Proximity to death and participation in the long-term care market

The health and long-term care costs in the last year of life in The Netherlands

Knowing the determinants of rising health and long-term care costs is crucial to support cost containment policies and to predict future expenditures. According to the "red herring" debate, not ageing per se, but proximity to death is the most important determinant of future expenditures. This study aims to update and expand the existing Dutch literature after two major reforms in health and long-term care. Insurance claims data from 2018-2019 of 13,738,193 insured individuals were included. Using negative binomial regression analyses, the association between deceased individuals and survivors on total health and long-term care costs was investigated, as well as per health care sector. Costs rose sharply in the two months prior to death. Regression models showed an association with total health and long-term care costs of 10.8 for deceased individuals compared with survivors (crude model) and 3.3 (adjusted model). Especially including age and chronic diseases decreased the association. The largest differences in costs between deceased individuals and survivors in the adjusted model were found for geriatric rehabilitation care and primary care stays (16.7), home nursing (10,6), and long-term care (9.3). Not just the costs of deceased individuals are important for health care costs, but also age, as measured by being in the highest age category, and chronic diseases. The costs of deceased individuals were heterogeneous across health care sectors.

Informal Care Costs According to Age and Proximity to Death to Support Cost-Effectiveness Analyses

BACKGROUND

Costs of informal care are ignored in many cost-effectiveness analyses (CEAs) conducted from a societal perspective; however, these costs are relevant for lifesaving interventions targeted at the older population. In this study, we estimated informal care costs by age and proximity to death across European regions and showed how these estimates can be included in CEAs.

METHODS

We estimated informal care costs by age and proximity to death using generalised linear mixed-effects models. For this, we selected deceased singles from the Survey of Health, Ageing and Retirement, which we grouped by four European regions. We combined the estimates of informal care costs with life tables to illustrate the impact of including informal care costs on the incremental cost-effectiveness ratio (ICER) of a hypothetical intervention that prevents a death at different ages.

RESULTS

Informal care use, and hence informal care costs, increase when approaching death and with increasing age. The impact of including informal care costs on the ICER varies between €200 and €17,700 per quality-adjusted life-year gained. The impact increases with age and is stronger for women and in southern European countries.

CONCLUSION

Our estimates of informal care costs facilitate including informal care costs in CEAs of life-extending healthcare interventions. Including these costs may influence decisions as it leads to reranking of life-extending interventions compared with interventions improving quality of life.

The Effect of a Long-Term Care Insurance Program on Subjective Well-Being of Older Adults with a Disability: Quasi-Experimental Evidence from China

China launched its long-term care insurance (LTCI) program for older adults in 2016. Although the scheme has shown some promising outcomes, little is known about whether it improves subjective well-being. This study explored this topic among older persons with a disability and identified the underlying mechanisms associated with the channel of this effect using data from a national survey. The LTCI program was shown to improve the subjective well-being among older persons with a disability and this effect increased over time. The LTCI program has great positive effect among women and those who lived alone compared to their counterparts. Mechanism analysis revealed that the main channel by which the LTCI program has positive effect occurred through the satisfaction of long-term care needs and improved self-reported health. This study suggests promising benefits of the LTCI program for older Chinese adults.

Retrospective Evaluation of Discharge Planning Linked to a Long-Term Care 2.0 Project in a Medical Center

BACKGROUND

Although there are several studies on discharge planning and long-term care systems in individual programs, research on the connection between discharge planning and the usage of long-term care is scanty. This study aims to evaluate the nature of the association between discharge planning (DP) and long-term care (LTC) and whether the utilization of LTC services improved after being discharged.

METHODS

This was a single-center retrospective medical record review study. Secondary data analysis was conducted of DP-LTC participation data between 2018 and 2019. The objectives were to clarify the distinct characteristics of each part of the service to explore the utility rate by overall users and users with willingness and to determine the factors influencing their usage. Medical claims were used to identify inpatients receiving discharge services, and data were matched with LTC system engagement data (n = 2155). Backward stepwise regression was used to explore the attributes associated with each type of service use.

