Osteoporosis disproportionately affects elderly women and is associated with fractures that result in pain, disability, and death and is responsible for a large expenditure of health care resources. The direct medical costs attributed to osteoporotic fractures in the United States in 1995 exceeded $13 billion.16 It was estimated that $8.6 billion were spent on inpatient care, $3.9 billion on nursing home care, and $1.3 billion on outpatient care and home health services. As the "baby-boomer" generation ages, the absolute number of people at risk for osteoporosis and its complications will increase dramatically.13 If prevention is not undertaken, this will greatly increase the direct medical costs attributable to osteoporosis. In results of one study, it was estimated that without preventive interventions, the costs associated with osteoporosis would more than double in the next 30 years.4
Two approaches to osteoporosis prevention and treatment must be considered. These include interventions at the population level (universal intervention) and selective interventions that target people at highest risk for fracture. For interventions that have few adverse side effects, benefits beyond the skeleton, and low net costs, universal approaches are favored (increased dietary calcium). In contrast, for interventions that impact only on bone (bisphosphonate treatment), or are associated with uncertain or adverse extraskeletal effects (hormone replacement therapy) or high cost, selective intervention must be considered.
One criterion for identifying a sensible approach to osteoporosis prevention is to assess the value of possible interventions using the formal quantitative methods of economic evaluation. The rationale for economic evaluation in general and cost-effectiveness evaluation in particular is that in a society of limited resources, each successive health intervention should produce a benefit that is worth its additional cost. This article will highlight the importance of quality of life in the economic evaluation of osteoporosis prevention and treatment. An overview of economic evaluation will be followed by a discussion of cost-effectiveness analysis and the importance of quality of life in assessing the effectiveness of interventions in osteoporosis. Finally, the quality of life data that are critically needed to assess the value of interventions in osteoporosis are discussed.
Overview of Economic Evaluation
There are several forms of economic evaluation to consider. These include cost-minimization analysis, cost-benefit analysis, and cost-effectiveness analysis.6 Cost minimization analysis is most appropriate in situations where interventions are viewed as equally effective. In contrast with cost-minimization analysis, cost-benefit and cost-effectiveness analyses assess the value of interventions relative to their impact on health. Cost-benefit analysis requires that all health effects be valued in monetary terms. A cost-benefit analysis of a program to screen and treat women with low bone mineral density (BMD) with a bone-active agent would estimate the net cost of the program (the monetary value of health benefits minus the monetary cost of the intervention). A cost-effectiveness analysis of this program would estimate the cost per unit of health outcome. The units of health outcome can be general (years of life saved) or can be disease-specific (hip fractures or vertebral fractures prevented). The advantage of general measurements is that they allow policy makers to compare the value of health programs in all diseases. In theory, cost-benefit and cost-effectiveness analyses can be used to allocate resources in a fixed budget to maximize the impact that expenditures have on health.
Although the term cost-effective is sometimes used synonymously with cost-saving, it is used more generally here to mean "having an additional benefit worth the additional cost."5 In this sense, the term cost-effective is a relative concept and means providing good value for resources expended. Cost-effectiveness analysis is often most useful in settings where programs increase cost and improve health. The question that cost-effectiveness analysis addresses is whether the added health care expenditure is justified by the improvement in health.
The role of cost-effectiveness analysis in policy formulation is evidenced by the U. S. Office of Disease Prevention and Health Promotion's recently established guidelines for cost-effectiveness evaluation3 and by the National Osteoporosis Foundation's reliance on cost-effectiveness analysis as the basis for its recent practice guidelines for osteoporosis prevention and treatment.15 It is noteworthy that Canadian and Australian authorities require evidence of cost-effectiveness for new pharmaceutical agents before the agents are approved for inclusion in the formulary.
The primary outcome measurement for a cost-effectiveness evaluation is the cost-effectiveness ratio, which estimates the net change in cost divided by the net change in effectiveness. Comparison of cost-effectiveness ratios of health interventions within and across disease areas provides information on the relative value of the interventions. Estimation of a cost-effectiveness ratio for a health intervention requires specifying a starting point for the evaluation, components of cost, and a measurement of effectiveness.
