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Background Worldwide, socioeconomic differences in health and use of healthcare resources have been reported, even in countries providing universal healthcare coverage. However, it is unclear how large these socioeconomic differences are for different types of care and to what extent health status plays a role. Therefore, our aim was to examine to what extent healthcare expenditure and utilization differ according to educational level and income, and whether these differences can be explained by health inequalities. Methods Data from 18,936 participants aged 25–79 years of the Dutch Health Interview Survey were linked at the individual level to nationwide claims data that included healthcare expenditure covered in 2017. For healthcare utilization, participants reported use of different types of healthcare in the past 12 months. The association of education/income with healthcare expenditure/utilization was studied separately for different types of healthcare such as GP and hospital care. Subsequently, analyses were adjusted for general health, physical limitations, and mental health. Results For most types of healthcare, participants with lower educational and income levels had higher healthcare expenditure and used more healthcare compared to participants with the highest educational and income levels. Total healthcare expenditure was approximately between 50 and 150 % higher (depending on age group) among people in the lowest educational and income levels. These differences generally disappeared or decreased after including health covariates in the analyses. After adjustment for health, socioeconomic differences in total healthcare expenditure were reduced by 74–91 %. Conclusions In this study among Dutch adults, lower socioeconomic status was associated with increased healthcare expenditure and utilization. These socioeconomic differences largely disappeared after taking into account health status, which implies that, within the universal Dutch healthcare system, resources are being spent where they are most needed. Improving health among lower socioeconomic groups may contribute to decreasing health inequalities and healthcare spending.

IntroductionEven in advanced economies with universal healthcare coverage (UHC), a social gradient in healthcare utilisation has been reported. Many individual, community and healthcare system factors have been considered that may be associated with the variation in healthcare utilisation between socioeconomic groups. Nevertheless, relatively little is known about the complex interaction and relative contribution of these factors to socioeconomic differences in healthcare utilisation. In order to improve understanding of why utilisation patterns differ by socioeconomic status (SES), the proposed systematic review will explore the main mechanisms that have been examined in quantitative research.Methods and analysisThe systematic review will follow the Preferred Reporting Items for Systematic Review and Meta-Analyses guidelines and will be conducted in Embase, PubMed, Scopus, Web of Science, Econlit and PsycInfo. Articles examining factors associated with the differences in primary and specialised healthcare utilisation between socioeconomic groups in Organisation for Economic Co-operation and Development (OECD) countries with UHC will be included. Further restrictions concern specifications of outcome measures, factors of interest, study design, population, language and type of publication. Data will be numerically summarised, narratively synthesised and thematically discussed. The factors will be categorised according to existing frameworks for barriers to healthcare access.Ethics and disseminationNo primary data will be collected. No ethics approval is required. We intend to publish a scientific article in an international peer-reviewed journal.

Samenvatting Inleiding We hebben berekend hoeveel er in 2015 aan preventie is uitgegeven. We maakten onderscheid tussen gezondheidsbescherming, gezondheidsbevordering en ziektepreventie. Bij de berekening van de uitgaven beperkten we ons tot universele, selectieve en geïndiceerde preventie. Zorggerelateerde preventie kan nauwelijks onderscheiden worden van curatieve zorg. De uitgaven aan preventie zijn berekend vanuit een maatschappelijk perspectief. Methode We hebben gevarieerde bronnen gebruikt om de uitgaven aan preventie te onderzoeken. Voor zover de kosten onderdeel waren van de uitgaven aan zorg zijn de berekeningen gebaseerd op de gegevens van het CBS. Voor het overige is gebruikgemaakt van jaarrapporten en jaarrekeningen van ministeries en andere organisaties. Ook uitgaven van consumenten, het bedrijfsleven, ngo’s en verzekeringsmaatschappijen zijn opgenomen. Resultaten In 2015 werd 12,5 miljard euro (1,8% van het bruto binnenlands product) uitgegeven aan preventie: 2,4 miljard aan ziektepreventie (18,8%), 0,6 miljard aan gezondheidsbevordering (5,2%) en 9,5 miljard aan gezondheidsbescherming (76%). Dit is 17% minder dan er in 2007 is uitgegeven, het laatste jaar dat een dergelijk onderzoek is uitgevoerd. Conclusie De uitgaven aan preventie zijn relatief laag vergeleken met de totale uitgaven aan zorg. Het grootste gedeelte gaat naar gezondheidsbescherming. In de komende jaren is er mogelijk een stijging aan uitgaven voor gezondheidsbevordering door regeringsbeleid, zoals het Nationaal Preventieakkoord.

Background Aggregated claims data on medication are often used as a proxy for the prevalence of diseases, especially chronic diseases. However, linkage between medication and diagnosis tend to be theory based and not very precise. Modelling disease probability at an individual level using individual level data may yield more accurate results. Methods Individual probabilities of having a certain chronic disease were estimated using the Random Forest (RF) algorithm. A training set was created from a general practitioners database of 276 723 cases that included diagnosis and claims data on medication. Model performance for 29 chronic diseases was evaluated using Receiver-Operator Curves, by measuring the Area Under the Curve (AUC). Results The diseases for which model performance was best were Parkinson’s disease (AUC = .89, 95% CI = .77–1.00), diabetes (AUC = .87, 95% CI = .85–.90), osteoporosis (AUC = .87, 95% CI = .81–.92) and heart failure (AUC = .81, 95% CI = .74–.88). Five other diseases had an AUC >.75: asthma, chronic enteritis, COPD, epilepsy and HIV/AIDS. For 16 of 17 diseases tested, the medication categories used in theory-based algorithms were also identified by our method, however the RF models included a broader range of medications as important predictors. Conclusion Data on medication use can be a useful predictor when estimating the prevalence of several chronic diseases. To improve the estimates, for a broader range of chronic diseases, research should use better training data, include more details concerning dosages and duration of prescriptions, and add related predictors like hospitalizations.

