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BackgroundIn the Netherlands in 2020, COVID-19 deaths were more concentrated among individuals with a lower income. At the same time, COVID-19 was a new cause that also displaced some deaths from other causes, potentially reducing income-related inequality in non-COVID deaths. Our aim is to estimate the impact of the COVID-19 pandemic on the income-related inequality in total mortality and decompose this into the inequality in COVID-attributed deaths and changes in the inequality in non-COVID causes.MethodsWe estimate excess deaths (observed minus trend-predicted deaths) by sex, age and income group for the Netherlands in 2020. Using a measure of income-related inequality (the concentration index), we decompose the inequality in total excess mortality into COVID-19 versus non-COVID causes.ResultsCause-attributed COVID-19 mortality exceeded total excess mortality by 12% for the 65–79 age group and by about 35% for 80+ in the Netherlands in 2020, implying a decrease in the number of non-COVID deaths compared with what was predicted. The income-related inequality in all-cause mortality was higher than predicted. This increase in inequality resulted from the combination of COVID-19 mortality, which was more unequally distributed than predicted total mortality, and the inequality in non-COVID causes, which was less unequal than predicted.ConclusionThe COVID-19 pandemic has led to an increase in income-related inequality in all-cause mortality. Non-COVID mortality was less unequally distributed than expected due to displacement of other causes by COVID-19 and the potentially unequal broader societal impact of the pandemic.

Measuring performance in healthcare remains a challenge. The use of health outcomes rather than structure and process indicators is considered as the way forward, but outcome-based results risk being biased by selection. Accounting for such selection bias is more difficult in settings with small-sized providers and low chances of resident health improvement, like in the case of nursing homes. In this paper we (i) measure the health outcomes of Dutch nursing homes in terms of mortality and avoidable hospitalizations among residents, (ii) we adopt a novel approach to test for selection bias and (iii) we examine the relationship between outcomes and other nursing home quality indicators and characteristics. Using administrative data from more than 110,000 residents, we estimate the performance of the 849 largest nursing homes in the Netherlands in the period 2015–2019. Controlling for an extensive set of observable case-mix variables, we first test for the presence of selection bias using a distance-based instrumental variable. We do not find any evidence for such a structural bias. While the wide confidence intervals of the estimates display considerable imprecision, our results do reveal substantial differences between top and bottom performing nursing homes. Because the outcome-based estimates turn out to be only weakly correlated with other quality indicators, we conclude that our mortality and avoidable hospitalization-based indicators provide important complementary information. When small sample issues and case-mix differences are adequately accounted for, outcome-based indicators can provide useful policy guidance for quality improvement in nursing homes.

A cost-effectiveness analysis has become an important method to inform allocation decisions and reimbursement of new technologies in healthcare. A cost-effectiveness analysis requires a threshold to which the cost effectiveness of a new intervention can be compared. In principle, the threshold ought to reflect opportunity costs of reimbursing a new technology. In this paper, we contrast the practical use of this threshold within a CEA with its theoretical underpinnings. We argue that several assumptions behind the theoretical models underlying this threshold are violated in practice. This implies that a simple application of the decision rules of CEA using a single estimate of the threshold does not necessarily improve population health or societal welfare. Conceptual differences regarding the interpretation of the threshold, widely varying estimates of its value, and an inconsistent use within and outside the healthcare sector are important challenges in informing policy makers on optimal reimbursement decision and setting appropriate healthcare budgets.

We estimate the relationship between household mortgage debt and consumption for the period 2006 to 2015. Using Dutch administrative data, we find that the average consumption of households with high mortgage debt prior to the financial crisis has decreased much more during the crisis than that of other households. We also find that the willingness or ability among households to use new mortgage debt to finance one-off high consumption decreased during the crisis. On the macro-level, the drop in Dutch consumption during the financial crisis is predominantly driven by households who were already in high debt. They are responsible for a 7 percentage points drop in macro-consumption at the worst point of the financial crisis. Within this group, the drop in consumption of households with negative home equity explains 6 percentage point of the total drop in macro-consumption.

Co‐payments for long‐term care (LTC) can impose a substantial financial burden on the elderly. How this burden is distributed across income groups depends on the design of the co‐payment. We estimate the lifecycle dynamics of LTC using Dutch administrative data. These estimates are inputs in a stochastic lifecycle decision model. Using the model, we analyze the welfare effects of the Dutch income‐ and wealth‐ dependent co‐payment system and compare it to alternative systems. We find that the Dutch co‐payment system redistributes income to low‐income groups, who use the most care over their life but contribute the least co‐payments, from high‐income groups, who pay the most. Moreover, the Dutch system protects the middle‐income groups relatively well against financial risk: although alternative co‐payment systems hardly affect these groups average payments, they induce welfare losses of 2% to 4% due to an increased risk of very high co‐payments.

