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Valuing Health for Regulatory Cost-Effectiveness Analysis (2006)

Chapter: 5 Recommendations for Regulatory Cost-Effectiveness Analysis

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Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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5
Recommendations for Regulatory Cost-Effectiveness Analysis

This report responds to a charge from a consortium of federal agencies to make recommendations for conducting cost-effectiveness analysis (CEA) to assess regulatory interventions affecting human health and safety. In particular, the Committee was asked to consider the theoretical soundness, feasibility, and ethical implications of health-adjusted life-year (HALY) measures in making our recommendations. The previous chapters review a number of issues related to the use of these measures in regulatory analysis, including current federal guidelines and agency practices (Chapter 2), various HALY measures and strategies for applying them (Chapter 3), and ethical and contextual considerations related to the use of these measures in decision making (Chapter 4). This final chapter presents the Committee’s conclusions based on the review and analysis described in the previous chapters, and its recommendations for conducting CEA in the regulatory setting.

The Committee drew on a variety of sources for insights, information, and evidence in determining how CEA could best inform regulatory decision making. These sources include:

  • Interviews with policy and analytic staff at federal agencies about how they currently assess the economic costs and benefits of environmental, health, and safety regulations;

  • Federal Executive Office of the President guidance on regulatory development, analysis, and reporting;

  • Regulatory impact analyses for proposed and final regulations from

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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federal agencies, including the Environmental Protection Agency, the Food and Drug Administration, the Food Safety Inspection Service, the National Highway Traffic Safety Administration, the Federal Motor Carrier Safety Administration, the Occupational Safety and Health Administration, and the Consumer Product Safety Commission;

  • Public workshop presentations by developers of health-related quality of life (HRQL) survey instruments and indexes, researchers in the fields of HRQL measurement and CEA, federal survey research officials, and ethicists;

  • Three CEA case studies developed by the Committee in collaboration with federal agency staff, based on published regulatory impact analyses for final rules governing air quality, food safety, and children’s car seat restraints; and

  • Reviews of the peer-reviewed literature on the performance of HRQL measures and methods, methodological research on CEA using health-related effectiveness measures, and empirical and theoretical ethical analyses of the use of HRQL indexes and HALYs in CEA.

The Committee’s investigations, analyses, and deliberations led us to the following overarching conclusions:

  • CEA, like benefit–cost analysis (BCA), offers a useful tool for the development and assessment of regulatory interventions to promote human health and safety. Different measures of effectiveness, including single-dimension measures such as life years and integrated metrics that combine estimates of HRQL and longevity such as HALYs, each provide useful and distinctive perspectives on regulatory impacts.

  • As in the case of BCA, the results of CEA for regulatory interventions are not by themselves sufficient for informed regulatory decisions. The results of economic analyses are routinely supplemented with other types of analysis, and with information from the public, to provide a more comprehensive assessment of the advantages and disadvantages of different regulatory strategies. These other sources of information are a necessary part of the decision-making process because it is not possible to quantify all of the impacts of concern.

  • It is feasible to apply CEA to regulatory interventions today, but additional data and improvements in the methods for measuring HRQL would make it more useful and reliable.

  • Federal regulatory agencies analyze disparate data and contemplate widely varying interventions and types of impacts from their actions. They use diverse approaches to value health-related benefits, partly because of these differences in data sources and types of impact, but also for reasons related to institutional history and precedent. Greater consistency in the

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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reporting of assumptions, data elements, analytic methods, and in the resulting estimates of costs, effectiveness, and benefits would increase the transparency and comparability of the results.

  • Presentations of cost-effectiveness ratios for diverse interventions can be misleading if they do not include information that highlights differences in methods, unmeasured effects, and distributional impacts across interventions.

Our recommendations for the use of CEA in regulatory analysis fall into four areas:

  • Selecting integrated measures of effectiveness;

  • Constructing and reporting cost-effectiveness ratios;

  • Providing additional information needed for decision making; and

  • Pursuing data collection and research necessary to improve HRQL measurement and regulatory CEA.

The recommendations are discussed in the following section and the chapter concludes with a brief summary.

RECOMMENDATIONS

Selecting Integrated Measures of Effectiveness

Because different effectiveness measures (e.g., deaths averted, life years saved, QALYs gained) have particular advantages and limitations, all regulatory CEAs should report more than one measure of effectiveness. Reporting a variety of measures provides decision makers with a richer understanding of the impacts of different regulatory choices and responds to different questions.

The Committee’s criteria for selecting integrated measures for use in regulatory CEA are summarized in Box 5-1.


Recommendation 1: Regulatory CEAs that integrate morbidity and mortality impacts in a single effectiveness measure should use the QALY to represent net health effects.

  • QALY estimates should be based, to the greatest possible extent, on research that considers the risk characteristics addressed and the population affected by the regulatory intervention.

  • The index values estimated for health conditions or health states of interest should be based on information from the population affected by the costs, benefits, or other impacts of the regulatory intervention,

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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BOX 5-1
Criteria for Selecting Integrated Effectiveness Measures for Health-Related CEA

Choices Among Health-Adjusted Life Year (HALY) Measures

Because the requirements for regulatory CEA are already in effect and analysts need tools that are ready for application, the Committee’s criteria for selecting among these HALY measures in the near term are largely practical ones:

  • The HALY metric should be widely used, and methods for estimating the index values as well as estimates for specific health states should be available in the literature.

  • The metric should be easy to understand and interpret.

  • The metric should be comparatively inexpensive to use, in terms of both providing immediately applicable methods and values and facilitating the development of values for additional health states.

In addition to these practical considerations, measures must also provide valid and reliable estimates of the relative value of different health states.


Choices Among Generic Health-Related Quality of Life (HRQL) Indexes

Because generic indexes are well established and easy to use, the Committee expects that they will often be applied in regulatory analysis in the near term. The Committee’s criteria for choosing among these indices focus on their suitability for regulatory analysis as well as the reliability and validity of the resulting estimates.

  • The HRQL instrument must be applicable to the range of health-related effects being evaluated.

  • The instrument should be sensitive enough to distinguish among health endpoints.

  • The instrument should reflect the values or preferences for health of the population of interest.

  • The instrument must be acceptable to and understandable by survey respondents, policy makers, and the general public.

  • The instrument should be as inexpensive to use as is compatible with the other objectives.

which for most economically significant regulations will be best represented by the general U.S. population.

  • In the absence of direct preference elicitation for health conditions of interest from the affected population, QALY estimates should be based on well-developed, generally accepted, and widely used generic HRQL indexes whose valuation is based on general population samples.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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  • The characterization of the health states or conditions of interest using generic HRQL indexes should be based on information obtained from people who are familiar with the conditions, such as patients.

The QALY is the best measure at present on which to standardize HALY estimation because of its widespread use, flexibility, and relative simplicity. As discussed in Chapter 3, alternatives to the QALY measure, including the healthy year equivalent, the saved young life equivalent, and the disability-adjusted life year, are either less feasible, have not been used extensively or evaluated, or incorporate features that render the measure not comparable with QALY results. For regulatory analysis, the QALY is best thought of in practical terms, as a measure of health improvement or production that allows analysts and decision makers to compare the impacts of different interventions. In short, we recommend the QALY as a useful construct on which to standardize the accounting of changes in health and longevity.

