In this study we estimated in a sample of patients in early stages of AD the incremental effect of patients' dependence on total costs of care and on two main component costs, direct medical care costs and informal caregiving costs, controlling for patient's function. We measured patients' dependence on others by the Dependence Scale (DS) and patients' function by the Blessed Dementia Rating Scale (BDRS). As expected, as patients' dependence increased, all aspects of costs substantially increased. Similar to previous studies, patients' function was independently associated with costs. We found that both function and dependence were significantly associated with total costs, yet related differently to direct medical care costs and informal caregiving costs. Poorer function was associated with higher direct medical care costs, while more severe levels of dependence were associated with higher informal caregiving costs. These results confirm that BDRS and DS represent distinct components of disability in AD, and suggest that measures of patients' function and dependence provide unique information for explaining variations in costs of care for patients with AD, and highlight the value of measuring both constructs in economics and outcomes research.
These results have substantial policy implications. They provide information for deriving estimates of potential cost savings if interventions are developed that aim to improve patients' function and lessen their dependence on others. Earlier studies have estimated that BDRS and DS scores worsen by, respectively, 1.5 points and 1 point per year.6, 31
Results in this study suggest that small differences in patients' function and dependence may be associated with large differences in medical care costs and informal caregiving costs. For example, an intervention that delays the worsening of BDRS score by 1 point among AD patients could be expected to yield average savings of $1,406 per year in direct medical costs. An intervention that delays the worsening of DS score by 1 point among AD patients could be expected to yield average savings of $1,690 per year in informal caregiving costs. Thus, the choice of interventions that aim to delay a patient moving to higher levels of either functional impairment or dependence on others have the potential to yield substantial economic benefit. Comparison of the strengths of the effects of BDRS and DS on different cost components suggests that success of the interventions to control costs and improve patient outcome depend on the cost component targeted.
It is notable that the potential cost savings we estimated are generated from a sample of mildly demented patients. Although most cost savings may not be realized immediately, a delay in disease progression for patients at early stages of the disease may yield greater cost savings than the same delay experienced by patients at later disease stages. Because subjects have been followed closely in our study, our future work will address issues of lifetime cost savings more appropriately by using longitudinal analyses. Longitudinal analyses also will confirm whether the relationships of BDRS and DS with different cost components are consistent over time.
In this study, we focused on direct medical costs and informal costs. An important component of costs that is not included in this analysis is non-medical costs, which include, among others, costs for home health aides, respite care, and adult day care. Previous studies have shown that, compared to direct medical costs and informal costs, the proportion of total costs attributable to non-medical costs is relatively small.32
Therefore, the effects of excluding non-medical costs from our total cost estimations should be minimal. Results from secondary analyses including use of non-medical care as an explanatory variable showed that it was not significantly associated with direct medical care costs or informal costs. Indeed, few patients in this sample (12.3%, n=22) reported using non-medical care, precluding detailed analysis of its relationship to patients' dependence. Bivariate analysis of the relationship between utilization (and costs) of non-medical care and patients' dependence showed that there was minimal use (and costs) of non-medical care for patients at mild levels of dependence, and that costs did not begin to rise until moderate levels of dependence were reached. This suggests that over time, as patients' dependence increases, utilization and costs of non-medical care will likely increase. While the magnitude of these costs may continue to be relatively small compared to direct medical care and informal care costs, they are nevertheless important for patients and families. Future longitudinal analyses will examine utilization and costs of non-medical care in more detail.
Several limitations of this study should be noted. First, data reported here are cross-sectional; therefore results can only be interpreted as associations. While poorer function and dependence may lead to higher costs, it also is possible that low spending on healthcare indicates insufficient medical care and results in poor health. In this sample of patients with relatively high education levels, however, the latter explanation is less likely. Second, aside from the patient characteristics included in the model, other variables may be associated with higher costs, however, the focus of this study was to examine whether the dependence scale could explain variations in costs, and identifying predictors of informal care was beyond the scope of the paper. Third, data on patients' healthcare costs from this study were reported by patients and informants, most of whom were the patients' primary caregivers. Studies have shown that caregivers are able to accurately report medical information of their care recipients.33, 34
There is no reason to believe our sample is systematically different, although it is possible that there are additional costs important to patients and families beyond the resource items collected. Our cost estimates were from a society's perspective, as all costs, regardless of the payer, were collected. Fourth, patients were selected from tertiary care university hospitals and specialized diagnostic and treatment centers and thus represent a nonrandom sample of those affected by AD in the population. The patients in our sample also were predominantly white and highly educated. Caution is needed in generalizing the results of this study to patients with lower levels of education and income and to non-white patients. Future research will need to examine the relationship between costs and the potential variables in samples that are more representative of the general population. However, because patients were drawn from multiple locations, generalizability of our findings is enhanced. We found substantial cost differences across sites. This result is consistent with regional differences in health services utilization and costs documented in the literature35
and more specifically a recent study on service utilization and costs among patients with AD.36
Because different sites were included in these studies, our results are not directly comparable with these studies. Further investigations are needed to examine whether variations in utilization and costs reflect differences in regional preferences, availability or access of services, ethnic and cultural differences, or socioeconomic factors.