Background Costs of informal care are ignored in many cost-efectiveness analyses (CEAs) conducted from a societal perspective; however, these costs are relevant for lifesaving interventions targeted at the older population. In this study, weestimated 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-efects 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-efectiveness 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 infuence decisions as it leads to reranking of life-extending interventions compared with interventions improving quality of life.

We study the effect of hospital admissions for specific conditions on wealth for the Dutch population aged 70–79. We consider 14 disease groups that affect mortality and disability to different extents. We apply a “difference-in-timing” design comparing individuals admitted in one year to similar individuals admitted later. Because the protection against income risks and medical spending is high, we can identify changes in saving behaviors driven by preferences for consumption, saving, and bequests, rather than by changes in budget constraints. Although the health shocks differ in mortality and disability, we find hardly any impact on wealth across conditions.

To improve the quality of nursing home care, reliable estimates of outcomes are essential. Obtaining such estimates requires optimal use of limited data, especially for small homes. We analyze the variation in mortality and hospital admissions across nursing homes in the Netherlands during the years 2010–2013. We use administrative data on all nursing home clients. We apply mixed-effects survival models, empirical Bayes estimation, and machine-learning techniques to optimally use the available longitudinal data. We find large differences in both outcomes across nursing homes, yet the estimates are surrounded by substantial uncertainty. We find no correlation between performance on mortality and avoidable hospital admissions, suggesting that these are related to different aspects of quality. Hence, caution is needed when evaluating the performance of individual nursing homes, especially when the number of outcome indicators is limited.

Weinig economische begrippen leiden tot zoveel verwarring als ‘bezuinigen op de gezondheidszorg’. Patiënten en hulpverleners spreken van uitholling van de gezondheidszorg door bezuinigingen, terwijl beleidsmakers zich druk maken over de aanhoudende groei van de zorguitgaven.

We examine the impact of the accessibility of an older individual's house on her use of nursing home care. We link administrative data on the accessibility of all houses in the Netherlands to data on long‐term care use of all older persons from 2011 to 2014. We find that older people living in more accessible houses are less likely to use nursing home care. The effects increase with age and are largest for individuals aged 90 or older. The effects are stronger for people with physical limitations than for persons with cognitive problems. We also provide suggestive evidence that older people living in more accessible houses substitute nursing home care by home care.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans’ mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

Medical interventions that increase life expectancy of patients result in additional consumption of non-medical goods and services in 'added life years'. This paper focuses on the distributional consequences across socio-economic groups of including these costs in cost effectiveness analysis. In that context, it also highlights the role of remaining quality of life and household economies of scale. Data from a Dutch household spending survey was used to estimate non-medical consumption and household size by age and educational attainment. Estimates of non-medical consumption and household size were combined with life tables to estimate what the impact of including non-medical survivor costs would be on the incremental cost effectiveness ratio (ICER) of preventing a death at a certain age. Results show that including non-medical survivor costs increases estimated ICERs most strongly when interventions are targeted at the higher educated. Adjusting for household size (lower educated people less often live additional life years in multi-person households) and quality of life (lower educated people on average spend added life years in poorer health) mitigates this difference. Ignoring costs of non-medical consumption in economic evaluations implicitly favors interventions targeted at the higher educated and thus potentially amplifies socio-economic inequalities in health.

Significance From 1990 to 2018, the Black–White American life expectancy gap fell 48.9% and mortality inequality decreased, although progress stalled after 2012 as life expectancy plateaued. Had improvements continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. Despite decreasing mortality inequality, income-based life expectancy gaps remain starker in the United States than in European countries. At the same time, European mortality improved strongly and even those U.S. populations with the longest life spans–White Americans living in the highest-income areas–experience higher mortality at all ages than Europeans in high-income areas in 2018. Hence, mortality rates of both Black and White Americans could fall much further in both high-income and low-income areas., Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans’ mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

This paper analyses the returns to publicly performed R&D investments in 22 OECD countries. We exploit a dataset containing time-series from 1963 to 2011 and compare the estimates of different types of production function models. Robustness analyses are performed to test the sensitivity of the outcomes for particular specifications, sample selections, assumptions about the construction of R&D stocks, and variable definitions. Analyses based on Cobb–Douglas and translog production functions mostly yield statistically insignificant or negative returns. In these models we control for private and foreign R&D investments and the primary production factors. Models including additional controls, such as public capital, the stock of inward and outward foreign direct investment, and the shares of high-tech imports and exports, yield more positive returns. Our findings suggest that publicly performed R&D investments do not automatically foster GDP and TFP growth in production function models. Furthermore, our estimates suggest that economic returns to publicly performed R&D seem to depend on the specific national context.