RESULTS

A total of 94% (2042/2155) of inpatients expressed a perceived need for LTC services, of which 14% (285/2042) were users of LTC services after discharge. When assessed by case-mix system (CMS) and willingness to use services during hospitalization, inpatients had higher rates of service utilization after discharge. Using LTC services was most likely to be associated with obesity, disability, high CMS level, higher education, and women.

CONCLUSION

The study confirms that the utilization of LTC services has improved under the integrated DP-LTC system. The gap between willing and actual users is worth considering. In the assessment stage, special attention should be paid to the service needs of persons with BMI ≥ 27 and disabilities. Future research with a larger sample could comprehensively evaluate the impact of integrated DP services on the use of LTC 2.0 service resources.

What is the marginal benefit of payment-induced family care? Impact on Medicaid spending and health of care recipients

Research on home-based long-term care has centered almost solely on the costs; there has been very little, if any, attention paid to the relative benefits. This study exploits the randomization built into the Cash and Counseling Demonstration and Evaluation program that directly impacted the likelihood of having family involved in home care delivery. Randomization in the trial is used as an instrumental variable for family involvement in care, resulting in a causal estimate of the effect of changing the combination of home health-care providers on health-care utilization and health outcomes of the beneficiary. We find that some family involvement in home-based care significantly decreases health-care utilization: lower likelihood of emergency room use, Medicaid-financed inpatient days, any Medicaid hospital expenditures, and fewer months with Medicaid-paid inpatient use. We find that individuals who have some family involved in home-based care are less likely to have several adverse health outcomes within the first 9 months of the trial, including lower prevalence of infections, bedsores, or shortness of breath, suggesting that the lower utilization may be due to better health outcomes.

Care choices in Europe: To Each According to His or Her Needs?

Growing long-term care (LTC) needs represent a major challenge for our aging societies. Understanding how utilization patterns of different types of care are influenced by LTC policies or changes in the population composition such as age patterns or health can provide helpful insight on how to adequately prepare for this situation. To this aim, this paper explores how individuals choose between different forms of LTC. We exploit variation between countries as well as between individuals within countries using data from the Survey of Health, Ageing, and Retirement in Europe (SHARE). Using nonlinear decomposition techniques, we break down the difference in utilization rates between countries into differences based on observed sociodemographic and need-related characteristics and differences in the impacts of these characteristics, which allows us to identify the drivers behind differences in the formal-informal care mix. Our results show that a substantial fraction of the observed country differences can be explained by differences in impacts. We argue that this is a result of the different incentives provided by the different LTC systems.

Long-term care is increasingly concentrated in the last years of life: a change from 2000 to 2011

Background

The use of long-term care (LTC) is common in very old age and in the last years of life. It is not known how the use pattern is changing as death is being postponed to increasingly old age. The aim is to analyze the association between the use of LTC and approaching death among old people and the change in this association from 2000 to 2011.

Methods

The data were derived from national registers. The study population consists of 315 458 case-control pairs. Cases (decedents) were those who died between 2000 and 2011 at the age of 70 years or over in Finland. The matched controls (survivors) lived at least 2 years longer. Use of LTC was studied for the last 730 days for decedents and for the same calendar days for survivors. Conditional logistic regression analyses were performed to test the association of LTC use with decedent status and year.

Results

The difference in LTC use between decedents and survivors was smallest among the oldest (OR 9.91 among youngest, 4.96 among oldest). The difference widened from 2000 to 2011 (OR of interaction of LTC use and year increased): use increased or held steady among decedents, but decreased among survivors.

Conclusions

The use of LTC became increasingly concentrated in the last years of life during the study period. The use of LTC is also common among the oldest survivors. As more people live to very old age, the demand for LTC will increase.

Trends in the use and costs of round-the-clock long-term care in the last two years of life among old people between 2002 and 2013 in Finland

BACKGROUND

The structure of long-term care (LTC) for old people has changed: care has been shifted from institutions to the community, and death is being postponed to increasingly old age. The aim of the study was to analyze how the use and costs of LTC in the last two years of life among old people changed between 2002 and 2013.

METHODS

Data were derived from national registers. The study population contains all those who died at the age of 70 years or older in 2002-2013 in Finland (N = 427,078). The costs were calculated using national unit cost information. Binary logistic regression and Cox proportional hazard models were used to study the association of year of death with use and costs of LTC.