QALY estimates of regulatory effects may be based either on newly collected information or on previously conducted research. In both cases, the QALY estimates should address the same health states (i.e., the specific types of disease or injury) as identified in the risk assessment for the regulatory analysis. For example, the health states should be similar in terms of the severity and duration of the symptoms and of the effects of treatment. For chronic or long-term impacts, it may be desirable to separately assess different phases to reflect the variation in the HRQL impacts at different points in time. The QALY estimate also should reflect, to the extent possible, the effect of the health state on the particular population affected by the regulatory intervention in terms of characteristics such as age, preexisting conditions, income, and geographic location. If the HRQL estimate reflects a health state or scenario that differs from the regulatory health endpoint (i.e., addresses a somewhat different condition or affected population), these differences should, to the extent possible, be discussed and addressed in the uncertainty analysis. (See Recommendation 6.)

Chapter 3 discusses alternative strategies for developing QALY estimates for use in regulatory analysis. Briefly, these include:

  • Eliciting preferences directly for the health states of interest, through a new valuation survey of the population that bears the costs and receives the benefits of the proposed regulation.

  • Using generic health indexes to characterize and value the health states of interest. Health states may be characterized through surveys of patients or physicians knowledgeable about the condition of interest. This descriptive step is separate from the valuation of these health states, which

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

ideally should be derived from a survey of a representative sample of the population affected by the costs and benefits of the rule.

  • Using previously published health state and/or condition values. Such previously published values may have been either directly elicited or estimated with generic indexes.

Due to time and budget constraints, the Committee recognizes that, in the near term, regulatory analysts are likely to rely on published research and to adopt relatively simple approaches to assess health-related impacts in regulatory CEAs. Over the long term, the Committee hopes that investment in additional research will improve the information available for these assessments. (See Recommendations 11 and 12.)

Different approaches in different regulatory analyses may be required to pursue the dual objectives of (1) ensuring that the health states and populations addressed in the QALY analysis match those identified in the risk assessment and affected by the intervention, and (2) using ethically sound and robust societal valuations of health states. The best approach will depend on the time and resources available and the extent and quality of existing valuation research for the conditions of interest. Because these factors vary, it is not possible to specify one standard approach for QALY-based CEA that would apply in all cases. Regulatory analysts must exercise judgment in weighing the importance of different factors in choosing an approach to QALY estimation. The following discussion summarizes the Committee’s conclusions from Chapter 3 and offers guidance regarding the use of existing HRQL research and generic indexes for QALY-based regulatory analysis.


Valuation. Health states can be valued directly in surveys of patients or the general population using elicitation techniques such as the standard gamble, time trade-off, category rating (e.g., visual analogue scale), and person trade-off. When a generic index is used, health states are described by locating their attributes within the functional categories or domains of the index. These domain attributes are then valued using a statistical model or algebraic formula based on a separate valuation survey that employed one or more elicitation methods. The underlying valuation surveys for the various generic indexes are based on general population surveys that differ in size and in the extent to which they represent the U.S. population as a whole (see Table 3-4).

For regulatory analysis, the population valuing different health states should include both those who will benefit from the intervention and those who will bear its costs. In the case of economically significant regulations that have relatively large costs and/or benefits, the affected population

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

whose valuations are of interest is usually best represented by the U.S. population.

Elicitation methods that include an explicit choice, such as the standard gamble and time trade-off, would be preferred to other methods of preference assessment if they were more comprehensible and more easily administered. However, standard gamble and time trade-off methods are difficult for many respondents to understand, and often lead to inconsistent or poorly reproducible responses. Although category rating and visual analogue scale methods do not imply a direct trade-off between years of life and HRQL (a trade-off that is implicit in QALY-based CEA), they are generally easy to administer. Particularly if they are calibrated against tradeoff methods to ensure that the same numerical rating means the same thing for both types of methods, rating scale elicitation methods can also play an important role.

Methods that elicit individual preferences for health have dominated QALY-based CEA. However, alternatives (such as the person trade-off method) that aim to elicit societal values for investments in health improvements more directly merit further development, as discussed in Recommendation 12. The aggregation of individual preferences for one’s own health is but one approach to determining societal preferences for improved health, and evidence suggests that values for health states elicited in the standard way may not be well correlated with societal health resource allocation choices (Ubel et al., 1996).


Generic indexes. The Committee reviewed, and applied in its case studies, several generic HRQL indexes. These included the Quality of Well-Being Scale (QWB), the Health Utilities Index (HUI) Marks 2 and 3, the EuroQol-5D (EQ-5D), and the SF-6D. As discussed in Chapter 3, we concluded that no generic instrument is superior in all respects to the alternatives. All four of these instruments have well-developed and widely tested survey formats. Health state values based on the QWB, HUI, and EQ-5D are well represented in the published literature and, because the SF-6D can be calculated from SF-36 and SF-12 health profile data, it has the potential for extensive application.

Recent research suggests that these four generic instruments rank-order health states consistently, although the absolute values of individual health states differ depending on the instrument used (Franks, 2004; Franks et al., 2006). Furthermore, a growing research literature offers statistical conversions or translations of values from one instrument to another; see Table 3-7 for a summary of these studies.

These instruments do vary, however, in the representativeness of their underlying valuation surveys and in specific aspects of their methodology.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

The QWB’s valuation survey dates back to the mid-1970s, was based on a San Diego community sample, and uses a rating-scale methodology. The HUI attributes were valued by a sample from a metropolitan population in Ontario, Canada. The SF-6D values were derived from a U.K. population survey. The EQ-5D is the only generic instrument with a nationally representative U.S. valuation survey underlying its index values. In addition, some of the instruments (e.g., the HUI) require licensing fees, and others involve fees to access health profile data (e.g., as would be useful with the SF-6D). Given the current state of the art of HRQL measurement, the Committee recommends that agencies consider using the EQ-5D in their primary estimates for regulatory analyses at this time.


Characterizing health states with generic indexes. Using generic indexes to measure HRQL involves characterizing or locating the health states of interest according to the specific functional categories or domains of the index. In contrast with direct preference elicitation surveys, with generic indexes this characterization of health states is separate from the valuation of the generically described health states, where the latter is based on general population samples.

As described in Chapter 3, health states can be characterized using generic indexes either by patients or clinical experts who are familiar with the condition of interest. Published studies are one source of patient-based characterization or description of health states using these indexes. If original data collection for a regulatory analysis is contemplated, direct elicitation of health state index values for the conditions of interest, rather than patient characterization using a generic health index, should be considered. If neither of these approaches is feasible, then clinical experts could be asked to characterize the health conditions of interest using a generic index, similar to the approach used in the Committee’s case studies. Good practices for expert assessment are discussed in Chapter 3.


HRQL measurement quality. Finally, the Committee recommends that sources of HRQL values for QALY-based CEA should be evaluated with specific and consistent criteria regarding:

  • The quality of underlying valuation surveys; and

  • The precision and reliability with which health states of interest are captured or located by direct elicitation or generic indexes, respectively.

Although it is not possible to develop absolute standards for assessing an existing study’s quality and applicability for regulatory CEA, greater specification and standardization of quality review criteria in HRQL measurement will help analysts to (1) weigh the limitations of a study against the

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

value of using it, and (2) determine when available valuation studies should not be used as a source of health state values in the context of a particular analysis.