Diverse maatschappelijke ontwikkelingen roepen de vraag op of we over de juiste kennis beschikken om de (potentiele) werkende bevolking duurzaam inzetbaar te houden. In samenwerking met vertegenwoordigers uit de praktijk, beleid en wetenschap heeft het RIVM het initiatief genomen een kennisagenda op het brede domein van Arbeid en Gezondheid te ontwikkelen. Hiertoe zijn interviews gehouden en is een werkconferentie gehouden met vertegenwoordigers uit praktijk, beleid en wetenschap. Dit heeft geresulteerd in een kennisagenda met 9 thema’s: wisselwerking arbeid en gezondheid, duurzame inzetbaarheid, preventie, arbeid en zorg, technologische ontwikkelingen, flexibilisering, psychische gezondheid, (her)waardering van werk, en inclusieve arbeidsmarkt. Naast behoefte aan kennisontwikkeling is de indruk dat bestaande preventieve interventies niet bekend zijn bij professionals in de praktijk en daardoor onvoldoende benut worden. Verspreiding van bestaande kennis verdient aandacht. Van belang is dat alle stakeholders kennisontwikkeling initieren om de kennisvraagstukken op te pakken teneinde de gezondheid van werkenden te bevorderen.

Objectives In many Western societies, the state pension age is being raised to stimulate prolonged working. In the Netherlands, the raise of the state pension age is linked to the remaining life expectancy at age 65 with a factor of 2/3rd, and is expected to be 68 years in 2040. It is not yet well understood whether health of the 60+ permits this increase. In this study, health of Dutch adults aged 60 to 68 is forecasted up to 2040. Methods Data are from the Dutch Health Interview Survey (HIS) 1990-2017 (N≈280.000) and the Dutch Public Health Monitor (PHM) 2016 (N≈460.000). Health is operationalized using binomial scores of 1) self-rated health and 2) limitations in hearing, seeing or mobility. Categories are: good health (healthy on both items), moderate health (healthy on one item) and poor health (unhealthy on both items). First, based on the HIS, health status in 5-year age categories was modelled up to 2040 using logistic regression analysis in R. Second, the growth factor from 2016 to 2040 was applied to the health level from the PHM 2016. Results In 2016, 63% of men aged 60-65 had good health, 25% had moderate health and 12% had poor health. Among women, this distribution was 64%, 22% and 14%, respectively. In 2040, the health distribution among men aged 60-68 is estimated to be 63-71% in good health, 17-28% in moderate health and 9-12% in poor health. Among women this is estimated to be 64-69%, 17-24% and 12-14%, respectively. Conclusions Health of Dutch cohorts nearing the state pension age in the future is estimated to remain the same or improve up to 2040. This development in health is not an obstacle to raising the state pension age. However, due to the increasing state pension age and the baby boom generation reaching age 60+ in the coming years, the absolute number of people aged 60+ in poor and moderate health that participates in labor will increase. Policy aiming at sustainable employability will therefore become increasingly important. Key messages Health of Dutch cohorts nearing the state pension age is estimated to remain the same or improve in the future. The development in health is not an obstacle to raising the state pension age. Although health is estimated to remain the same or improve, the absolute number of people aged 60+ in poor and moderate health that participate in labor will increase due to an aging population.

Item does not contain fulltext The recent epidemic of Ebola virus disease (EVD) resulted in countries worldwide to prepare for the possibility of having an EVD patient. In this study, we estimate the costs of Ebola preparedness and response borne by the Dutch health system. An activity-based costing method was used, in which the cost of staff time spent in preparedness and response activities was calculated based on a time-recording system and interviews with key professionals at the healthcare organizations involved. In addition, the organizations provided cost information on patient days of hospitalization, laboratory tests, personal protective equipment (PPE), as well as the additional cleaning and disinfection required. The estimated total costs averaged euro12.6 million, ranging from euro6.7 to euro22.5 million. The main cost drivers were PPE expenditures and preparedness activities of personnel, especially those associated with ambulance services and hospitals. There were 13 possible cases clinically evaluated and one confirmed case admitted to hospital. The estimated total cost of EVD preparedness and response in the Netherlands was substantial. Future costs might be reduced and efficiency increased by designating one ambulance service for transportation and fewer hospitals for the assessment of possible patients with a highly infectious disease of high consequences.

Background Since in an ageing society more long-term care (LTC) facilities are needed, it is important to understand the main determinants of first-time utilization of (LTC) services. Methods The Andersen service model, which distinguishes predisposing, enabling and need factors, was used to develop a model for first-time utilization of LTC services among the general population of the Netherlands. We used data on 214,821 persons registered in a database of general practitioners (NIVEL Primary Care Database). For each person the medical history was known, as well as characteristics such as ethnicity, income, home-ownership, and marital status. Utilization data from the national register on long-term care was linked at a personal level. Generalized Linear Models were used to determine the relative importance of factors of incident LTC-service utilization. Results Top 5 determinants of LTC are need, measured as the presence of chronic diseases, age, household size, household income and homeownership. When controlling for all other determinants, the presence of an additional chronic disease increases the probability of utilizing any LTC service by 45% among the 20+ population (OR = 1.45, 95% CI: 1.41–1.49), and 31% among the 65+ population (OR = 1.31, 95% CI: 1.27–1.36). With respect to the 20+ population, living in social rent (OR = 2.45, 95% CI = 2.25–2.67, ref. = home-owner) had a large impact on utilizing any LTC service. In a lesser degree this was the case for living alone (OR = 1.63, 95% CI = 1.52–1.75, ref. = not living alone). A higher household income was linked with a lower utilization of any LTC service. Conclusions All three factors of the Anderson model, predisposing, enabling, and need determinants influence the likelihood of future LTC service utilization. This implies that none of these factors can be left out of the analysis of what determines this use. New in our analysis is the focus on incident utilization. This provides a better estimate of the effects of predictors than a prevalence based analysis, as there is less confounding by changes in determinants occurring after LTC initiation. Especially the need of care is a strong factor. A policy implication of this relative importance of health status is therefore that LTC reforms should take health aspects into account. Electronic supplementary material The online version of this article (10.1186/s12913-017-2570-z) contains supplementary material, which is available to authorized users.

