Claudine de Meijer

Determinants of long-term care spending: Age, time to death or disability?

In view of population aging, better understanding of what drives long-term care expenditure (LTCE) is warranted. Time-to-death (TTD) has commonly been used to project LTCE because it was a better predictor than age. We reconsider the roles of age and TTD by controlling for disability and co-residence and illustrate their relevance for projecting LTCE. We analyze spending on institutional and homecare for the entire Dutch 55+ population, conditioning on age, sex, TTD, cause-of-death and co-residence. We further examined homecare expenditures for a sample of non-institutionalized conditioning additionally on disability. Those living alone or deceased from diabetes, mental illness, stroke, respiratory or digestive disease have higher LTCE, while a cancer death is associated with lower expenditures. TTD no longer determines homecare expenditures when disability is controlled for. This suggests that TTD largely approximates disability. Nonetheless, further standardization of disability measurement is required before disability could replace TTD in LTCE projections models.

The role of disability in explaining long-term care utilization.

Objective:In view of aging populations, it is important to improve our understanding of the determination of long-term care (LTC) service use among the middle-aged and elderly population. We examined the likelihood of using 2 levels of LTC—homecare and institutional care—in the Netherlands and focused on the influence of the measured degree of disability. Methods:We pooled 2 cross-sectional surveys—one that excluded institutionalized and one that was targeted at institutionalized individuals aged 50+. Disability is measured by impairment in (instrumental) activities of daily living (iADL, ADL) and mobility. Consistency with official Dutch LTC eligibility criteria resulted in the selection of an ordered response model to analyze utilization. We compared a model with separate disability indicators to one with a disability index. Results:Age and disability, but not general health, proved to be the main determinants of utilization, with the composite index sufficiently representing the disaggregated components. The presence of at least 1 disability displayed a greater effect on utilization than any additional disabilities. Apart from disability and age, sex, living alone, psychologic problems, and hospitalizations showed a significant influence on LTC use. Some determinants affected the likelihood of homecare or institutional care use differently. Conclusions:Even after extensive control for disability, age remains an important driver of LTC use. By contrast, general health status hardly affects LTC use. The model and disability index can be used as a policy tool for simulating LTC needs.

The effect of population aging on health expenditure growth: a critical review

Although the consequences of population aging for growth in health expenditures have been widely investigated, research on this topic is rather fragmented. Therefore, these consequences are not fully understood. This paper reviews the consequences of population aging for health expenditure growth in Western countries by combining insights from epidemiological and health economics research. Based on a conceptual model of health care use, we first review evidence on the relationship between age and health expenditures to provide insight into the direct effect of aging on health expenditure growth. Second, we discuss the interaction between aging and the main societal drivers of health expenditures. Aging most likely influences growth in health expenditures indirectly, through its influence on these societal factors. The literature shows that the direct effect of aging depends strongly on underlying health and disability. Commonly used approximations of health, like age or mortality, insufficiently capture complex dynamics in health. Population aging moderately increases expenditures on acute care and strongly increases expenditures on long-term care. The evidence further shows that the most important driver of health expenditure growth, medical technology, interacts strongly with age and health, i.e., population aging reinforces the influence of medical technology on health expenditure growth and vice versa. We therefore conclude that population aging will remain in the centre of policy debate. Further research should focus on the changes in health that explain the effect of longevity gains on health expenditures, and on the interactions between aging and other societal factors driving expenditure growth.

Going Formal or Informal, Who Cares? The Influence of Public Long-Term Care Insurance

International differences in long-term care (LTC) use are well documented, but not well understood. Using comparable data from two countries with universal public LTC insurance, the Netherlands and Germany, we examine how institutional differences relate to differences in the choice for informal and formal LTC. Although the overall LTC utilization rate is similar in both countries, use of formal care is more prevalent in the Netherlands and informal care use in Germany. Decomposition of the between-country differences in formal and informal LTC use reveals that these differences are not chiefly the result of differences in population characteristics but mainly derive from differences in the effects of these characteristics that are associated with between-country institutional differences. These findings demonstrate that system features such as eligibility rules and coverage generosity and, indirectly, social preferences can influence the choice between formal and informal care. Less comprehensive coverage also has equity implications: for the poor, access to formal LTC is more difficult in Germany than in the Netherlands.

Health Expenditure Growth: Looking Beyond the Average Through Decomposition of the Full Distribution

Explanations of growth in health expenditures have restricted attention to the mean. We explain change throughout the distribution of expenditures, providing insight into how expenditure growth and its explanation differ along the distribution. We analyse Dutch data on actual health expenditures linked to hospital discharge and mortality registers. Full distribution decomposition delivers findings that would be overlooked by examination of changes in the mean alone. The growth rate of hospital expenditures is greatest at the middle of the distribution and is driven mainly by changes in the distributions of determinants. Pharmaceutical expenditures increase most rapidly at the top of the distribution and are mainly attributable to structural changes, including technological progress, making treatment of the highest cost cases even more expensive. Changes in hospital practice styles make the largest contribution of all determinants to increased spending not only on hospital care but also on pharmaceuticals, suggesting important spill over effects.