There is a growing body of evidence on the quality of different valuation techniques and surveys, and formal criteria are being developed for judging quality in survey-based valuation research that addresses both willingness-to-pay and QALY estimation.1 Such criteria for evaluating study quality should be further developed and applied to HRQL valuation research. For example, more attention should be given to internal consistency tests. Chapter 3 provides additional information on the research underlying generic indexes and these criteria.

Constructing and Reporting Cost-Effectiveness Ratios

The overarching objective of the Committee’s recommendations is to improve the quality and comprehensiveness of the information available for regulatory decision making. We believe this objective can be advanced by standardizing, to the extent practical, the structure of CEAs within and across agencies, thus increasing the transparency of the presentation of analytic assumptions, methods, and results in regulatory analyses.


Recommendation 2: Regulatory analyses should report four measures of cost-effectiveness:

  • Compliance cost per death averted using the net number of deaths averted as the outcome measure.

  • Compliance cost per life year gained using the net change in years of preventable mortality as the outcome measure.

  • A health-benefits-only ratio using the net change in QALYs as the outcome measure. Costs would include those associated with compliance, offset by estimates of the net changes in health care treatment costs associated with the outcomes included in the QALY measure.

  • A comprehensive ratio using QALYs as the outcome measure and incorporating the value of other benefits as offsets to compliance costs. The cost measure would incorporate both net changes in health care treatment costs and the value of any monetized nonhealth benefits as offsets.

The components of these four ratios are illustrated in Table 5-1.

1  

See Freeman (2003, Chapter 6) and OMB (2003a) regarding criteria for willingness-to-pay studies and Chapman et al. (2000), Neumann et al. (2000), and AHRQ (2005) for criteria for QALY-based CEA.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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TABLE 5-1 Components of Cost-Effectiveness Ratios

 

Compliance Costs Per Death Averted

Compliance Costs Per Life Year Gained

Health-Benefits-Only Ratio

Comprehensive Ratio

Included in net costs

Regulatory compliance costs

Health care treatment cost savings

 

 

Value of nonhealth benefits

 

Included in net effects

Fatal effects: Deaths averted

 

Fatal effects: Years of life gained

 

Fatal effects: Quality-adjusted life years gained

 

 

Nonfatal effects: Quality-adjusted life years gained

 

 

Ratios need not be reported if they do not provide additional information for decision making. For example, compliance cost per life year gained need not be presented when a regulation would have negligible impacts on longevity, and the comprehensive ratio need not be presented for regulations that do not provide monetized nonhealth benefits.

These ratios should be calculated over a time period selected to reflect the effects of the full implementation of the regulation. In addition, annualized impacts should also be reported and used to estimate expected cost-effectiveness on a yearly basis. The time periods within which the costs and savings and the health-related effects accrue should be reported using a time line to indicate the undiscounted impacts expected in each year. In addition, the present value of the impacts should be calculated using the same discount rate for both costs and effects (life years or QALYs). As discussed in Recommendations 8 and 9, agencies should also highlight information on distributional impacts and ethical considerations, on uncertainty in the estimates, and on any regulatory impacts not included in the cost-effectiveness measure.

A simplified example of the four recommended cost-effectiveness ratios, as well as the results of an accompanying BCA, is provided in Box 5-2.

The Committee recommends reporting all four cost-effectiveness ratios because no single formulation will be ideal in all circumstances. Different audiences will find different formulations more informative, more readily interpretable, or more comparable to other analyses. Furthermore, differ-

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

BOX 5-2
Example of Cost-Effectiveness Ratios

Values used in example:

Regulatory compliance costs:

$100 million

Benefits values (willingness to pay) for BCA:

$60 million for averted mortality

$30 million for averted morbidity

$40 million for averted ecological impacts

Benefits values for CEA:

400 QALYs gained

or

100 life years saved

or

10 premature deaths averted

Health treatment cost savings associated with reduced morbidity and mortality:

$20 million

Net benefits:

Net benefits = ($60 million + $30 million + $40 million) − $100 million = $30 million

Cost-effectiveness ratios:

  • Compliance costs per premature death averted = $100 million / 10 lives = $10 million/death averted

  • Compliance costs per life year gained = $100 million/100 life years = $1 million/life year

  • Costs per QALY, health benefits only = ($100 million − $20 million) / 400 QALYs = $200,000/QALY

  • Costs per QALY, comprehensive = ($100 million − $20 million − $40 million) / 400 QALYs = $100,000 / QALY

NOTES: For simplicity, this example provides the results for a single year and ignores the need to address the timing of the impacts. It also does not provide information on the uncertainty in the estimates. For simplicity we assume that the willingness-to-pay estimates used in the BCA calculation of net benefits encompass health treatment cost savings. See Chapter 2 and OMB, 2003a (Appendix C), for more discussion of this issue.

ences among potential interventions in the relative size or ranking of the four measures can highlight important aspects of the impact of alternative interventions. While agencies should report these four ratios at a minimum as relevant, they may also, at their discretion, provide additional comparisons that incorporate alternative perspectives if such comparisons are useful for decision making.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

Each of the four formulations has particular advantages.


Compliance cost per death averted. This ratio focuses on the number of deaths averted, without regard for the expected years of life extended by a regulatory action. It is the simplest of the four ratios and excludes consideration of the HRQL for the life years gained, of nonfatal health impacts, of medical care savings, and of benefits that are not health related. This ratio avoids the criticism leveled at cost-effectiveness formulations that use some form of life years as the effectiveness measure, namely, that they discriminate against older people and those with lesser life expectancies. All preventable deaths count equally in this calculation.


Compliance cost per life year gained. This ratio is also limited to the mortality effects of a regulatory action and sets aside impacts on health status, but considers the years of life extension rather than simply the number of lives extended. It excludes consideration of the health-related quality of life for the life years gained, of nonfatal health impacts, of medical care savings, and of benefits that are not health related. This ratio may be more acceptable or understandable to those who find it difficult to interpret QALY measurement. It may be most important to those who are concerned primarily with the mortality impacts of the regulations or who are ethically opposed to reflecting HRQL differences in conveying information about preventable mortality.


Health-benefits-only ratio. This formulation is most comparable to and in harmony with the approach used as the reference case for CEAs that address public health and medical interventions. It answers the question of what it costs to produce a particular unit of health—that is, a QALY—that incorporates information on the HRQL impacts for both nonfatal illness and injury and life years lost. In this formulation, information about nonhealth benefits is not included in the ratio, but would be provided by listing and highlighting these effects in accompanying narrative.


Comprehensive ratio. For some regulations, the BCA will include the monetary valuation of benefits unrelated to health, such as ecological effects. In these cases, a comprehensive ratio should be reported. In most of these regulations, the costs of achieving the health and non-health benefits are not separable, and attributing all costs to the achievement of the health benefits can be misleading. Disregarding those impacts excluded from the previously described quantitative measures would result in decisions that underinvest in regulations that provide nonhealth as well as health benefits. The comprehensive ratio offers a more global perspective by incorporating a fuller set of implications of the regulatory action, and uses more of the

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

available information about regulatory impacts.