Introduction In November 2018, the Ministry of Health, Welfare and Sports presented the National Prevention Agreement (NPA). Within this NPA, interventions targeting smoking, being overweight and problematic alcohol use were proposed to induce lifestyle changes. In addition to measures aimed at these three themes, there is also a range of interventions that are promising, either because they could be cost saving or cost-effective, or because they have a positive impact on burden of disease. We explored which preventive interventions are promising in the Dutch context and systematically quantified costs, savings and health effects. Methods In a literature search via the website kosteneffectviteitvanpreventie.nl we selected interventions that: a) have not yet been introduced in the Netherlands; and b) were promising with respect to effectiveness and cost-effectiveness. All interventions, including health protection and environmental measures, were eligible. We estimated the number of people who are eligible and compliant, costs and possible savings related to the interventions and health effects in terms of DALYs avoided. Interventions were ranked with regard to possible savings and DALYs avoided. Results Our exploration shows a number of preventive interventions that are cost saving or cost-effective. These interventions are aimed at anxiety and depression, heart disease, skin cancer, fractures, air quality and road safety. Examples of cost-saving or cost-effective interventions are a food tax on food and drinks with high fat/sugar content, screening an aneurysm of the aorta and fully subsidized sound insulation of homes. Conclusions Our study shows that there are much more preventive opportunities than those presented in the NPA. The substantiation of the interventions is often based on foreign research and findings therefore cannot be simply translated to the Netherlands. However, the interventions identified in this study are promising and deserve further consideration. Key messages Health gain by environmental measures. Many interventions are not systematically implemented.

Background In the Netherlands, toxoplasmosis ranks third in disease burden among foodborne pathogens, with an estimated health loss of 1,900 Disability Adjusted Life Years and a cost-of-illness estimated at €44 million annually. We performed a Social Cost-Benefit Analysis (SCBA) to evaluate the net value of two potential interventions, freezing meat and improving biosecurity in pig farms, for the Dutch society. Methods We assessed the costs and benefits of the two interventions and compared them with the current practice of education, especially during pregnancy. A ‘minimum scenario’ and a ‘maximum scenario’ was assumed, using input parameters with least benefits to society and input parameters with most benefits to society, respectively. Results The freezing meat intervention was far more effective than the biosecurity intervention. Despite high freezing costs, freezing two meat products: steak tartare and mutton leg yielded net social benefits in both the minimum and maximum scenario, ranging from €10.6 million to €31 million for steak tartare and €0.6 million to €1.5 million for mutton leg. The biosecurity intervention would result in net costs in all scenarios ranging from €1 million to €2.5 millions. Conclusions From a public health perspective (i.e. reducing the burden of toxoplasmosis) freezing steak tartare and leg of mutton is to be considered.

Introduction In 2015, Dutch healthcare expenditure exceeded 85 billion euros. But what about prevention? In this study we estimated national expenditure on prevention. A distinction was made between health protection, health promotion and disease prevention. In the estimation of prevention expenditures, this study is limited to universal, selective and indicated prevention, as healthcare-related prevention can hardly be distinguished from curative care. This study analyzed expenditure on preventive activities in the Netherlands in 2015 and took a societal perspective. Methods We used various sources to investigate spending on prevention in 2015. Insofar as costs were part of healthcare expenditure, estimates were based on the Care Accounts of Statistics Netherlands. For the remainder, we estimated expenditure using annual reports and annual accounts of governments and other organizations. We included preventive activities by consumers, industry, NGOs, insurance companies, and government. Results In 2015, an estimated € 12.4 billion (1.8% of the GDP) was spent on prevention: € 2.4 billion on disease prevention (19%), € 0.6 billion on health promotion (5%) and € 9.4 billion on health protection (76%). This is a decrease of 17% compared to 2007, the last year that a similar estimate was made. Within health promotion, the largest expenditure was for working conditions and safety: € 160 million. € 67 million was spent on mental disorders. The largest expenditure item within disease prevention was dental care: € 675 million. Within health protection, this was the sewer by more than € 3 billion. Conclusions Spending on prevention is relatively low compared to total spending on healthcare. The largest part is targeted at health protection. In the coming years there may be an increase in expenditure, due to more governmental prevention policies such as the National Prevention Agreement. Key messages Spending on prevention is relatively low compared to total spending on healthcare. Relatively little money for health protection.

People often intend to exercise but find it difficult to attend their gyms on a regular basis. At times, people seek and accept deadlines with consequences to realize their own goals (i.e. commitment devices). The aim of our cluster randomized controlled trial is to test whether a lottery-based commitment device can promote regular gym attendance. The winners of the lottery always get feedback on the outcome but can only claim their prize if they attended their gyms on a regular basis. In this paper we present the design and baseline characteristics of a three-arm trial which is performed with 163 overweight participants in six in-company fitness centers in the Netherlands.Keywords: Physical activity, Cluster randomized trial, Lottery deadline, Commitment device

Consumption of raw or undercooked meat increases the risk of infection with Toxoplasma gondii. Freezing meat products can eliminate this risk. Freezing of meat may affect consumers' valuation of meat products in two different ways: it may be valued positively because of increased food safety or valued negatively because of (perceived) loss of quality. In a Discrete Choice Experiment on four different meat products we studied the difference in willingness to pay for frozen and non-frozen meat products in the Netherlands. Analyses revealed that most Dutch consumer groups prefer non frozen meat. Price was important in consumer decisions, whereas the meat being frozen appeared to play a minor role in the decision to purchase meat products. Even though it may seem obvious that people would prefer safe food to unsafe food, in a context where consumers presume food being safe, many consumers appear unwilling to pay for freezing of meat as additional measure to reduce the risk of food borne infections such as toxoplasmosis.

BackgroundAlthough job loss has been associated with decline in health, the effect of long term unemployment is less clear and under-researched. Furthermore, the impact of an economic recession on this relationship is unclear. We investigated the associations of single transitions and persistence of unemployment with health. We subsequently examined whether these associations are affected by the latest recession, which began in 2008.MethodsIn total, 57,911 participants from the Dutch Health Interview Survey who belonged to the labour force between 2004 and 2014 were included. Based on longitudinal tax registration data, single employment transitions between time point 1 (t1) and time point 2 (t2) and persistent unemployment (i.e. number of years individuals were unemployed) between t1 and time point 5 (t5) were defined. General and mental health, smoking and obesity were assessed at respectively time point 3 (t3) and time point 6 (t6). Logistic regression models were performed and interactions with recession indicators (year, annual gross domestic product estimates and regional unemployment rates) were tested.ResultsCompared with individuals who stayed employed at t1 and t2, the likelihood of poor mental health at the subsequent year was significantly higher in those who became unemployed at t2. Persistent unemployment was associated with poor mental health, especially for those who were persistently unemployed for 5 years. Similar patterns, although less pronounced for smoking, were found for general health and obesity. Indicators of the economic recession did not modify these associations.ConclusionsSingle transitions into unemployment and persistent unemployment are associated with poor mental and general health, obesity, and to a lesser extend smoking. Our study suggests that re-employment might be an important strategy to improve health of unemployed individuals. The relatively extensive Dutch social security system may explain that the economic recession did not modify these associations.