For a cost-effectiveness analysis to be meaningful, it is imperative that a relevant starting point for assessing the health intervention be chosen. The starting point should reflect a realistic set of alternatives and should allow accurate assessment of the health of the target population before implementation of the intervention. For example, to assess the cost-effectiveness of hormone replacement therapy (HRT) at menopause for prevention of hip fractures, "no intervention" might be considered a relevant alternative. Alternatively, evaluation of screening and treatment of older postmenopausal women with a bone-active agent should be assessed recognizing that some of these women would already be receiving HRT.
Once the starting point is defined, the components of cost must be determined. Costs to be considered include direct medical costs, direct nonmedical costs and indirect costs. The particular cost components that would be included would vary, depending on the perspective of the analysis.3 One example of direct medical cost components that might be estimated includes the cost of the intervention, savings from fractures prevented, and costs from side effects of the intervention.
Next, the net impact of the intervention on health must be assessed. One measurement of the effectiveness of osteoporosis interventions might be the number of fractures averted. As noted earlier, however, this disease-specific outcome measurement does not allow for comparisons between the value of interventions in osteoporosis with interventions in other disease areas. Another problem with fractures averted as an effectiveness measurement is that all fractures are not equal in associated complications. Finally, focusing on fractures averted as an endpoint ignores the impact that interventions may have beyond the skeleton. This is particularly troublesome in evaluation of osteoporosis prevention using HRT, because HRT may have substantial effects on heart disease and breast cancer that must be considered. Failure to account for a broader view of impact on health could produce misleading results.
Quality of Life in Cost-Effectiveness Analysis
In cost-effectiveness analysis, it is desirable to take both length and quality of life into account. Consider a costly intervention that does not lengthen life but greatly reduces morbidity. If evaluated only on the basis of cost per year of life saved, such an intervention would be considered an inappropriate use of resources. If, however, the measurement of effectiveness reflected mortality and morbidity, such an intervention may be considered to provide a benefit worth its cost. Cost-effectiveness analyses that estimate cost per quality-adjusted life year (QALY) gained take both mortality and morbidity into account. Such analyses, also known as cost-utility analyses, have been recommended as the best approach for assessing the value of health interventions.3
The benchmark for considering an intervention cost-effective has been debated. There is consensus, however, that cost-effectiveness ratios should be interpreted relative to the cost-effectiveness of widely accepted health interventions. For example, treatment of severe hypertension (diastolic blood pressure ≥ 105 mm Hg), which is a widely accepted practice, has a cost-effectiveness ratio of approximately $23,000/QALY in 1996 U.S. dollars.23 Generally, cost-effectiveness ratios below $25,000/QALY are regarded as favorable.
Considering quality of life when measuring the effectiveness of osteoporosis interventions is particularly important, because many osteoporotic complications result in morbidity but not in mortality. For example, hip fractures among residents of New England 65 years old and older are associated with mortality rates of from 6% to 39%.7 Mortality, however, is only one aspect of the impact of osteoporotic fractures. After a hip fracture, only 50% of patients return to their prefracture ambulatory health state.14 Chrischilles et al1 have estimated that osteoporosis-related fractures will cause 6.7% of women to become dependent in basic activities of daily living during their lifetimes. Because the majority of fractures result in morbidity but not mortality, it is imperative that the value of preventing these fractures be captured in the effectiveness measurement (see Melton's article in this issue for further discussion of morbidity).
Utility Data for Estimating Quality-Adjusted Life Years
Utilities are quantitative expressions of patient preferences for the desirability of health states3,17,18 and are needed to estimate quality-adjusted life expectancy. When estimating quality-adjusted life expectancy, each year of life is not weighed equally. Instead, every health state is assigned a utility weight, which represents a person's (or a group of people's) preference for that health state. Utilities range from 0 to 1, where perfect health is typically assigned a value of 1 and death is assigned a value of 0. Quality-adjusted life expectancy is estimated as a sum of the utility for each health state multiplied by the length of time spent in each health state.