RESULTS

The proportion of those who used LTC and the sum of days in LTC in the last two years of life increased between 2002 and 2013. The mean number of days in institutional LTC decreased, while that for sheltered housing increased. The costs of LTC per user decreased.

CONCLUSIONS

Use of LTC in the last two years of life increased, which was explained by the postponement of death to increasingly old age. Costs of LTC decreased as sheltered housing replaced institutional LTC. However, an accurate comparison of costs of different types of LTC is difficult, and the societal costs of sheltered housing are not well known.

Explaining regional variation in home care use by demand and supply variables

In the Netherlands, home care services like district nursing and personal assistance are provided by private service provider organizations and covered by private health insurance companies which bear legal responsibility for purchasing these services. To improve value for money, their procurement increasingly replaces fee-for-service payments with population based budgets. Setting appropriate population budgets requires adaptation to the legitimate needs of the population, whereas historical costs are likely to be influenced by supply factors as well, not all of which are necessarily legitimate. Our purpose is to explain home care costs in terms of demand and supply factors. This allows for adjusting historical cost patterns when setting population based budgets. Using expenses claims of 60 Dutch municipalities, we analyze eight demand variables and five supply variables with a multiple regression model to explain variance in the number of clients per inhabitant, costs per client and costs per inhabitant. Our models explain 69% of variation in the number of clients per inhabitant, 28% of costs per client and 56% of costs per inhabitant using demand factors. Moreover, we find that supply factors explain an additional 17-23% of variation. Predictors of higher utilization are home care organizations that are integrated with intramural nursing homes, higher competition levels among home care organizations and the availability of complementary services.

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.

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.

A country for old men? Long-term home care utilization in Europe

This paper investigates long-term home care utilization in Europe. Data from the first wave of the Survey on Health, Ageing and Retirement (SHARE) on formal (nursing care and paid domestic help) and informal care (support provided by relatives) are used to study the probability and the quantity of both types of care. The overall process is framed in a fully simultaneous equation system that takes the form of a bivariate two-part model where the reciprocal interaction between formal and informal care is estimated. Endogeneity and unobservable heterogeneity are addressed using a common latent factor approach. The analysis of the relative impact of age and disability on home care utilization is enriched by the use of a proximity to death (PtD) indicator built using the second wave of SHARE. All these indicators are important predictors of home care utilization. In particular, a strong significant effect of PtD is found in the paid domestic help and informal care models. The relationship between formal and informal care moves from substitutability to complementarity depending on the type of care considered, and the estimated effects are small in absolute size. This might call for a reconsideration of the effectiveness of incentives for informal care as instruments to reduce public expenditure for home care services.

Variation in the costs of dying and the role of different health services, socio-demographic characteristics, and preceding health care expenses

The health care costs of population ageing are for an important part attributable to higher mortality rates in combination with high costs of dying. This paper answers three questions that remain unanswered regarding the costs of dying: (1) contributions of different health services to the costs of dying; (2) variation in the costs of dying; and (3) the influence of preceding health care expenses on the costs of dying. We retrieved data on 61,495 Dutch subjects aged 65 and older from July 2007 through 2010 from a regional health care insurer. We included all deceased subjects of whom health care expenses were known for 26 months prior to death (n=2833). Costs of dying were defined as health care expenses made in the last six months before death. Lorenz curves, generalized linear models and a two-part model were used for our analyses. (1) The average costs of dying are €25,919. Medical care contributes to 57% of this total, and long-term care 43%. The costs of dying mainly relate to hospital care (40%). (2) In the costs of dying, 75% is attributable to the costliest half of the population. For medical care, this distribution figure is 86%, and for long-term care 92%. Age and preceding expenses are significant determinants of this variation in the costs of dying. (3) Overall, higher preceding health care expenses are associated with higher costs of dying, indicating that the costs of dying are higher for those with a longer patient history. To summarize, there is not a large variation in the costs of dying, but there are large differences in the nature of these costs. Before death, the oldest old utilize more long-term care while their younger counterparts visit hospitals more often. To curb the health care costs of population ageing, a further understanding of the costs of dying is crucial.