Psychologically designed lottery-deadlines promoted gym attendance among overweight adults. The combination of weekly commitment lotteries and an additional long-term lottery yielded the most durable effects., Background The World Health Organization has identified physical inactivity as the fourth leading risk factor for global mortality. People often intend to engage in physical activity on a regular basis, but have trouble doing so. To realize their health goals, people can voluntarily accept deadlines with consequences that restrict undesired future behaviors (i.e., commitment devices). Purpose We examined if lottery-based deadlines that leverage regret aversion would help overweight individuals in attaining their goal of attending their gym twice per week. At each deadline a lottery winner was drawn from all participants. The winners were only eligible for their prize if they attained their gym-attendance goals. Importantly, nonattending lottery winners were informed about their forgone prize. The promise of this counterfactual feedback was designed to evoke anticipated regret and emphasize the deadlines. Methods Six corporate gyms with a total of 163 overweight participants were randomized to one of three arms. We compared (i) weekly short-term lotteries for 13 weeks; (ii) the same short-term lotteries in combination with an additional long-term lottery after 26 weeks; and (iii) a control arm without lotteries. Results After 13 weeks, participants in the lottery arms attained their attendance goals more often than participants in the control arm. After 26 weeks, we observe a decline in goal attainment in the short-term lottery arm and the highest goal attainment in the long-term lottery arm. Conclusions With novel applications, the current research adds to a growing body of research that demonstrates the effectiveness of commitment devices in closing the gap between health goals and behavior. Clinical Trial information This trial is registered in the Dutch Trial Register. Identifier: NTR5559

To overcome self-control difficulties, people can commit to their health goals by voluntarily accepting deadlines with consequences. In a commitment lottery, the winners are drawn from all participants, but can only claim their prize if they also attained their gym-attendance goals. In a 52-week, three-arm trial across six company gyms, we tested if commitment lotteries with behavioral economic underpinnings would promote physical activity among overweight adults. In previous work, we presented an effective 26-week intervention. In the present paper we analyzed maintenance of goal attainment at 52-week follow-up and the development of weight over time. We compared weight and goal attainment (gym attendance ≥ 2 per week) between three arms that—in the intervention period- consisted of (I) weekly short-term lotteries for 13 weeks; (II) the same short-term lotteries in combination with an additional long-term lottery after 26 weeks; and (III) a control arm without lottery-deadlines. After a successful 26-week intervention, goal attainment declined between weeks 27 and 52 in the long-term lottery arm, but remained higher than in the control group. Goal attainment did not differ between the short-term lottery arm and control arm. Weight declined slightly in all arms in the first 13 weeks of the trial and remained stable from there on. Commitment lotteries can support regular gym attendance up to 52 weeks, but more research is needed to achieve higher levels of maintenance and weight loss.

Summary The rise in healthcare expenditures has raised doubts about the sustainability of health systems and instigated a discussion on their design. Policy making in this field requires a proper understanding of how healthcare expenditures evolve throughout an individual's lifetime, and of how they vary between individuals. Given the lack of data on healthcare expenditures during an individual's lifetime, we developed a new nearest neighbour resampling approach to construct realistic individual life cycles of healthcare expenditures based on cross-sectional data from the Netherlands. This approach provides insight into lifetime healthcare expenditures. Our main finding is that the inequality in lifetime healthcare expenditures is much smaller than the inequality as derived from cross-sectional healthcare expenditures.

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. © 2012 Elsevier B.V.

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. Keywords: Population aging, Morbidity, Technology, Health expenditures, Acute care, Long-term care

Item does not contain fulltext BACKGROUND: In The Netherlands, 1168 Q-fever patients were notified in 2007 and 2008. Patients and general practitioners (GPs) regularly reported persisting symptoms after acute Q-fever, especially fatigue and long periods of sick leave, to the public health authorities. International studies on smaller Q-fever outbreaks demonstrate that symptoms may persist years after acute illness. Data for the Dutch outbreaks were unavailable. The aim of this study is to quantify sick leave after acute Q-fever and long-term symptoms. METHODS: Our study targeted 898 acute Q-fever patients, notified in 2007 and 2008 residing in the Province Noord-Brabant. Patients from the 2008 cohort were mailed a questionnaire at 12 months and those of the 2007 cohort at 12-26 months after onset of illness. Patients reported underlying illness, Q-fever-related symptoms and sick leave. RESULTS: The response rate was 64%. Forty percent of the working patients reported long-term (>1 month) sick leave. Pre-existent heart disease odds ratio (OR) 4.50; confidence interval (CI) 1.27-16.09), hospitalization in the acute phase (OR 3.99; 95% CI 2.15-7.43) and smoking (OR 1.69; 95% CI 1.01-2.84) were significant predictors for long-term absence. Of the patients who resumed work, 9% were-at the time of completing the questionnaire-still unable to function at pre-infection levels due to fatigue or concentration problems. Of the respondents, 40% reported persisting physical symptoms at the time of follow-up. Fatigue (20%) was most frequently reported. Daily activities were affected in 30% of cases. CONCLUSIONS: Q-fever poses a serious persisting long-term burden on patients and society.

Health care utilization is expected to rise in the coming decades. Not only will the aggregate need for health care grow by changing demographics, so too will per capita utilization. It has been suggested that trends in health care utilization may be age-specific. In this paper, age-specific trends in health care utilization are presented for different health care sectors in the Netherlands, for the period 1981-2009. For the hospital sector we also explore the link between these trends and the state of medical technology. Using aggregated data from a Dutch health survey and a nationwide hospital register, regression analysis was used to examine age-specific trends in the probability of utilizing health care. To determine the influence of medical technology, the growth in age-specific probabilities of hospital care was regressed on the number of medical patents while adjusting for confounders related to demographics, health status, supply and institutional factors. The findings suggest that for most health care sectors, the trend in the probability of health care utilization is highest for ages 65 and up. Larger advances in medical technology are found to be significantly associated with a higher growth of hospitalization probability, particularly for the higher ages. Age-specific trends will raise questions on the sustainability of intergenerational solidarity in health care, as solidarity will not only be strained by the ageing population, but also might find itself under additional pressure as the gap in health care utilization between elderly and non-elderly grows over time. For hospital care utilization, this process might well be accelerated by advances in medical technology.