Methods for assessing utilities include the time-tradeoff technique and standard-gamble technique.3 To assess the utility for a health state using the time-tradeoff technique, patients are offered a choice between living in a health state for their remaining actuarial life expectancy or living for a shorter time in perfect health. The point at which a person is indifferent to the choice between living in the health state for the remaining life expectancy and living for fewer years in perfect health is used to compute the person's utility for the health state (Figure 1). For example, if a woman's remaining life expectancy is 10 years and she is indifferent to the choice between living for 6 years in perfect health (giving up 4 years) and living for 10 years with disability from vertebral fractures, her utility for disability from vertebral fractures is estimated as 6/10 = 0.6.
Utility assessment with the standard-gamble technique requires that patients choose between a "sure thing," living in a health state for the remaining life expectancy, or taking a gamble on a treatment that offers life with perfect health with probability P and immediate death with probability 1 - P. The probability P at which a patient is indifferent to the choice between living in the health state and taking the gamble between the best (perfect health) and worst (death) outcomes is used as the utility for the health state (Figure 2). For example, if a woman is indifferent to the choice between the gamble (trying a treatment with 60% chance of perfect health and 40% chance of immediate death) and the sure thing (life with disability from vertebral fractures), then her utility for disability from vertebral fractures is estimated as 0.6.
Although there has been increased interest in studies that document the impact of fractures on general health status, as evidenced by development of osteoporosis-specific health status instruments,2,8,12 very limited data are available on utilities for postfracture health states.11,19,20 Utilities for health states are distinct from measurements of general health status (e.g., Medical Outcome Study Short-Form 36 [SF-36]) or functional status (e.g., activities of daily living [ADLs]), because they reflect how patients feel about what they can do rather than what they are able to do.22 To clarify this point, consider two patients, Jane and Sally, who are both impaired in their ability to bend over and pick up objects after the occurrence of several vertebral fractures. Although these two patients may have the same functional status, they have very different utilities for their health state. Jane, who regularly cared for her two grandchildren and is an avid gardener, has a utility for her postvertebral fracture health of 0.75. Sally, who is an avid reader and leads a relatively sedentary lifestyle, has a utility for her postvertebral fracture health state of 0.95. Clearly, Jane, who has a more active lifestyle, is more bothered by her limitations than is Sally.
Impact of Quality-Adjusted Life Years on Cost-Effectiveness of Osteoporosis Interventions
The importance of focusing on QALYs rather than simply on impact on life expectancy is demonstrated by published estimates of the cost-effectiveness of screening and treating perimenopausal women with HRT21 or with agents that affect only bone for a period of 15 years.24 When hypothetical utilities were assigned to fracture and disability health states (0.8 for disability after hip fracture, 0.4 for nursing home residency, 0.95 for acute hip fracture, and 1 for returning to prefracture health9), the value of all interventions was improved by 50-60%. Similar reductions in cost-effectiveness ratios were noted when quality of life was considered in a recent Swedish cost-effectiveness study of treatment of established osteoporosis for 5 years with a therapeutic agent that reduces the rate of any osteoporotic fracture by 50%.10 Changes of this magnitude have the potential to change cost-effectiveness results qualitatively. Unfortunately, because the utilities in these studies were hypothetical and were based only on a few expert clinicians' preferences, they may not reflect how populations would value the interventions.
The importance of QALYs as an effectiveness measurement in osteoporosis prevention and treatment is also highlighted by the National Osteoporosis Foundation's reliance on this endpoint and a cost-effectiveness threshold of $30,000/QALY in establishing practice guidelines.15 It is noted, however, that the utilities used to make these estimates were based on the preferences and values of members of the National Osteoporosis Foundation's scientific advisory panel and not on data from representative populations who were either at-risk for or experienced with the outcomes of osteoporosis. Data from such populations are critically needed for future cost-effectiveness evaluations of prevention and treatment of osteoporosis.
In recent years, increased attention has focused on measuring the impact of osteoporosis on functional health status. This represents an important advance in the understanding of the impact of osteoporosis on health-related quality of life. Further attention is needed to obtain the utility data that are necessary for economic evaluations in osteoporosis. Future studies should include general health status measurements and utility measurements in assessing the effectiveness of interventions in osteoporosis on quality of life.
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