When evaluating different regulatory options, analysts may find that the relative magnitudes of health and nonhealth benefits vary among options. If so, then the comprehensive ratio could lead to a different ordering (in terms of economic efficiency) of policy alternatives from the one that would emerge from the health-only ratio. The comprehensive approach is most consistent with the content of the accompanying BCA.


Definitions: The following definitions should be used in developing each component of the ratios:

  • Deaths averted: the net change in the expected number of cases (sometimes referred to as “statistical cases”) of preventable mortality attributable to the regulation, summed across the affected population.

  • Life years gained: the net change in the predicted years of life extension attributable to the regulation, summed across the affected population.

  • Quality-adjusted life years gained: the net change in health-related quality of life associated with morbidity, injury, and preventable mortality attributable to the regulation, summed across the affected population.

  • Regulatory compliance costs: the net value of the materials, labor, and other inputs used to comply with the requirements of the regulation, and the impact of these net costs on related markets.

  • Regulatory benefits: the net impacts related to the goals of, or rationale for, the regulation, including health benefits (averted morbidity, injury, and mortality) and nonhealth benefits (e.g., enhanced recreational value or increased protection of natural resources).

  • Health-care-treatment-cost impacts: the net change in resource and time costs as a result of reduced need for medical treatment for the condition(s) affected by the regulatory intervention.

Sometimes it is difficult to make clear distinctions among these categories; however, they generally should include the following.

Deaths averted reflects the comparison of the predicted number of deaths in the population without the regulation to the number of deaths with the regulation. Conceptually, these deaths reflect the net number of people expected to live longer once the regulation is implemented. They are often calculated as statistical cases (changes in the risk of preventable mortality summed across a population). This measure should be calculated as the net change; that is, they should include both increases and decreases in the risks of preventable mortality attributable to the regulation, and information on related uncertainties should be presented along with the quantified estimates.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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Life years gained reflects the comparison of life expectancy of the affected population in the absence of the regulation to life expectancy with the regulation in place. These estimates are not adjusted for the quality of life, and should reflect the actual predicted change in the life expectancy of the affected population to the maximum extent possible given available data. Any limitations of the data used to predict life expectancy should be included in the assessment of the uncertainty in the estimates and modeling.

QALYs gained reflects the net changes in HRQL and HRQL-adjusted life expectancy in the affected population without and with the regulation, including the HRQL impacts of morbidity, injury, and preventable mortality.

Regulatory compliance costs reflect the resources diverted from other purposes to meet the specific legal requirements established by the regulation. Costs may include, for example, those associated with testing for contamination, installing airbags in cars, or administering a new program. Where such costs lead to noticeable market impacts (e.g., decreased demand due to increased prices in the regulated industry and/or spillover effects in related sectors), these “second-order” consequences should also be included. In addition, compliance costs should include any significant savings that result. For example, if standards for vehicle engines result in fuel savings, these should be included as offsets to compliance costs.

Regulatory benefits generally relate to the goals of, or rationale for, the regulation. For health and safety regulations, these benefits will include the effects of the regulation on morbidity, injury, and preventable mortality, but may also include nonhealth benefits. Again, these effects may include “second-order” consequences if significant; for example, a chemical used to remove contaminants from drinking water may itself pose risks or can lead to additional risk reductions by removing co-occurring contaminants. Benefits may include some offsetting increases in risks.

Health-care-treatment-cost impacts are the net changes in health-care-related costs as a result of the regulation. These impacts are defined by the U.S. Panel on Cost-Effectiveness in Health and Medicine (PCEHM) as including “changes in the use of health care resources, changes in the use of non-health care resources, changes in the use of informal caregiver time, and changes in the use of patient time (for treatment)” (Gold et al., 1996b, p. 177).2 In the case of regulations that prevent the occurrence of health conditions, these impacts are generally additional savings attributable to the regulations. In BCA, these impacts (if estimated) are usually counted as benefits to the extent that they do not double count other monetary estimates of impacts. In CEA, they should be counted as offsets to regulatory costs under both the health-only and comprehensive approaches.

2  

The PCEHM definition of treatment-related costs is discussed more fully in Chapter 1.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

The Committee recognizes that in some cases the distinctions among the categories defined above may be difficult to determine, and analysts will need to rely on their own judgment. Judgment will also be needed to separate effects that are negligible and need not be quantified from effects that are significant and warrant inclusion in the analysis. Regardless, the rationale for including and excluding various impacts for each of these ratios, or for excluding impacts entirely from the quantitative assessment, should be included in the text of the regulatory analysis.

In reporting these measures, the agencies should make every effort to ensure that the results and limitations are reported clearly. Although OMB and agency guidance already emphasize the need for transparency, the Committee found that these qualities were lacking in many of the regulatory analyses it reviewed. To meet this goal, agencies should present summary materials describing the analyses in nontechnical language, including key definitions and assumptions, that can be easily understood by the general reading public. In addition, they should discuss data sources, calculations, results, and the implications of nonquantified effects as well as uncertainty in the quantified results.


Recommendation 3: The life-year and QALY estimates used in regulatory analyses should reflect actual population health as closely as possible, comparing the predicted HRQL and life expectancy of the affected population in the absence of the intervention (i.e., the regulatory baseline) to the predicted postintervention HRQL and health-adjusted life expectancy.


The economically significant regulations most directly affected by the Committee’s recommendations will often have national impacts. However, the characteristics of the population affected by associated health risks may differ from the characteristics of the general U.S. population. For example, foodborne illness may be more severe in individuals with weakened immune systems; certain car safety problems may disproportionately affect children; and air emissions may lead to preventable mortality primarily among the elderly. In some cases, the analysis may not fully reflect the characteristics of these affected populations due to limitations in the available data. In these cases, the data limitations should be included in the uncertainty analysis discussed under Recommendation 6.

However, as discussed in Chapter 4, some practitioners have argued that the HRQL results should be adjusted to reflect equity issues; for example, higher QALY values could be assigned to subpopulations of concern such as the elderly, children, or those with preexisting conditions. The Committee believes that such approaches should be avoided for two reasons: (1) they lack transparency, and (2) they substitute the analyst’s judg-

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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ment about relative values for the deliberative process (see Recommendations 8 and 9).

The intent, as well as the underlying theory and methods, for preparing most components of regulatory CEAs (and BCAs) is to compare the relative economic efficiencies of alternative interventions. Equity weighting confuses the message; it becomes difficult to separate the extent to which a particular intervention appears preferable due to its economic efficiency from its equity impacts. In addition, there is no agreed-on set of weights for any subpopulation of concern. The Committee believes that the analysis should include the best available information about the impacts on groups of concern so that it can be incorporated into the deliberative decision-making process. Decision makers are better served by CEAs that clearly represent the actual impacts of regulations, supplemented by information that emphasizes the equity impacts.

The Committee’s judgment is that the more comprehensive information needed to address equity considerations in policy decisions is not well suited for incorporation into cost-effectiveness ratios. The recommended formulations of cost-effectiveness ratios also reflect the value judgment implicit in the QALY measure to value life years rather than lives, and to adjust for quality. One consequence is that less weight is placed on permanent changes in HRQL for those with fewer remaining years of life, and on life extensions for those who have worse-than-average quality of life. Recognizing these concerns, we conclude that equity issues are better addressed as part of the discussion of distributive impacts of the intervention rather than by quantitative weighting of the QALY measure.