We analyse the trends in inequality in mortality across poverty groups at different ages over the period 1996–2016 in the Netherlands. In addition, we examine whether these trends are related to unequal changes in avoidable mortality, separated by preventable and treatable causes of death. We find that while inequalities in mortality have decreased at ages up to 65, inequalities increased for the oldest age groups. The decline in inequality at the younger ages can, to a large extent, be explained by a strong decrease of mortality from preventable and cardiovascular causes among the poor. The link between inequality and avoidable mortality at the oldest ages is less straightforward. The increasing inequality at old age might be the result of the inequalities shifting from the young to the older age groups, or of the rich benefiting more from the recent health (care) improvements than the poor.

Encouraging and helping elderly to postpone a nursing home admission appears to be a win-win that keeps long-term care spending in check and is in line with the target population's preferences, but there is little evidence about its effects. We study the causal impact of nursing home admission eligibility using Dutch administrative data and exploiting variation between randomly assigned assessors in their tendency to grant eligibility for a nursing home admission. We find a drop in medical care use when eligibility is granted, especially in hospital admissions, while total healthcare spending is unaffected. This suggests that postponing an admission may not always be a win-win after all.

Background There has been a shift from institutional care towards home care, and from formal to informal care to contain long-term care (LTC) costs in many countries. However, substitution to home care or informal care might be harder to achieve for some conditions than for others. Therefore, insight is needed in differences in LTC use, and the role of potential informal care givers, across specific conditions. We analyze differences in LTC use of previously independent older patients after a fracture of femur and stroke, and in particular examine to what extent having a partner and children affects LTC use for these conditions. Methods Using administrative data on Dutch previously independent older people (55+) with a fracture of femur or stroke in 2013, we investigate their LTC use in the year after the condition takes place. We use administrative treatment data to select individuals who were treated by a medical specialist for a stroke or femoral fracture in 2013. Subsequent LTC use is measured as using no formal care, home care, institutional care or being deceased at 13 consecutive four-weekly periods after initial treatment. We relate long-term care use to having a partner, having children, other personal characteristics and the living environment. Results The probability to use no formal care 1 year after the initial treatment is equally high for both conditions, but patients with a fracture are more likely to use home care, while patients with a stroke are more likely to use institutional care or have died. Having a spouse has a negative effect on home care and institutional care use, but the timing of the effect, especially for institutional care, differs strongly between the two conditions. Having children also has a negative effect on formal care use, and this effect is consistently larger for patients with a fracture than patients with a stroke. Conclusion As the condition and the effect of potential informal care givers matter for subsequent long-term care use, policy makers should take the expected prevalence of specific conditions within the older people population into account when designing long-term care policies.

Including the costs of non-medical consumption in life years gained in economic evaluations of medical interventions has been controversial. This paper focuses on the estimation of these costs using Dutch data coming from cross-sectional household surveys consisting of 56,569 observations covering the years 1978–2004. We decomposed the costs of consumption into age, period and cohort effects and modelled the non-linear age and cohort patterns of consumption using P-splines. As consumption patterns depend on household composition, we also estimated household size using the same regression modeling strategy. Estimates of non-medical consumption and household size were combined with life tables to estimate the impact of including non-medical survivor costs on an incremental cost-effectiveness ratio (ICER). Results revealed that including non-medical survivor costs substantially increases the ICER, but the effect varies strongly with age. The impact of cohort effects is limited but ignoring household economies of scale results in a significant overestimation of non-medical costs. We conclude that a) ignoring the costs of non-medical consumption results in an underestimation of the costs of life prolonging interventions b) economies of scale within households with respect to consumption should be accounted for when estimating future costs.

Long-term care expenditures in the Netherlands have risen substantially over the last 40 years. Only a part of this growth can be attributed to the ageing of the population. Rising long-term care costs threaten the sustainability of Dutch public finances: additional public revenues are needed to cover the additional spending. In this paper, we evaluate four alternative policies to finance the anticipated additional growth in long-term care above the rate implied by projected demographic growth. We analyse these financing alternatives using a macro model, focusing on the long-term effects on economic growth and on the redistribution of costs and benefits between birth cohorts. We find a relatively large intergenerational redistribution of lifetime net benefits for a pay-as-you-go system and for an immediate one-time increase of the premium rate, while a cohort-specific savings system or a pensioner tax both have relatively small intergenerational effects. Labour supply and private consumption decline in all four financing alternatives, although the size and timing of these effects differ.