The inclusion of medical costs in life years gained in economic evaluations of health care technologies has long been controversial. Arguments in favour of the inclusion of such costs are gaining support, which shifts the question from whether to how to include these costs. This paper elaborates on the issue how to include cost in life years gained in cost effectiveness analysis given the current practice of economic evaluations in which costs of related diseases are included. We combine insights from the theoretical literature on the inclusion of unrelated medical costs in life years gained with insights from the so-called 'red herring' literature. It is argued that for most interventions it would be incorrect to simply add all medical costs in life years gained to an ICER, even when these are corrected for postponement of the expensive last year of life. This is the case since some of the postponement mechanism is already captured in the unadjusted ICER by modelling the costs of related diseases. Using the example of smoking cessation, we illustrate the differences and similarities between different approaches. The paper concludes with a discussion about the proper way to account for medical costs in life years gained in economic evaluations. Copyright (C) 2010 John Wiley & Sons, Ltd.

A shortcoming of many economic evaluations is that they do not include all medical costs in life-years gained (also termed indirect medical costs). One of the reasons for this is the practical difficulties in the estimation of these costs. While some methods have been proposed to estimate indirect medical costs in a standardized manner, these methods fail to take into account that not all costs in life-years gained can be estimated in such a way. Costs in life-years gained caused by diseases related to the intervention are difficult to estimate in a standardized manner and should always be explicitly modelled. However, costs of all other (unrelated) diseases in life-years gained can be estimated in such a way. We propose a conceptual model of how to estimate costs of unrelated diseases in life-years gained in a standardized manner. Furthermore, we describe how we estimated the parameters of this conceptual model using various data sources and studies conducted in the Netherlands. Results of the estimates are embedded in a software package called 'Practical Application to Include future Disease costs' (PAID 1.0). PAID 1.0 is available as a Microsoft® Excel tool (available as Supplemental Digital Content via a link in this article) and enables researchers to 'switch off' those disease categories that were already included in their own analysis and to estimate future healthcare costs of all other diseases for incorporation in their economic evaluations. We assumed that total healthcare expenditure can be explained by age, sex and time to death, while the relationship between costs and these three variables differs per disease. To estimate values for age- and sex-specific per capita health expenditure per disease and healthcare provider stratified by time to death we used Dutch cost-of-illness (COI) data for the year 2005 as a backbone. The COI data consisted of age- and sex-specific per capita health expenditure uniquely attributed to 107 disease categories and eight healthcare provider categories. Since the Dutch COI figures do not distinguish between costs of those who die at a certain age (decedents) and those who survive that age (survivors), we decomposed average per capita expenditure into parts that are attributable to decedents and survivors, respectively, using other data sources.

BackgroundChronic infection with hepatitis B or C virus (HBV/HCV) can progress to cirrhosis, liver cancer, and even death. In a low endemic country as the Netherlands, migrants are a key risk group and could benefit from early diagnosis and antiviral treatment. We assessed the cost-effectiveness of screening foreign-born migrants for chronic HBV and/or HCV using a societal perspective.MethodsThe cost-effectiveness was evaluated using a Markov model. Estimates on prevalence, screening programme costs, participation and treatment uptake, transition probabilities, healthcare costs, productivity losses and utilities were derived from the literature. The cost per Quality Adjusted Life Year (QALY) gained was estimated and sensitivity analyses were performed.ResultsFor most migrant groups with an expected high number of chronically infected cases in the Netherlands combined screening is cost-effective, with incremental cost-effectiveness ratios (ICERs) ranging from (sic)4,962/QALY gained for migrants originating from the Former Soviet Union and Vietnam to (sic)9,375/QALY gained for Polish migrants. HBV and HCV screening proved to be cost-effective for migrants from countries with chronic HBV or HCV prevalence of >= 0.41% and >= 0.22%, with ICERs below the Dutch cost-effectiveness reference value of (sic)20,000/QALY gained. Sensitivity analysis showed that treatment costs influenced the ICER for both infections.ConclusionsFor most migrant populations in a low-endemic country offering combined HBV and HCV screening is cost-effective. Implementation of targeted HBV and HCV screening programmes to increase early diagnosis and treatment is important to reduce the burden of chronic hepatitis B and C among migrants.

Aim The cost-effectiveness of passive immunisation against respiratory syncytial virus (RSV) in the Netherlands was studied by assessing incremental costs to prevent one hospitalisation in high-risk children using a novel individualised monthly approach. Methods Cost-effectiveness analysis was performed by combining estimates of individual hospitalisation costs and monthly hospitalisation risks, with immunisation costs, parental costs and efficacy of passive immunisation for a reference case with the highest hospitalisation risks and costs of hospitalisation during the RSV season (male, gestational age ≤28 weeks, birth weight ≤2500 g, having bronchopulmonary dysplasia (BPD), aged 0 months at the beginning of the season (October)). Various sensitivity analyses and a cost-neutrality analysis were performed. Results Cost-effectiveness of passive immunisation varied widely by child characteristics and seasonal month. For the reference case it was most cost effective in December at €13 190 per hospitalisation averted. Cost-effectiveness was most sensitive to changes in hospitalisation risk. For the reference case, cost neutrality was reached in December, if acquisition costs of passive immunisation decreased from €930 to €375, monthly hospitalisation risk increased from 7.6% to 17%, or hospitalisation costs increased from €10 250 to €23 250 per hospitalisation. Even if passive immunisation prevented all hospitalisations, costs per hospitalisation averted in December would still exceed €2645. Conclusions Although cost-effectiveness of passive immunisation varied strongly by child characteristics and seasonal month, incremental costs per hospitalisation averted were always high. A restrictive immunisation policy only immunising children with BPD in high-risk months is therefore recommended. The costs of passive immunisation would have to be considerably reduced to achieve cost-effectiveness.

Objectives To assess international comparability of general cost of illness (COI) studies and to examine the extent to which COI estimates differ and why. Methods Five general COI studies were examined. COI estimates were classified by health provider using the system of health accounts (SHA). Provider groups fully included in all studies and matching SHA estimates were selected to create a common data set. In order to explain cost differences descriptive analyses were carried out on a number of determinants. Results In general similar COI patterns emerged for these countries, despite their health care system differences. In addition to these similarities, certain significant disease-specific differences were found. Comparisons of nursing and residential care expenditure by disease showed major variation. Epidemiological explanations of differences were hardly found, whereas demographic differences were influential. Significant treatment variation appeared from hospital data. Conclusions A systematic analysis of COI data from different countries may assist in comparing health expenditure internationally. All cost data dimensions shed greater light on the effects of health care system differences within various aspects of health care. Still, the study's objectives can only be reached by a further improvement of the SHA, by international use of the SHA in COI studies and by a standardized methodology.