Care utilisation in the last years of life in Sweden: the effects of gender and marital status differ by type of care

The effects of gender and marital status on care utilisation in the last years of life are highly correlated. This study analysed whether gender differences in use of eldercare (home help services or institutional care) or hospital care in the last 5 years of life, and the place of death, could be attributed to differences in marital status and thereby to potential access to informal care. A longitudinal Swedish study provided register data on 567 participants (aged 83 +) who died between 1995 and 2004. A higher proportion of unmarried than married people used home help services; this was true of both men and women. The likelihood of receiving home help was lower for those living with their spouse (OR = 0.38) and for those with children (OR = 0.60). In the 2 years preceding death, the proportion receiving home help services decreased and the proportion in institutional care increased. Women were significantly more likely to die in institutional care (OR = 1.88) than men. Although men were less likely to live in institutional care than women and more likely to be inpatients in the 3 months preceding death, after controlling for residence in institutional care, neither gender nor marital status was statistically significant when included in the same model. In summary, the determining factor for home help utilisation seemed to be access to informal care, whereas gender differences in health status could explain women's higher probability of dying in institutional care.

Determinants of long-term care services among the elderly: a population-based study in Taiwan

Objectives

The aim of the study was to investigate determinants of long-term care use and to clarify the differing characteristics of home/community-based and institution-based services users.

Design

Cross-sectional, population-based study.

Setting

Utilizing data from the 2005 National Health Interview Survey conducted in Taiwan.

Participants

A national sample of 2,608 people (1,312 men, 1,296 women) aged 65 and older.

Measurements

The utilization of long-term care services (both home/community- and institution-based services) was measured. A χ² analysis tested differences in baseline characteristics between home/community-based and institution-based long-term care users. The multiple-logistic model was adopted with a hierarchical approach adding the Andersen model’s predisposing, enabling, and need factors sequentially. Multiple logistic models further stratified data by gender and age.

Results

Compared with users of home/community-based care, those using institution-based care had less education (p = 0.019), greater likelihood of being single (p = 0.001), fewer family members (p = 0.002), higher prevalence of stool incontinence (p = 0.011) and dementia (P = .025), and greater disability (p = 0.016). After adjustment, age (compared with 65–69 years; 75–79 years, odds ratio [OR] = 2.08, p = 0.044; age ≥80, OR = 3.30, p = 0.002), being single (OR = 2.16, p = 0.006), urban living (OR = 1.68, p = 0.037), stroke (OR = 2.08, p = 0.015), dementia (OR = 2.32, p = 0.007), 1–3 items of activities of daily living (ADL) disability (OR = 5.56, p<0.001), and 4–6 items of ADL disability (OR = 21.57, p<0.001) were significantly associated with long-term care use.

Conclusion

Age, single marital status, stroke, dementia, and ADL disability are predictive factors for long-term care use. The utilization was directly proportional to the level of disability.

The Economics of Long-Term Care

Long-term care expenditure is expected to rise, driven by an ageing population. Given that public long-term care expenditure is high in many OECD countries, governments are increasingly concerned about its future growth. This study focuses on three relevant issues. First, we discuss factors that affect the growth of long-term expenditure and its projections. These include demographics, the balance in provision between informal and formal care, whether higher life expectancy translates into higher disability, the interrelation between health and long-term care, and whether long-term care suffers from Baumol’s disease. Second, given that a significant proportion of long-term care expenditure is nursing- and care-home expenditure, we discuss the role of government regulation aimed at ensuring that individuals receive appropriate quality of care in such institutions. We focus in particular on price regulation, competition, and the non-profit sector; these have been the subject of considerable empirical work (mainly in the United States). Third, we discuss the relative merits of public and private insurance. Countries differ greatly in their approach. Some countries have nearly exclusively public insurance but in others this is small. We consider the conditions under which public insurance can overcome the limitations of a private insurance market.

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.