Aging-in-place policies substitute home care for nursing home admissions (NHA). They appear to be a win-win by keeping public spending in check and being in line with personal preferences, but have hitherto not been evaluated. We study the impact of NHA eligibility using Dutch administrative data and exploiting variation between randomly assigned assessors in their tendency to grant admission. The impact on mortality is zero, but with considerable effect heterogeneity. Moreover, aging-in-place policies come at the cost of increased curative care, especially hospital admissions, and do not reduce total healthcare spending, suggesting they may not be a win-win after all.

In this paper we investigate individual income differences between individuals with Master and PhD degrees over the first 20 years of a career. We compare monthly incomes of Dutch higher education graduates with the same years of experience, gender and field of study. It turns out that over the first 20 years of experience, the average annual return to a PhD education is not significantly different from zero. During the PhD track and the first years after PhD graduation PhDs earn less than Masters, but this is compensated by higher earnings in later years. Income differences differ strongly by sex.

Contains fulltext : 155179.pdf (Publisher’s version ) (Open Access) BACKGROUND: Organizational data such as bed occupancy rate and nurse-to-patient ratio are related to clinical outcomes and to the efficient use of intensive care unit (ICU) resources. Standards for these performance indicators are provided in guidelines. We studied the effects of a multifaceted feedback strategy to improve the adherence to these standards. METHODS: In a cluster randomized controlled study design the intervention ICUs received extensive monthly feedback reports, they received outreach visits and initiated a quality improvement team. The control ICUs received limited quarterly feedback reports only. We collected primary data prospectively within the setting of a Dutch national ICU registry over a 14-month study period. The target indicators were bed occupancy rate (aiming at 80 % or below) and nurse-to-patient ratio (aiming at 0.5 or higher). Data were collected per 8-h nursing shift. Logistic regression analysis was performed. For both study end points, the odds ratios (OR) for improvements at follow-up versus at baseline were calculated separately for control and intervention ICUs. RESULTS: We analyzed data on 67,237 nursing shifts. The bed occupancy rate did not improve in the intervention group compared to baseline (adjusted OR 0.88; 95 % confidence interval (CI), 0.62-1.27) or compared to control group (OR 0.67; 95 % CI 0.39-1.15). The nurse-to-patient ratio did not improve (OR 0.72; 95 % CI 0.41-1.26 compared to baseline and OR 0.65; 95 % CI 0.35-1.19 compared to control group). CONCLUSIONS: A multifaceted feedback intervention did not improve the adherence to guideline-based standards on the organizational issues bed occupancy rate and nurse-to-patient ratio in the ICU. The reasons may be a limited confidence in data quality, the lack of practical tools for improvement, and the relatively short follow-up. TRIAL REGISTRATION: ISRCTN: ISRCTN50542146.

Expenditures on long term care in the Netherlands have risen substantially over the last decades. Only a part of this growth can be attributed to ageing of the population. These rising costs are one of the main concerns for sustainability of future public finances. We define long term sustainability of public finances as a situation where future generations can benefit from the same public arrangements as current generations without having to raise taxes in the future. Given this definition, growth in long term care expenditures due to changing demographics should be taken into account in determining the sustainability gap. For growth due to other factors this is less clear. When rising expenditures are related to a better quality of health services per patient in the future, it makes sense to let future generations finance this care themselves. In this paper, we evaluate different alternatives to finance additional long term care growth on top of the demographic component. We analyze these alternatives using a macro model for the long term development of the Dutch economy. We focus on the consequences of different financing schemes for the redistribution of costs and benefits between birth-cohorts. We find relatively large intragenerational redistribution of lifetime net benefits for a pay-as-yougo system or an immediate one-time increase in taxes, while a cohort-specific savings system or an “elderly tax” have relatively small intergenerational consequences. We also find that all financing options have a negative effect on labour supply and private consumption.

The European Union has formulated an increase in healthy life expectancy (HLE) by two years as one of the Horizon 2020 goals. Given the increasing prevalence of multimorbidity, it is important to limit the disabling effect of chronic diseases, and thus increase disability-free life expectancy. This MOPACT-study considers the promotion of social participation among older individuals with multimorbidity as one of the tools to do so. Three scenarios that foster social engagement in older people with multimorbidity are generated, and the effects of these scenarios on HLE are assessed for sixteen European countries. We found only very modest effects on HLE. Our most realistic scenario results in improvements in HLE between 0 and 0.1 years. We conclude that substantial increases in HLE cannot be expected to come from a single intervention alone but will have to be the result of combined efforts on several fronts.