Age- and sex-specific U.S. population HRQL averages exist for four of the generic indexes used in the Committee’s case studies. (See Hanmer et al., 2006, for population norms for several indexes.) For many regulations, these general population averages are likely to provide the best available estimates of the postregulatory (i.e., generally, improved) health of the affected population. Using age-specific population averages marks an advance over many studies published in the CEA literature that use an index value of 1.0 (perfect or optimal health) to assess health status in the absence of the condition of concern.

This practice could be further improved, however, by the development of better information on the extent to which persons who are likely to be affected by a regulatory intervention also have other health conditions or co-morbidities, on the extent to which these co-morbidities are affected (in terms of increases or decreases) by the regulations, and on the effect on HRQL of eliminating one health impairment when another remains.


Recommendation 4: Incremental cost-effectiveness ratios are generally the most useful summary measure for comparing different regulatory interven-

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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tions. Such ratios are not meaningful, however, for interventions that reduce both costs and risks. Options that are dominated (i.e., have higher costs and lower effectiveness) also should not be included in the incremental comparisons.


Before incremental cost-effectiveness ratios are calculated, the analyst should determine whether any of the options are both more costly and less effective than other options. These options are dominated by the other options. The dominance should be reported, but cost-effectiveness ratios need not be calculated. Incremental cost-effectiveness ratios are usually calculated relative to all other alternatives that are not dominated. The determination of dominance may vary across the different ratios discussed under Recommendation 2. For example, one ratio may dominate another but still not be optimal if it is in turn dominated by, or at least broadly considered inferior to, some third strategy. In addition, uncertainty must be taken into account in determining dominance. If some elements of the CEA are particularly variable, the analyst will need to consider the probability that an alternative is dominated under different assumptions. The discussion of Recommendation 6 addresses this further.3

Whenever the value of a cost-effectiveness ratio is negative (i.e., it is both cost saving and health enhancing, or both costly and results in net life year or QALY losses), ratios should not be calculated or reported because they are not meaningful and cannot be interpreted. The underlying estimates of net costs and net effects are informative, however, and should be reported.

The results for each nondominated option should be independently compared to each of the other nondominated options. The ranking of interventions and whether they are dominated can vary among these ratios. So, for example, in Table 5-2, intervention B dominates C on compliance costs/life year saved, and is dominated by C on comprehensive costs/QALY gained.


Recommendation 5: In addition to reporting effects in the aggregate, regulatory analyses should report QALY impacts separately for each health endpoint. Impacts should also be reported in terms of single-dimension measures such as avoided cases of disease and cause-specific mortality averted.

To make the analysis more transparent and to provide more complete information for decision making, the QALY gains attributable to each

3  

See Hunink et al. (2001, Chapter 9) and Drummond et al. (1997, Chapter 5) for extended treatments of how to calculate and use incremental cost-effectiveness ratios.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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TABLE 5-2 Comparison of Cost-Effectiveness Ratios

 

Intervention A

Intervention B

Intervention C

Input data

Compliance costs

$100 million

$140 million

$200 million

Health care cost savings

$10 million

$5 million

$10 million

Value of other (nonhealth) benefits

$40 million

$100 million

$200 million

Averted mortality

8 cases

10 cases

9 cases

Life years gained

250 life years

300 life years

280 life years

Quality-adjusted life years (QALYs) gained

2,000 QALYs

800 QALYs

1,000 QALYs

Cost numerators

Compliance costs

$100 million

$140 million

$200 million

Compliance costs net of health care savings

$90 million

$135 million

$190 million

Compliance costs net of health care savings and other benefits

$50 million

$35 million

Savings of $10 million

Incremental cost-effectiveness

Compliance costs per death averted

$13 million per case

$20 million per additional case

Dominated by B

Compliance costs per life year gained

$400,000 per life year

$800,000 per additional life year

Dominated by B

Compliance costs net of health care savings per QALY gained

$45,000 per QALY

Dominated by A

Dominated by A

Compliance costs net of health care savings and other benefits per QALY gained

$25,000 per QALY

Dominated by C

Cost saving

NOTES: For simplicity, this example provides the results for a single year and does not report information on the uncertainty in the estimates. All results are rounded to two significant figures. Estimates of life years and QALYs represent the discounted lifetime impacts of the new cases averted in a single year. For example, a case of premature mortality in the current year leads to life year losses equivalent to the individual’s expected remaining life span.

regulatory option should be reported on a disaggregated basis. Detailed breakouts provide additional information for decision makers on the relative importance of different types of effects. Several types of disaggregation are desirable.

First, the QALY estimates should be reported separately for each health endpoint or condition, for example, preventable deaths, particular types of chronic health effects (e.g., heart disease, lung cancer), specific

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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types of acute, time-limited health effects (e.g., gastrointestinal illness from a foodborne pathogen), and types of acute exacerbations of chronic conditions (e.g., an acute asthmatic episode). Net changes in expected life years should be calculated first and then adjusted for HRQL, so that only preventable mortality is reflected in the first estimate. Second, the analyses should report single-dimension estimates of impacts for each endpoint, for example, the estimated number of cases of illness, injury, or mortality averted and the number of life years saved. Table 5-3 illustrates these reporting recommendations.

Third, to the extent that the regulation is likely to disproportionately affect certain population subgroups of concern, impacts should be reported separately for each group (e.g., for children, elderly people, low-income populations, members of minority groups, and those with preexisting conditions, as relevant). The treatment of distributive impacts is discussed further under Recommendation 8.


Recommendation 6: The reporting of all CEA results should be accompanied by information on related uncertainties and on nonquantified effects.


Uncertainty in estimates of the costs and health-related effects of regulatory actions are attached to each component and accompany every step of

TABLE 5-3 Disaggregated Impacts

 

Intervention A

Intervention B

Intervention C

Quality-adjusted life year (QALY) impacts

 

Averted mortality

200 QALYs

240 QALYs

220 QALYs

Averted incidence of heart disease (morbidity only)

1,700 QALYs

520 QALYs

600 QALYs

Averted asthma exacerbations

100 QALYs

40 QALYs

180 QALYs

Total

2,000 QALYs

800 QALYs

1,000 QALYs

Single-dimension impacts

 

Averted mortality

8 cases; 250 life years

10 cases; 300 life years

9 cases; 280 life years

Averted incidence of heart disease

85 cases

26 cases

30 cases

Averted asthma exacerbations

30,000 events

12,000 events

54,000 events

NOTES: For simplicity, this example provides the results for a single year and does not provide information on the uncertainty in the estimates. All results are rounded to two significant figures. Life-year and QALY estimates represent the discounted lifetime impacts of the new incidence. For example, the 26 to 85 new cases of heart disease are likely to lead to QALY impacts over each individual’s remaining lifespan; hence the QALY impacts exceed the number of cases averted.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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a CEA. Because BCA and CEA rely on much of the same data and employ many of the same tools, they face similar challenges in dealing with uncertainty in their results. For the common components of these analyses (e.g., the estimates of compliance costs and of cases of illness or injury averted), the treatment of uncertainty should be symmetrical across BCA and CEA. CEA, however, presents some particular challenges for analysis of uncertainty.4

Uncertainty means that regulatory alternatives that compare unfavorably in terms of both their costs and effectiveness (i.e., that are dominated) may still be worth considering if they involve substantially different technologies or intervention from the better performing alternatives. For example, when regulatory options differ only in stringency (e.g., a standard of 1 versus 5 parts per million), then dominated options should be excluded from the comparison. When options differ in other respects, such as warning labels versus mandatory processing standards for food contaminants, options that are only slightly dominated may be worth considering because the sources of uncertainty may be quite different for alternative interventions.