Achtergrond: De invloed van leefstijl op zorguitgaven speelt een belangrijke rol in het debat rondom preventie. Doel van het onderzoek was te onderzoeken welk deel van de zorguitgaven in 2003 kan worden toegewezen aan roken en overgewicht, wat de invloed is van roken en overgewicht op toekomstige zorguitgaven en wat de invloed is van trends in roken en overgewicht op ontwikkelingen in zorguitgaven, in vergelijking met de invloed van demografische ontwikkelingen. Methode: Met behulp van het RIVM Chronische Ziekten Model (CZM) en data van de Kosten van Ziekten 2003 studie is geschat welk deel van de zorgkosten in 2003 toewijsbaar was aan roken en overgewicht. Vervolgens is geschat hoe de zorguitgaven zich zouden ontwikkelen als roken en overgewicht hypothetisch worden uitgebannen. Ten slotte is de invloed van trends in roken en overgewicht op zorguitgaven afgezet tegen de invloed van demografische ontwikkelingen op zorguitgaven. Resultaten: In 2003 was 3,7% van de zorguitgaven toewijsbaar aan roken en 2,0% aan overgewicht. Echter, uitbanning van roken en overgewicht zou leiden tot stijging van de zorguitgaven op lange termijn vanwege een stijging in de levensverwachting. Demografische ontwikkelingen verhogen de jaarlijkse groei van de zorguitgaven met ongeveer 1%. Trends in roken en overgewicht verhogen deze jaarlijkse groei van de zorguitgaven met maximaal 0,06%. Conclusie: Gezond gedrag is een belangrijke determinant van de volksgezondheid, voor de zorguitgaven is de betekenis echter gering.

Background Obesity is a major cause of morbidity and mortality and is associated with high medical expenditures. It has been suggested that obesity prevention could result in cost savings. The objective of this study was to estimate the annual and lifetime medical costs attributable to obesity, to compare those to similar costs attributable to smoking, and to discuss the implications for prevention. Methods and Findings With a simulation model, lifetime health-care costs were estimated for a cohort of obese people aged 20 y at baseline. To assess the impact of obesity, comparisons were made with similar cohorts of smokers and “healthy-living” persons (defined as nonsmokers with a body mass index between 18.5 and 25). Except for relative risk values, all input parameters of the simulation model were based on data from The Netherlands. In sensitivity analyses the effects of epidemiologic parameters and cost definitions were assessed. Until age 56 y, annual health expenditure was highest for obese people. At older ages, smokers incurred higher costs. Because of differences in life expectancy, however, lifetime health expenditure was highest among healthy-living people and lowest for smokers. Obese individuals held an intermediate position. Alternative values of epidemiologic parameters and cost definitions did not alter these conclusions. Conclusions Although effective obesity prevention leads to a decrease in costs of obesity-related diseases, this decrease is offset by cost increases due to diseases unrelated to obesity in life-years gained. Obesity prevention may be an important and cost-effective way of improving public health, but it is not a cure for increasing health expenditures., Using a simulation model, Pieter van Baal and colleagues conclude that obesity prevention leads to a decrease in costs of obesity-related diseases, but this is offset by cost increases due to diseases unrelated to obesity in life-years gained., Editors' Summary Background. Since the mid 1970s, the proportion of people who are obese (people who have an unhealthy amount of body fat) has increased sharply in many countries. One-third of all US adults, for example, are now classified as obese, and recent forecasts suggest that by 2025 half of US adults will be obese. A person is overweight if their body mass index (BMI, calculated by dividing their weight in kilograms by their height in meters squared) is between 25 and 30, and obese if BMI is greater than 30. Compared to people with a healthy weight (a BMI between 18.5 and 25), overweight and obese individuals have an increased risk of developing many diseases, such as diabetes, coronary heart disease and stroke, and tend to die younger. People become unhealthily fat by consuming food and drink that contains more energy than they need for their daily activities. In these circumstances, the body converts the excess energy into fat for use at a later date. Obesity can be prevented, therefore, by having a healthy diet and exercising regularly. Why Was This Study Done? Because obesity causes so much illness and premature death, many governments have public-health policies that aim to prevent obesity. Clearly, the improvement in health associated with the prevention of obesity is a worthwhile goal in itself but the prevention of obesity might also reduce national spending on medical care. It would do this, the argument goes, by reducing the amount of money spent on treating the diseases for which obesity is a risk factor. However, some experts have suggested that these short-term savings might be offset by spending on treating the diseases that would occur during the extra lifespan experienced by non-obese individuals. In this study, therefore, the researchers have used a computer model to calculate yearly and lifetime medical costs associated with obesity in The Netherlands. What Did the Researchers Do and Find? The researchers used their model to estimate the number of surviving individuals and the occurrence of various diseases for three hypothetical groups of men and women, examining data from the age of 20 until the time when the model predicted that everyone had died. The “obese” group consisted of never-smoking people with a BMI of more than 30; the “healthy-living” group consisted of never-smoking people with a healthy weight; the “smoking” group consisted of lifetime smokers with a healthy weight. Data from the Netherlands on the costs of illness were fed into the model to calculate the yearly and lifetime health-care costs of all three groups. The model predicted that until the age of 56, yearly health costs were highest for obese people and lowest for healthy-living people. At older ages, the highest yearly costs were incurred by the smoking group. However, because of differences in life expectancy (life expectancy at age 20 was 5 years less for the obese group, and 8 years less for the smoking group, compared to the healthy-living group), total lifetime health spending was greatest for the healthy-living people, lowest for the smokers, and intermediate for the obese people. What Do These Findings Mean? As with all mathematical models such as this, the accuracy of these findings depend on how well the model reflects real life and the data fed into it. In this case, the model does not take into account varying degrees of obesity, which are likely to affect lifetime health-care costs, nor indirect costs of obesity such as reduced productivity. Nevertheless, these findings suggest that although effective obesity prevention reduces the costs of obesity-related diseases, this reduction is offset by the increased costs of diseases unrelated to obesity that occur during the extra years of life gained by slimming down. Additional Information. Please access these Web sites via the online version of this summary at http://dx.doi.org/doi:10.1371/journal.pmed.0050029. The MedlinePlus encyclopedia has a page on obesity (in English and Spanish) The US Centers for Disease Control and Prevention provides information on all aspects of obesity (in English and Spanish) The UK National Health Service's health Web site (NHS Direct) provides information about obesity The International Obesity Taskforce provides information about preventing obesity The UK Foods Standards Agency, the United States Department of Agriculture, and Shaping America's Health all provide useful advice about healthy eating The Netherlands National Institute for Public Health and the Environment (RIVM) Web site provides more information on the cost of illness and illness prevention in the Netherlands (in English and Dutch)