Use of hospital and long-term institutional care services in relation to proximity to death among older people in Finland

Using nationally-representative register data for older people in Finland in period 1998-2003 we study how the number of days in acute hospital and long term institutional care services varies by age and proximity to death and how these use patterns change as mortality improves. Acute health care use depends more on proximity to death than on age, a finding often interpreted as showing that the need for care services among older people will be substantially less than would be expected based on the likely increase in population numbers. We show that this assumption is too optimistic for three reasons: (1) the increase in population numbers will be concentrated mainly among the "old old" where use of services is substantial; (2) earlier findings of much lower use of acute care services by older than younger people who are close to death are not observed; and (3) any savings in acute care are more than offset by greater use of residential long-term care (LTC). The main consequences of improving mortality are: (1) to postpone rather than to reduce overall demand for health care; (2) to shift the balance of care from acute to long-term care services; and (3) to increase considerably the average age of time spent in care. We further construct a new indicator "care-free life expectancy" based on number of days in hospital and long-term care to summarise care use patterns for cohorts under a range of plausible mortality assumptions. As mortality improves, lifetime use of acute hospital and long-term care after age 65 and the proportion of life spent in LTC increases for later cohorts, but the proportion spent in acute care decreases slightly.

Does availability of informal care within the household impact hospitalisation?

This study assesses the effect of having informal support available at home on inpatient care use in Switzerland. The main contributions are to consider the availability of care regardless of its source, measured by multiple-adult living arrangements, and to examine this effect by type of inpatient care and source of potential support. A two-part model with region and time fixed effects is estimated to determine the impact of informal care availability on the likelihood of hospitalisation and length of stay, conditional on hospitalisation. The analysis is conducted on a sample of individuals aged 18+ from four waves of the Swiss Household Panel survey (2004-2007). Overall, availability of informal care has no impact on the likelihood of hospitalisation but does significantly reduce length of stay by 1.9 days. Available support has no effect on the shortest stays (up to 10 days), but has a significant impact on acute care stays up to 30 days and longer stays. Additionally, the effect does not significantly vary whether the source of informal support is a spouse only, a spouse and other adults, or other adults only. These results indicate that social changes leading to an expansion in the proportion of one-person households may increase future inpatient care use.

The role of young users in determining long-term care expenditure in Norway

AIMS

In Norway, it is the responsibility of the country's 429 municipalities to provide long term care (LTC) services to their residents. Recent years have seen a sharp rise in the number of LTC users under the age of 65. This article aims to explore the effect of this rise on LTC expenditure.

METHODS

Panel data models are used on data from municipalities from 1986 to 2011. An instrumental variable approach is also utilized to account for possible endogeneity related to the number of young users.

RESULTS

The number of young users appears to have a strong effect on LTC expenditure. There is also evidence of municipalities exercising discretion in defining eligibility criteria for young users in order to limit expenditure.

CONCLUSIONS

The rise in the number of young LTC users presents a long-term challenge to the sustainability of LTC financing. The current budgeting system appears to compensate municipalities for expenditure on young LTC users.

Modeling the relationship between health and health care expenditures using a latent Markov model

We investigate the dynamic relationship between several dimensions of health and health care expenditures for older individuals. Health data from the Longitudinal Aging Survey Amsterdam is combined with data on hospital and long term care use. We estimate a latent variable based jointly on observed health indicators and expenditures. Annual transition probabilities between states of the latent variable are estimated using a Markov model. States associated with good current health and low annual health care expenditures are not associated with lower cumulative health care expenditures over remaining lifetime. We conclude that, although the direct health care cost saving effect is limited, the considerable gain in healthy lifeyears can make investing in the improvement of health of the older population worthwhile.

Los(T) in long-term care: empirical evidence from German data 2000-2009

Using microdata, that is, representative samples of 114,403 German long-term care dependants (LTCDs) observed from 2000 to 2009, we give a comprehensive insight into the length of stay (LOS) in long-term care (LTC). Furthermore, this paper evaluates the effects of longevity on the LOS, thus revisiting the debate on the validity of the competing theories of compression or expansion of morbidity in LTC. The analysis finds significant effects on the LOS when AGE is controlled for, albeit do not confirm the time-to-death hypothesis. However, controlling for ASSESSMENT LEVEL suggests an improved health status of LTCDs over time, thus supporting the time-to-death hypothesis. An analysis of the mortality rates of LTCDs is to give insight into the opposing results. But the regression of mortality shows a divergence in the development of mortality rates for different disability levels. This is evidence to suggest that the 'improved' health status in LTC is not only due to actual changes in the health status, but also a consequence of political intervention.