One common source of uncertainty is the inability to quantify or value in monetary or QALY terms some potentially important health and nonhealth impacts. Agencies should report these impacts, including, for example, preclinical physiological changes that are difficult to evaluate and effects on pregnant women that could affect fetal development. An example of a format for reporting these types of effects is provided in Table 5-4, from the Environmental Protection Agency’s (EPA’s) regulatory assessment of the nonroad diesel rule (EPA, 2004b).

In addition, the quantified estimates will often contain significant uncertainties. An earlier National Research Council committee reviewed EPA’s work in estimating the health benefits of air pollution regulations. That committee recommended that the sources of uncertainty in impact analyses should be considered jointly in the primary analysis, rather than singly, so that the probability distributions describing ultimate effects (e.g., cases of illness avoided) and their values (e.g., QALY losses avoided) would be calculated correctly (NRC, 2002). The OMB 2003 guidelines for regulatory

4  

See Fenwick et al. (2004), Heitjan (2000), and Willan and O’Brien (1996) for discussions of these issues and of alternative approaches to statistical analysis of cost-effectiveness data. See also Estimating the Public Health Benefits of Proposed Air Pollution Regulations (NRC, 2002), which considers sources of uncertainty and offers guidance on the reporting of uncertainty in regulatory analysis. The use of ratios in CEA raises issues that do not occur in addressing uncertainty in BCA. For example, when zero is a possible value for the effectiveness measure, infinity becomes a possible value for the ratio, and the statistical expectation of the ratio is thus also infinite.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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TABLE 5-4 Nonmonetized Benefits of the Environmental Protection Agency’s Nonroad Diesel Rule

Pollutant/Type of Impact

Nonquantified Effects

Ozone health

Premature mortality.

Respiratory hospital admissions.

Minor restricted activity days.

Increased airway responsiveness to stimuli.

Inflammation in the lung.

Chronic respiratory damage.

Premature aging of the lungs.

Acute inflammation and respiratory cell damage.

Increased susceptibility to respiratory infection.

Nonasthma respiratory emergency room visits.

Increased school absence rates.

Ozone welfare

Decreased yields for commercial forests.

Decreased yields for fruits and vegetables.

Decreased yields for noncommercial crops.

Damage to urban ornamental plants.

Impacts on recreational demand from damaged forest aesthetics.

Damage to ecosystem functions.

PM health

Low birth weight.

Changes in pulmonary function.

Chronic respiratory diseases other than chronic bronchitis.

Morphological changes.

Altered host defense mechanisms.

Cancer.

Nonasthma respiratory emergency room visits.

PM welfare

Visibility in many Class I areas.

Residential and recreational visibility in non-Class I areas.

Soiling and materials damage.

Damage to ecosystem functions.

Nitrogen and sulfate deposition welfare

Impacts of acidic sulfate and nitrate deposition on commercial forests.

Impacts of acidic deposition to commercial freshwater fishing.

Impacts of acidic deposition to recreation in terrestrial ecosystems.

Reduced existence values for currently healthy ecosystems.

Impacts of nitrogen deposition on commercial fishing, agriculture, and forests.

CO health

Premature mortality.

Behavioral effects.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

Pollutant/Type of Impact

Nonquantified Effects

HC health

Cancer (benzene, 1,3-butadiene, formaldehyde, acetaldehyde).

Anemia (benzene).

Disruption of production of blood components (benzene).

Reduction in the number of blood platelets (benzene).

Excessive bone marrow formation (benzene).

Depression of lymphocyte counts (benzene).

Reproductive and developmental effects (1,3-butadiene).

Irritation of eyes and mucus membranes (formaldehyde).

Respiratory irritation (formaldehyde).

Asthma attacks in asthmatics (formaldehyde).

Asthma-like symptoms in nonasthmatics (formaldehyde).

Irritation of the eyes, skin, and respiratory tract (acetaldehyde).

Upper respiratory tract irritation and congestion (acrolein).

HC welfare

Direct toxic effects to animals.

Bioaccumulation in the food chain.

Damage to ecosystem function.

Odor.

NOTES: PM = particulate matter; CO = carbon monoxide; HC = hydrocarbons.

SOURCE: EPA (2004b, p. 39139, Table VI.E-6).

analysis make a number of recommendations for treating uncertainty in all economically significant rules, noting the need for qualitative discussion as well as quantitative assessment using sensitivity analysis or probabilistic modeling. This guidance now requires agencies to conduct formal probabilistic uncertainty analysis for all rules with impacts that exceed $1 billion annually (OMB, 2003a). Recommendation 10 of this report addresses the need for better information on the health effects of regulatory interventions, which is one major source of uncertainty.

At present there is also uncertainty about the correct health state index values to use in calculating QALYs due to several factors: (1) the lack of agreement on the concept of HRQL, (2) how it should be measured, and (3) measurement error. Different generic instruments and elicitation methods produce different results without a clear consensus on the theoretical or empirical superiority of one particular approach or model. Measurement error in estimating health state index values should be reported as credible intervals around point estimates and examined in the uncertainty analysis.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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Recommendation 7: Regulatory analyses should not assign monetary values to estimates of health-adjusted life years as a method for valuing health states.


In the existing literature, monetary values have been applied to HALYs for two reasons. First, as discussed in Chapter 2, agencies often use monetized HALYs in their BCAs, apparently because suitable, high-quality willingness-to-pay estimates are lacking for many nonfatal health effects of concern. Health state index values are more plentiful, and address the shortcomings associated with reliance on other proxy measures (such as cost-of-illness estimates) for valuation.

Although the Committee recognizes that in the short term, regulatory agencies might continue this practice of using monetized HALY values in BCAs due to the lack of willingness-to-pay estimates for morbidity effects, we disapprove of and discourage this practice. As discussed in Chapter 1, willingness-to-pay and HRQL valuation and measurement have developed out of distinct disciplinary and methodological traditions. Given their different theoretical underpinnings and the different types of trade-offs they consider, it is misleading to combine them.

The second reason for assigning monetary values to HALYs is to provide a threshold for determining whether an intervention should be pursued. As discussed in Chapters 1 and 3, neither theoretical justification for nor evidence of a consensus about any particular threshold value exists. In the absence of any compelling rationale, the Committee concludes that the use of thresholds is inappropriate.

Information Needed for Regulatory Decision Making

Regardless of whether economic analysis takes the form of BCA or CEA, economic analysis is only one of many inputs into the policy-making process. Statutory requirements, judicial decisions, executive orders, and agency guidance all stress the importance of considering the distribution of a regulatory intervention’s impacts, the ethical implications of different options, and the implications of nonquantifiable effects, some of which may be related to health and others not. The Committee endorses this multifaceted approach to decision making, and believes that the results of CEA should continue to be but one element in a deliberative policy development process that takes full account of both quantified and qualitative information.