Stelt u zich eens voor: Een prachtig dorpje in een verder groene vallei. Het is ochtend. Er hangt nog een laatste restje nevel over de groene velden rondom het dorpje, dat nu snel zal verdwijnen dankzij de opkomende zon. Het enige geluid dat u hoort terwijl u het dorpje nadert over het zandpaadje waarlangs allerhande bloemen de nieuwe dag begroeten met hun kleurenpracht, is het geluid van het ruisen van de zachte wind vermengd met het gezang van de vele vogels die deze vallei herbergt. Als u het dorpje binnenloopt, en over de soms steile straatjes omhoog wandelt in de richting van de toren van het eeuwenoude kerkje, dat op het met bomen omgeven pleintje in het midden van het dorpje staat, komt u plotseling de geur van vers gebakken brood tegemoet.

Dit is de tweede in een serie van tien bijdragen waarin verschillende gezondheidseconomische concepten en aspecten worden belicht. Deze bijdrage stelt een aantal aspecten van de zorgverzekering centraal (noot a).

Health expenditure depends heavily on age. Common wisdom is that the age pattern is dominated by costs in the last year of life. Knowledge about these costs is important for the debate on the future development of health expenditure. According to the 'red herring' argument traditional projection methods overestimate the influence of ageing because improvements in life expectancy will postpone rather than raise health expenditure. This paper has four objectives: (1) to estimate health care costs in the last year of life in the Netherlands; (2) to describe age patterns and differences between causes of death for men and women; (3) to compare cost profiles of decedents and survivors; and (4) to use these figures in projections of future health expenditure. We used health insurance data of 2.1 million persons (13% of the Dutch population), linked at the individual level with data on the use of home care and nursing homes and causes of death in 1999. On average, health care costs amounted to 1100 Euro per person. Costs per decedent were 13.5 times higher and approximated 14,906 Euro in the last year of life. Most costs related to hospital care (54%) and nursing home care (19%). Among the major causes of death, costs were highest for cancer (19,000 Euro) and lowest for myocardial infarctions (8068 Euro). Between the other causes of death, however, cost differences were rather limited. On average costs for the younger decedents were higher than for people who died at higher ages. Ten per cent of total health expenditure was associated with the health care use of people in their last year of life. Increasing longevity will result in higher costs because people live longer. The decline of costs in the last year of life with increasing age will have a moderate lowering effect. Our projection demonstrated a 10% decline in the growth rate of future health expenditure compared to conventional projection methods.

Reliable estimates of hospitalization costs for severe respiratory syncytial virus (RSV) infection are necessary to perform economic analyses of preventive strategies of severe RSV disease. We aimed to develop a model that predicts anticipated mean RSV hospitalization costs of groups of young children at risk for hospitalization, but not yet hospitalized, based on readily available child characteristics.We determined real direct medical costs of RSV hospitalization from a societal perspective, using a bottom-up strategy, in 3458 infants and young children hospitalized for severe RSV disease during the RSV seasons 1996-1997 to 1999-2000 in the Southwest of the Netherlands. We used a linear regression model to predict anticipated mean RSV hospitalization costs of groups of children at risk, based on 4 child characteristics [age, gestational age, birth weight and bronchopulmonary dysplasia (BPD)], expressed in EC Euros as of the year 2000.The mean RSV hospitalization costs of all patients were 3110 Euros. RSV hospitalization costs were higher for patients with lower gestational age (5555 Euros; gestational age,/=28 weeks), lower birth weight (3895 Euros; birth weight/=2500 g), BPD (5785 Euros; with BPD) and young age (4730 Euros; first month of life). The linear regression model had an adjusted R of 0.08. This indicates a low explanatory ability for hospitalization costs of individual children. However, the model could accurately estimate the anticipated mean hospitalization costs of groups of children with the same characteristics.RSV hospitalization costs were substantial, especially of specific high risk groups. Anticipated mean hospitalization costs of groups of children at risk for RSV hospitalization, but not yet hospitalized, could well be estimated with 4 child characteristics (age, gestational age, birth weight and BPD). These estimated costs can be used for economic analyses of preventive strategies for severe RSV disease.

Contains fulltext : 142607.pdf (Publisher’s version ) (Closed access) - Background: The study describes variations in use of surgical procedures by community income in the Netherlands. From the literature it is known that surgical rates have a socioeconomic gradient. Both positive and negative associations of socioeconomic factors of patients (for example, income, education) with surgical rates have been reported. The question raised here is: how do (possible) socioeconomic variations in surgery in the Netherlands compare with variations observed elsewhere? - Data and Methods: The data comprised Dutch hospital discharges and population estimates for 1999. Socioeconomic status was indicated by a patient’s income and based on the average family income of the postcode area of residence. Poisson regression was used to compute relative incidence (odds ratios) for 10 common surgical procedures. The model included age, gender, degree of urbanisation, and province of residence. - Results: The association between surgical rates and community level income is rather weak. For half of the surgical rates the authors observed higher utilisation rates in communities with low income levels, but the differences are small. The range of odds ratios in the lowest income quintile group (compared with the group with the highest income) observed is: 0.87 to 1.18. Men from a low income community received more appendicectomies (1.18), cholecystectomies (1.12), knee replacements (1.06), and prostatectomies (1.14) and less tonsillectomies (0.90). Women from a low income community received more appendicectomies (1.12), caesarean sections (1.18), hip and knee replacements (1.05,1.17), and hysterectomies (1.14). Whereas they received less coronary artery bypass grafts (0.92), cholecystectomies (0.87), and tonsillectomies (0.92). - Conclusions: Compared with findings reported in the international literature, this study indicates that variations in use of surgical procedures by community income in the Netherlands are comparatively small. Because of lack of data the authors could not study the influence of variations in need for surgical care by community income, but as the incidence of conditions requiring surgical interventions generally is higher in lower income groups, it is suspected some degree of underutilisation exists in these groups.

