvements more difficult to interpret. However, presenting the quantitative results of such alternative measures as sensitivity analyses may help to highlight those distributive implications in a way that promotes consideration of them in the deliberative process.


Presenting the components of summary economic analyses individually is an important contribution to the transparency and accountability of regulatory decisions because such disaggregated information may be easier to understand and it conveys the relative contributions of various health impacts to the summary results.


Public participation in the development of regulatory priorities and specific regulations is vital to well-informed policy making. Existing administrative procedures that govern the issuance of regulations provide a framework for publicity, transparency, public involvement, and accountability. They do not guarantee adequate citizen participation in setting regulatory agendas and rulemaking, however. Greater public understanding of the environmental, health, and safety risks and the benefits and costs of strategies to mitigate such risks can be promoted by well-conducted and clearly presented regulatory impact analyses.


The next and final chapter presents the Committee’s recommendations for regulatory analysis and policy development. Our recommendations reflect the conclusions above, as well as discussions and evidence that appeared earlier in this report.

Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 130
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 131
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 132
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 133
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 134
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 135
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 136
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 137
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 138
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 139
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 140
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 141
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 142
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 143
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 144
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 145
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 146
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 147
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 148
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 149
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 150
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 151
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 152
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 153
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 154
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 155
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 156
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 157
Suggested Citation:"4 Beyond Ratios: Ethical and Nonquantifiable Aspects of Regulatory Decisions." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×
Page 158
Next: 5 Recommendations for Regulatory Cost-Effectiveness Analysis »
Valuing Health for Regulatory Cost-Effectiveness Analysis Get This Book
×
Buy Hardback | $81.00 Buy Ebook | $64.99
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

Promoting human health and safety by reducing exposures to risks and harms through regulatory interventions is among the most important responsibilities of the government. Such efforts encompass a wide array of activities in many different contexts: improving air and water quality; safeguarding the food supply; reducing the risk of injury on the job, in transportation, and from consumer products; and minimizing exposure to toxic chemicals. Estimating the magnitude of the expected health and longevity benefits and reductions in mortality, morbidity, and injury risks helps policy makers decide whether particular interventions merit the expected costs associated with achieving these benefits and inform their choices among alternative strategies. Valuing Health for Regulatory Cost-Effectiveness Analysis provides useful recommendations for how to measure health-related quality of- life impacts for diverse public health, safety, and environmental regulations. Public decision makers, regulatory analysts, scholars, and students in the field will find this an essential review text. It will become a standard reference for all government agencies and those consultants and contractors who support the work of regulatory programs.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    Switch between the Original Pages, where you can read the report as it appeared in print, and Text Pages for the web version, where you can highlight and search the text.

    « Back Next »
  6. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  7. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  8. ×

    View our suggested citation for this chapter.

    « Back Next »
  9. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!