Recommendation 8: The regulatory decision-making process should explicitly address and incorporate the distributional, ethical, and other implications of a proposed intervention along with the quantified results of BCA

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
×

and CEA. Comparisons of different interventions should highlight these distinctive features of the interventions and also any methodological differences, both in the case of cost-effectiveness ratios and of estimates of net benefits.


CEA plays an important role in regulatory development, providing a useful approach for collecting and organizing information, as well as for reporting the quantifiable results in summary form. Decision makers should, however, recognize the limitations of this and other approaches to economic analysis. Both BCA and CEA must be supplemented by other types of information.

Because both BCA and CEA focus on economic efficiency, they should be accompanied by a discussion that highlights distributional and ethical considerations that are not fully incorporated into the quantitative results. These concerns may relate to the disproportionate adverse effects of baseline (preregulatory) or postregulatory health conditions on subgroups of particular concern (e.g., very young and very old people, minority and/or low-income groups, or individuals with preexisting conditions). They also may relate to the characteristics of the risk itself, such as the extent to which those experiencing the risk do so voluntarily or involuntarily.

The Committee proposes that regulatory analysts and decision makers use a structured and systematic approach in the consideration of distributional and other ethical considerations raised by a particular regulatory action. By design, BCA and CEA aggregate benefits across the population. Their summary forms thus obscure important distributional effects that should be considered explicitly in the policy development process. In addition, they generally focus on the physiological consequences of the risk, and do not consider other characteristics of risk that may lead to different values. For example, the societal value placed on addressing two causes of preventable mortality—air pollution and car accidents, for example—may vary even if the probability of fatality is the same. A 1-in-100,000 chance of death may be valued differently depending on whether the risk is perceived as controllable or voluntary.

To help ensure that important concerns are not omitted, we have identified (in Box 5-3) features of a specific risk or regulatory intervention that should be considered, if applicable, in the regulatory impact analysis and in any summary comparison of CEAs. This itemization is not intended merely as a checklist, but rather as a framework for organizing important considerations not likely to be emphasized sufficiently in the CEA itself. Such distributional and other ethical considerations could be highlighted, for example, by presenting disaggregated quantified information about regulatory effects or by conducting sensitivity analyses with alternative valuation assumptions that reflect some of these considerations. As discussed in Chapter 4,

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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BOX 5-3
Distributional and Other Aspects of Risk and Regulation

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

Characteristics of Risks

Do the risks have attributes that affect their value, but that are not reflected in the quantified valuation measures?

  • 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?

agencies may want to conduct alternative quantitative analyses that use measures other than standard QALYs in uncertainty analyses. Such quantification of certain distributional effects could highlight the implications of particular value commitments.

Although comparisons of CEA ratios across different types of regulatory interventions can provide useful information on the relative impacts of different programs or policies, those using or reviewing these comparisons should recognize their limitations. Both policy makers and scholars are often interested in the relative effectiveness of different governmental or nongovernmental interventions aimed at achieving particular outcomes, such as the relative effectiveness of different programs for reducing preventable mortality. Those developing or using such comparisons, however, should recognize that economic evaluations in their summary forms (i.e., cost-effectiveness ratios and net benefits) are incomplete and may not be fully comparable due to differences in methodology as well as differences in the types of effects considered.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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Different approaches to estimating risks or valuing effects may lead to differing estimates; the ranking of interventions may be affected by the lack of a standardized methodology rather than by real differences in effectiveness. Interventions that appear to differ significantly based on central tendency estimates may in fact be indistinguishable when the uncertainty in the estimates is considered. Thus it is important that such presentations of comparative information across interventions, such as relative cost-effectiveness or net benefit estimates, highlight these types of factors.

The Committee endorses the addition of QALY-based CEA to the other requirements for regulatory impact analysis. At the same time, we are concerned that presenting summary measures such as cost-effectiveness ratios in simple tables without reference to limitations of such comparisons or to their ethical and distributional implications could hinder—rather than help—the development of sound regulatory policy.


Recommendation 9: Because of the many value dimensions encompassed by societal decisions regarding the mitigation of risks to health and safety and the far-ranging impacts of such decisions, policy makers and program administrators should work to ensure the substantive involvement of a broad range of individuals and groups at all stages of policy development for regulating risks.


Regulatory agencies are, by definition, part of a political system designed to involve the public in decision making and balance competing views. Public outreach is mandated by several statutes and administrative orders and is a standard component of the regulatory development process. The Committee is concerned about the need to ensure that this outreach encourages widespread involvement and allows adequate consideration of the concerns voiced by diverse parties. Numbers can be very powerful in policy contexts; thus it is important that decision makers are presented not only with the results of economic analyses, but also have an opportunity to engage in deliberations with all constituencies and affected parties.

Although we did not evaluate the role of public participation in the regulatory development process in depth, we suggest that these activities merit further review and study. In particular, an effective deliberative process is needed to ensure that the appropriate weight is placed on those ethical, distributional, and nonquantifiable factors that are not included in the quantitative analysis.

Data Collection and Research Needed to Improve HRQL Measurement and CEA for Regulatory Decision Making

Although useful for regulatory analysis, the data and methods currently available for measuring and valuing health impacts in CEA have limitations

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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that should be addressed by a long-term research agenda. As regulations become more stringent, or simply more costly, the importance of sound methods and accurate information for assessing societal priorities and values grows. Additional data collection and research to support regulatory analysis are costly undertakings that must be considered in the context of federal agencies’ overall missions and priorities. Better planning and coordination among the relevant agencies could improve the cost-effectiveness of their investments in improved information.

For example, population HRQL norms for one or more generic indexes broken out by demographic characteristics (age, gender, race and ethnicity) have not been available in the past, and are not a standard component of periodic national health surveys. In addition, QALY-based CEAs may use any one of several generic HRQL indexes, and estimates based on different survey instruments are not readily combined or compared, because the relationships among the estimates produced by different instruments are not well understood. Perhaps most importantly, the data collection efforts for the risk assessments and epidemiological studies that underlie the economic analyses of regulations have not been designed with QALY-based analyses in mind, and the data are often inadequate for estimating HRQL impacts. The areas where additional routine data collection and research are most needed and likely to be fruitful include the following.


Recommendation 10: A high research priority should be improving the data used to assess the health risks (effects on incidence of particular types of illness, injuries, and deaths, and the duration and latency of effects) addressed by regulatory actions.


One significant source of uncertainty in estimating the economic impact of regulations is the information and modeling underlying the estimation of the type and magnitude of health-related effects on a population, that is, the risk assessment itself. Risk assessment is of fundamental importance because it supports BCA and CEA alike, as well as other aspects of the regulatory development process. Comparative risk assessment also helps set regulatory priorities. Greater precision and detail in the estimation of health effects would particularly improve QALY-based CEA because it provides more extensive information on the impact of the risk and its abatement on health status over time that are needed for this kind of analysis. As did the recent National Research Council Committee to Estimate the Public Health Benefits of Proposed Air Pollution Regulations, we recommend that federal agencies set as a high research priority improving the epidemiological and health status data used to model health and safety risks and the effects of interventions for reducing these impacts (NRC, 2002). For a discussion of methodological issues related to the calculation

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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of attributable risk and population attributable fractions, see the Institute of Medicine workshop summary, Estimating the Contributions of Lifestyle-Related Factors to Preventable Death (IOM, 2005).


