The costs of caring for patients with AD have been extensively studied (Ernst and Hay 1994
; Stommel et al 1994
; Max et al 1995
; Hux et al 1998
; Leon and Neumann 1998
; Gutterman et al 1999
; Langa et al 2001
; Moore et al 2001
; Murman et al 2002
; Small et al 2002
; Andersen et al 2003
). In terms of total costs to society, AD is the third most costly disease in the US after cancer and coronary heart disease (Meek et al 1998
). Average annual costs of caring for patients with AD have been estimated at US$80–100 billion in the US (CDC and NCCDPHP 2000
). Total costs include direct, indirect, and intangible costs. Direct costs include multiple dimensions of medical care costs (eg, nursing home care, medications, physician visits, hospitalizations) and nonmedical care costs (eg, home health aides, respite care, adult daycare). Indirect costs are imputed values of resources lost due to the illness, including premature deaths, patient and caregiver lost productivity, and unpaid caregiving time. Intangible costs are those related to pain and suffering endured by patients and families, and those related to deterioration of patient and caregiver quality of life (QoL). Because the inclusion of intangible costs in economic studies is highly controversial and their evaluation notoriously difficult, most studies have focused on estimating direct and indirect costs of AD.
Alzheimer’s disease costs depend strongly on caregiving settings. Early in the disease, indirect costs often exceed direct costs as the majority of AD patients are cared for by informal caregivers in the community. For patients living in the community, some 60%–70% of the total cost of caring for AD patients has been attributed to informal caregiving. When patients are institutionalized, costs shift from indirect to direct (Huang et al 1988
; Ernst and Hay 1994
; Wimo et al 1997
; Leon and Neumann 1998
). About three-fourths of the total costs of AD occur during severe stages of AD, mainly due to institutionalization (Wimo, Winblad, Stoffler, et al 2003
). One study suggests that relatively small delays in the onset and progression of dementia could substantially reduce disease costs (Brookmeyer et al 1998
). It has been estimated that a 1-month delay in institutionalization of a patient with moderate to severe AD would result in savings of US$1863 per month (Leon and Neumann 1998
). The incidence and prevalence of AD is likely to rise as the population continues to age, and the already staggering costs of caring for patients with AD also will increase.
An important objective of economic analysis is to show the value of a medical treatment or intervention. This is a complex issue. For example, if a treatment delays institutionalization, but does not affect survival, the overall disease costs may be lowered if reductions in the cost of institutionalization outweigh the increases in treatment cost. Cost reductions, however, may be partially offset by potential increases in informal caregiving costs. If on the other hand, treatment prolongs survival, lifetime disease cost may in fact increase. Further complicating the issues are the possible impact on patient and family QoL. However, these important issues are often neglected.
Several different methods have been used in analyzing the effects of treatment on the costs of caring for patients with AD, including RCT, matched-control trials, pre-post designs, observational studies, and modeling analyses. Each of these methods is subject to a number of criticisms. Collecting resource utilization data prospectively in large, multicentered RCTs is a preferred method in economic analyses. However, while these analyses have superior internal validity, they are expensive to conduct and are often limited by their relatively short time horizon, and may not be applicable outside the trial settings. Because other studies are not of random design, possible selection effects cannot be ruled out. For example, in matched-control trials, caregivers of patients who tolerated the drugs better may have selectively delayed institutionalization and artificially lowered the costs of care. Because utilization and costs are expected to increase overtime as a result of disease progression, possible cost savings in studies with pre-post designs may be underestimated. In pre-post studies, it also is not meaningful to adjust for other covariates that influence disease cost (eg, comorbid conditions).
Dementia patients are expected to live approximately seven to ten years after diagnosis (Brookmeyer et al 2002
; Cummings and Cole 2002
). Pharmacological treatments may have substantial effects on long-term costs, which is particularly important because of the progressive nature of the disease. However, long-term effects of pharmacological treatments are not yet known. In the absence of long-term clinical data, modeling studies often use clinical data from short periods of time (eg, 6 months, 26 months) and project longer term costs (2, 5, or 10 years) relying on data from a variety of external sources. The underlying assumption is that clinical benefits observed in the short run will persist at the same rate at later time points. This assumption may not be valid. Making matters worse, clinical data often are derived from other countries. It is possible that there may be differences in drug efficacy between populations in different countries that are yet unknown. Therefore, even if studies are robust to plausible changes in key variables, results may not be applicable to other settings or regions. In the very long-term studies, proper discounting of costs has not been employed. highlights the findings of pharmacoeconomic studies.
Pharmacoeconomic studies with approved treatments for Alzheimer’s disease