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.

Mortality risk associated with disability: a population-based record linkage study

OBJECTIVES

We assessed the association between mortality and disability and quantified the effect of disability-associated risk factors.

METHODS

We linked data from cross-sectional health surveys in the Netherlands to the population registry to create a large data set comprising baseline covariates and an indicator of death. We used Cox regression models to estimate the hazard ratio of disability on mortality.

RESULTS

Among men, the unadjusted hazard ratio for activities of daily living, mobility, or mild disability defined by the Organization for Economic Co-operation and Development at age 55 years was 7.85 (95% confidence interval [CI] = 4.36, 14.13), 5.21 (95% CI = 3.19, 8.51), and 1.87 (95% CI = 1.58, 2.22), respectively. People with disability in activities of daily living and mobility had a 10-year shorter life expectancy than nondisabled people had, of which 6 years could be explained by differences in lifestyle, sociodemographics, and major chronic diseases.

CONCLUSIONS

Disabled people face a higher mortality risk than nondisabled people do. Although the difference can be explained by diseases and other risk factors for those with mild disability, we cannot rule out that more severe disabilities have an independent effect on mortality.

Exploring the influence of proximity to death on disease-specific hospital expenditures: a carpaccio of red herrings

It has been demonstrated repeatedly that time to death is a much better predictor of health care expenditures than age. This is known as the 'red herring' hypothesis. In this article, we investigate whether this is also the case regarding disease-specific hospital expenditures. Longitudinal data samples from the Dutch hospital register (n=11 253 455) were used to estimate 94 disease-specific two-part models. Based on these models, Monte Carlo simulations were used to assess the predictive value of proximity to death and age on disease-specific expenditures. Results revealed that there was a clear effect of proximity of death on health care expenditures. This effect was present for most diseases and was strongest for most cancers. However, even for some less fatal diseases, proximity to death was found to be an important predictor of expenditures. Controlling for proximity to death, age was found to be a significant predictor of expenditures for most diseases. However, its impact is modest when compared to proximity to death. Considering the large variation in the degree to which proximity to death and age matter for each specific disease, we may speak not only of age as a 'red herring' but also of a 'carpaccio of red herrings'.

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.

Predictors of the utilization of long-term care (LTC) services among residents in community-based LTC facilities in Taiwan

Identifying the utilization behaviors of LTC residents is necessary in order to forecast the demand and the level of resource use for health services. The purpose of this study is to understand the utilization behaviors and their predictors among residents of community-based LTC facilities in Taiwan. A prospective design was used in this study. Subjects were from six community-based LTC facilities in Beitou district of Taipei, Taiwan. A one-month time sheet was developed comprising subjects' socio-demographic characteristics, health status, and their use of LTC services. Among five types of LTC services examined in this study, assistance with activities of daily living (ADL) were the most commonly used (mean=67.3±46.0). ADL score was the strongest predictor of service utilization, accounting for 40% of the total variation in the utilization of personal assistance services (R2=0.396). The second most commonly used service was skilled-nursing services (mean=13.3±10.3). The most common skilled-nursing activities were administration of medication (mean=5.2±3.9) and measuring vital sign measurement (mean=3.4±2.3). The results provide useful information on how to allocate resources among staff in community-based LTC facilities.

Use of formal and informal care services among older people in Ireland and France

This paper focuses on current use of elderly care services in Ireland and France. In light of health care resource allocation problems, it is important to know the level of current use of home care on which future projections may be based. With the availability of SHARE (Survey of Health Ageing and Retirement in Europe) data, it is now possible to analyse this process and estimate the relationship between formal and informal care, and our econometric model tests for endogeneity of informal care. Previous research has not included Ireland into the analysis. Given that Ireland has a younger population base, lessons could be learned from countries with older populations, such as France. Results suggest informal care is endogenous and negatively linked with formal care in the pooled (France and Ireland) model. There is a higher unmet need for care in Ireland. These results have important policy implications for Ireland as the demographic makeup will change from 11 per cent to 15 per cent of older people over the next 10 years.