Recommendation 11: The Department of Health and Human Services (DHHS) and other federal agencies should collect HRQL information through routinely administered population health surveys and other major studies and data collection efforts related to risk assessment and monitoring.


DHHS should ensure that at least one population health survey—such as the National Health Interview Survey or the Medical Expenditure Panel Survey—incorporates on a periodic basis (e.g., every 3–4 years) at least one complete HRQL survey instrument that supports a preference-based measure in order to provide age- and sex-specific population HRQL norms or baselines. Survey questions regarding specific health conditions should be developed in consultation with regulatory agencies so that conditions that are common health endpoints for regulatory analyses or that are anticipated to be the targets of future regulatory action can be included. DHHS and its statistical agencies and programs should consult with regulatory agencies to identify these information needs and to reserve a portion of questionnaires and surveys for these purposes.

The sampling frames of these national health surveys are not ideally constructed for the collection of nationally representative HRQL information. People who reside in institutions, including those with severe mental and physical disabling conditions, and homeless people are systematically excluded from these household-based surveys. These exclusions may skew the statistical characterization of HRQL for the population overall and inhibit the ability of the agencies to assess HRQL impacts on these subgroups.

Regulatory agencies should consider including HRQL measures, as well as individual-level diagnostic and health profile information, in major data collection efforts and epidemiological studies undertaken as part of their risk monitoring systems and risk assessment research.

All federally supported research that includes HRQL measures and applications of any such measures should produce public access data sets.

DHHS should support the refinement and expansion of a catalogue of health state values derived from information in population health surveys, building on recent work to create a catalogue of preference-based chronic disease index values (see Sullivan et al., 2005). Such research should give special attention to the documentation of co-morbid conditions and the development of HRQL values for health states involving multiple impairments.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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Recommendation 12: DHHS should coordinate, with the involvement of federal regulatory offices and agencies, the development of an integrated research agenda to improve the quality, applicability, and breadth of HRQL measures for use in regulatory CEA. The Committee identifies the following areas as priorities for research:


Current elicitation methods such as the standard gamble and time tradeoff, while theoretically well founded, may be difficult for respondents to understand and prone to generate inconsistent responses. Research to facilitate improved methods is needed. In addition, methods for eliciting societal values for investments in health (in contrast to individual preferences for health states), such as person trade-off techniques, should also be investigated.

Despite widespread acceptance and endorsement by economists and decision theorists in the health field, preference elicitation methods based in utility theory have been criticized by behavioral scientists and survey researchers who have focused on the cognitive challenges, artificiality of choices posed, and susceptibility of responses to the framing of the choices (Fischhoff, 1991; Kahneman and Tversky, 2000). Research to refine survey practices for eliciting preferences for health states through standard gamble and time trade-off methods could improve the reliability, precision, and validity of survey results.

A more fundamental critique of using aggregate individual preferences to represent societal values in health policy has been offered by ethicists and political philosophers, among others (Nord, 1999; Ubel et al., 2000; Hausman, 2004). One approach to value elicitation that has attempted to capture judgments about societal investments in health has been the person trade-off method, either conducted individually or in consensus group settings. This method is still in a developmental phase. Although the person trade-off method will doubtless be tested and refined further to improve reliability and interpretability of results, other approaches to social valuation beyond the simple aggregation of individual preferences should also be explored.


Methods for measuring children’s HRQL, including characterization of the impact of illness and injury and the valuation of these impacts, need continued development and refinement.

The Committee is particularly concerned about the adequacy of current metrics and methods for valuing health-related effects in children in two respects. First, the impacts of illness and injury on children are not well understood, due to limitations in the underlying health science research and in the methods used to describe these effects with HRQL instruments.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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Existing instruments are limited in their capacity to capture important aspects of HRQL for children, such as impacts on cognitive abilities and social interactions. Second, the surveys used to assess societal values for changes in HRQL generally address impacts on adults. In reality, those affected by costs and benefits of economically significant regulations may assign a higher value to improving the HRQL and longevity of children than of adults. In addition, there are questions about when it may be desirable to include children’s valuation of their own health states as one component of the total societal value of these effects.

Because children may lack the maturity and experience to evaluate their own health, and especially to provide informed responses to choice-based valuation questions, it may be appropriate to substitute the judgments of parents or other proxy respondents. Other questions include how to adapt preference elicitation techniques for use with children and young adolescents and how to include the effects of children’s health on the well-being of parents and caretakers, effects that are not captured by individual-level HRQL measures. There appears to be no consensus on best practices for the measurement of children’s HRQL and the conduct of CEA for pediatric interventions, and a concerted research and consensus development initiative on this topic is warranted. (See Griebsch et al., 2005, for a literature survey of pediatric CEAs and variability in valuation methods.)


Methods to correlate QALY estimates based on different generic HRQL indexes should be developed so that estimates from different underlying valuation studies are consistent and can be used in the same analysis.

As noted in Chapter 3, a federally supported survey effort with a nationally representative sample of noninstitutionalized adults is under way to collect HRQL information using several generic indexes, so that the relationships among the estimates produced by different indexes can be documented and conversion formulae developed. The results of this major data collection effort should make it possible to combine HRQL information based on different generic indexes, and could obviate the kinds of problems the Committee encountered in the air quality case study using published health state index values based on different generic instruments. (See Box 3-7 and Appendix A for discussions of this case study.)

SUMMARY

Regulatory decisions are, and should continue to be, based on a public and transparent deliberative process that includes consideration of a wide range of factors, including but not limited to the results of economic analyses using BCA and CEA. BCA and CEA are complementary tools in the development of major health and safety rules because they offer distinct

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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perspectives and different types of information about regulatory impacts and effects. Both kinds of analyses provide a structured framework for collecting, analyzing, and presenting information on regulatory impacts. They do not, however, provide a complete accounting of all the effects and consequences that are important for policy-making purposes.

Given the substantial impact of major health and safety regulations on the national economy and societal welfare, it is imperative that related decisions be based on high-quality policy analysis, the results and limitations of which are clearly communicated in a form that is understandable by a wide variety of audiences. Because these rules vary significantly in the type of intervention, the characteristics of the affected population, and the characteristics of the risks addressed, benefits measures are needed that can be applied to a broad range of health scenarios. These measures should be supplemented by discussion of any attributes of the scenarios that cannot be fully captured in the quantitative measures. Furthermore, the substantial uncertainty that accompanies the risk analysis underlying the calculation of health-related effects, along with uncertainty about the preference weighting of QALYs due to alternative HRQL concepts and constructs and variability in measurement, should be conveyed in uncertainty analyses.

Finally, the process of developing and issuing regulations should:

  • Be publicly accessible;

  • Be based on information (including that used in BCA and CEA) that can be interpreted for and communicated to a wide audience;

  • Facilitate the involvement of affected individuals, populations, and organizations in deliberations about health and safety risks and proposed interventions; and

  • Be accountable for the policy choices made with reasons that are available to all participants and observers.

Suggested Citation:"5 Recommendations for Regulatory Cost-Effectiveness Analysis." Institute of Medicine. 2006. Valuing Health for Regulatory Cost-Effectiveness Analysis. Washington, DC: The National Academies Press. doi: 10.17226/11534.
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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.

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