Background: The escalating costs of health care raise questions about demographic, epidemiological and technological determinants and future projections. The objectives of this work are to describe the age pattern of health care costs, to analyse the age‐specific cost changes and to project future health care costs in an ageing population. Methods: Comprehensive cost‐of‐illness data for the whole Dutch population in 1988 and 1994 are compared by age and type of care. National data on all hospital admissions, nursing days and clinical interventions for the period 1988–1994 is used to describe trends in hospital care. Population forecasts are used to project the age distribution of future health care costs. Results: The distribution of health care costs per capita depends strongly on age. The growth rate of per capita costs increases by age for acute care but decreases by age for long‐term care. Both combined cause an average annual growth rate of 4.6%, nearly constant with age. Conclusions: Ageing will result in increasing health care demands and costs. Secular trends in acute and long‐term care indicate major shifts in costs from younger to older people and from long‐term to acute care. Received 9 June 2000. Accepted 16 February 2001.

De recessie is een feit. Knarsend en piepend is de economie tot stilstand gekomen. [1] “Zo’n crisis maak je maar een keer mee. En wil je ook maar een keer meemaken,” aldus een dramatische Coen Teulings, directeur van het Centraal Plan Bureau eind vorig jaar bij de presentatie van de decemberraming. Het CPB voorziet zwaar weer en verwacht dat de Nederlandse economie in 2009 fors zal krimpen. [2] Volgens Ruding en Wellink, economen van naam en faam, zijn de voorspellingen van het CPB echter nog te rooskleurig. Zij verwachten een veel sterkere teruggang die grote repercussies zal hebben. [3] Anderzijds zijn er ook opinieleiders die veel minder somber tegen de economische malaise aankijken. Zoals Erica Verdegaal. “Wolvengehuil”, schreef ze boven haar column in het NRC Handelsblad. “Een crisis is geen Titanic, die hele werelddelen naar de ondergang vaart. Het is meer een griepepidemie. Zodra het heerst, voelt half Nederland zich plotseling niet helemaal lekker. Hooguit een kwart blijft, al dan niet noodzakelijk, een poosje thuis. Een beperkte club pechvogels tot slot meestal met te hoge of te dure (hypotheek)schuldenzal helaas aan het crisisvirus bezwijken.” [4]

Wie een willekeurig dagblad openslaat ziet daar een stroom van onderwerpen voorbij trekken die vaak onder het kopje ‘economie’ worden gebracht en meestal gaan over geld: “Goede sier maken met de huizen van anderen.” “Rabobank wint aandeel hypotheekmarkt terug.” “Loonstijging blijft achter bij eis vakbond.” “USG profiteert van economische groei.”1 Zelfs het Journaal heeft een vaste rubriek economisch nieuws waarin meestal vooral de actuele standen van de beurzen worden genoemd.

Tot 11 december 2006 behoorde ik tot de kleine groep gelukkigen die niets van voetbal weten en ik dacht dat nog lang vol te houden. Niet dus. Een uitnodiging van de Nationale DenkTank bracht mij in het ING House te Amsterdam. Dit opmerkelijke gebouw aan de A10 is onmiskenbaar geschoeid op de leest van koning voetbal (zie www.inghouse.com). Het was echter niet het gebouw dat mij inwijdde in de wondere wereld van Johan Cruijff. De DenkTank zelf zette mij aan het denken. Als “Recept voor Morgen” presenteerde zij een menu met tien ingredienten voor “Een frisse blik op betere zorg voor chronisch zieken”.1 Het eerste advies zal de supporters van preventie voor altijd aan de groene mat binden: “Introduceer het Health Transfer Systeem”. Op pagina 31 van het rapport lezen we: “Het Health Transfer Systeem creeert gezonde financiele prikkels. Het stimuleert investeringen van zorgverzekeraars op het gebied van preventie, die complementair zijn aan het overheidsbeleid. Het principe is geinspireerd op het transfersysteem in de voetbalwereld. De voetbaltransfersom is het bedrag dat de nieuwe club betaalt aan de oude club, wanneer een niet-transfervrije voetballer van club wisselt.”

Topdrukte werd er verwacht, een jaar of drie geleden, op de Oudlaan in Utrecht waar het hoofdkantoor van Actiz is gevestigd. Lange files met durfkapitalisten, banken, private equity financiers en alle anderen die wat meer rendement uit hun euro’s willen halen dan de schamele percentages die de banken bieden.

Objectives : To determine the demands on healthcare resources caused by different types of illnesses and variation with age and sex. Design: Information on healthcare use was obtained from all 22 healthcare sectors in the Netherlands. Most important sectors (hospitals, nursing homes, inpatient psychiatric care, institutions for mentally disabled people) have national registries. Total expenditures for each sector were subdivided into 21 age groups, sex, and 34 diagnostic groups. Setting: Netherlands, 1994. Main outcome measures: Proportion of healthcare budget spent on each category of disease and cost of health care per person at various ages. Results: After the first year of life, costs per person for children were lowest. Costs rose slowly throughout adult life and increased exponentially from age 50 onwards till the oldest age group (95). The top five areas of healthcare costs were mental retardation, musculoskeletal disease (predominantly joint disease and dorsopathy), dementia, a heterogeneous group of other mental disorders, and ill defined conditions. Stroke, all cancers combined, and coronary heart disease ranked 7, 8, and 10, respectively. Conclusions: The main determinants of healthcare use in the Netherlands are old age and disabling conditions, particularly mental disability. A large share of the healthcare budget is spent on long term nursing care, and this cost will inevitably increase further in an ageing population. Non-specific cost containment measures may endanger the quality of care for old and mentally disabled people. Key messages Little is known about demands for health care outside acute sectors In the Netherlands health costs are strongly age dependent, increasing exponentially after age 50 The five highest healthcare costs are for mental retardation, musculoskeletal disease, dementia, other mental disorders, and ill defined conditions Coronary heart disease, all cancers, and stroke accounted for only 9% of costs The main healthcare costs are for care not cure and costs are likely to increase rapidly in an ageing society