Explaining Declining Rates of Institutional LTC Use in the Netherlands: A Decomposition Approach

The use of long-term care (LTC) is changing rapidly. In the Netherlands, rates of institutional LTC use are falling, whereas homecare use is growing. Are these changes attributable to declining disability rates, or has LTC use given disability changed? And have institutionalization rates fallen regardless of disability level, or has LTC use become better tailored to needs? We answer these questions by explaining trends in LTC use for the Dutch 65+ population in the period 2000-2008 using a nonlinear variant of the Oaxaca-Blinder decomposition. We find that changes in LTC use are not due to shifts in the disability distribution but can almost entirely be traced back to changes in the way the system treats disability. Elderly with mild disability are more likely to be treated at home than before, whereas severely disabled individuals continue to receive institutional LTC. As a result, LTC use has become better tailored to the needs for such care. This finding suggests that policies that promote LTC in the community rather than in institutions can effectively mitigate the consequences of population aging on LTC spending.

Forecasting lifetime and aggregate long-term care spending: accounting for changing disability patterns.

Objective:The impact population aging exerts on future levels of long-term care (LTC) spending is an urgent topic in which few studies have accounted for disability trends. We forecast individual lifetime and population aggregate annual LTC spending for the Dutch 55+ population to 2030 accounting for changing disability patterns. Methods:Three levels of (dis)ability were distinguished: none, mild, and severe. Two-part models were used to estimate LTC spending as a function of age, sex, and disability status. A multistate life table model was used to forecast age-specific prevalence of disability and life expectancy (LE) in each disability state. Finally, 2-part model estimates and multistate projections were combined to obtain forecasts of LTC expenditures. Results:LE is expected to increase, whereas life years in severe disability remain constant, resulting in a relative compression of severe disability. Mild disability life years increase, especially for women. Lifetime homecare spending—mainly determined by mild disability—increases, whereas institutional spending remains fairly constant due to stable LE with severe disability. Lifetime LTC expenditures, largely determined by institutional spending, are thus hardly influenced by increasing LE. Aggregate spending for the 55+ population is expected to rise by 56.0% in the period of 2007–2030. Conclusions:Longevity gains accompanied by a compression of severe disability will not seriously increase lifetime spending. The growth of the elderly cohort, however, will considerably increase aggregate spending. Stimulating a compression of disability is among the main solutions to alleviate the consequences of longevity gains and population aging to growth of LTC spending.

Time to Drop Time-to-Death? Unraveling the Determinants of LTC Spending in the Netherlands

A better understanding of what drives long term care (LTC) expenditures is important for all countries with aging populations. We employ unique new data sources to analyze the determinants of LTC spending in the Netherlands. First, we use two-part models, to analyze institutional LTC and homecare expenditures for the entire 55+ population, conditioning not only on age, sex, time-to-death (TTD), but also on cause-of-death and co-residence status. These have profound effects. Those living alone, as well as those who deceased from diabetes, mental illness, stroke, diseases of the respiratory or digestive system have higher LTC expenditures, while a neoplasm death resulted in lower expenditures. Secondly, we examine homecare expenditures among a sample of non-institutionalized individuals conditioning, additionally, on morbidity and disability. Finally, we reconsider the roles of age and TTD, when controlling for the most important determinants of LTC use - morbidity, disability and co-residence - andillustrate their relevance for forecasting LTC expenditures. Our analysis reveals that TTD is not a predictor of homecare expenditures when disability is controlled for, while age and co-residence are. We therefore conclude that it is time to drop time-to-death from LTC expenditure models as it merely acts as a proxy for disability status.

The Influence of Spouse Ability to Provide Informal Care on Long-Term Care Use

Objective: Informal care substitutes for or postpones formal long-term care (LTC) use, especially in the Netherlands, where informal care supply affects eligibility for public LTC. The effect of potential informal care supply within the household has received less attention. We examine the role of spouse’s physical ability to provide informal care in explaining LTC use and transitions.Method: We used Dutch respondents from waves 1 and 2 of the Survey of Health, Ageing and Retirement in Europe. A mixed multinomial logit regression is used to model the choice between no LTC use, informal LTC use only, and formal LTC use. Transitions into formal care use are modeled with a logit regression.Results: Spouse ability affects LTC use but living alone remains important after controlling for spouse ability. Other important determinants of use are having a child , age, disability and health status. Transitions are explained by informal care supply and changes therein, health and disability and the respondent’s age. Discussion: Spouse ability to provide informal care reduces use of formal LTC, which implies that future compression of morbidity/disability and its impact would lower demand for LTC, directly and through increased spouse ability to provide informal care.