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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.

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.

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.

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.

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.

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.

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

The Dutch risk equalization scheme has been improved over the years by including health related risk adjusters. The purpose of the Dutch risk equalization scheme is to prevent risk selection and to correct for predictable losses and gains for insurers. The objective of this paper is to explore the financial incentives for risk selection under the Dutch risk equalization scheme.We used a simulation model to estimate lifetime health care costs and risk equalization contributions for three cohorts (a smoking; an obese; and a healthy living cohort). Financial differences for the three cohorts were assessed by subtracting health care costs from risk equalization contributions.Even under an elaborate risk equalization system, the healthy living cohort was still most financially attractive for insurers. Smokers were somewhat less attractive, while the obese cohort was least attractive. Lifetime differences with healthy living individuals (revenues minus costs) were modest: €4840 for obese individuals and €1101 for smokers. Under a simple form of risk equalization these differences were higher, €8542 and €4620 respectively.Improvement of the risk equalization scheme reduced the gap between costs and revenues. Incentives for undesirable risk selection were reduced, but simultaneously incentives for health promotion were weakened. This highlights a new prevention paradox: improving the level playing field for health insurers will inevitably limit their incentives for promoting the health of their clients.Highlights► Improved risk equalization is important to reduce incentives for risk selection by health insurers. ► We describe insurers' financial incentives for risk selection in relation to recent improvements in Dutch risk equalization. ► We estimated lifetime costs and benefits for Dutch health insurers for smoking, obese and healthy living individuals. ► Insurers can expect different health care costs and risk equalization revenues for healthy living, smoking and obese people. ► Healthy living individuals are only slightly more financially attractive for insurers than smoking and obese individuals.Keywords: The Netherlands, Risk equalization, Prevention, Chronic Disease Model

Objective This article presents methods for using administrative data to study multimorbidity in hospitalized individuals and indicates how the findings can be used to gain a deeper understanding of hospital multimorbidity. Study Design and Setting A Dutch nationwide hospital register ( n =4,521,856) was used to calculate age- and sex-standardized observed/expected ratios of disease-pairing prevalences with corresponding confidence intervals. Results The strongest association was found for the combination between alcoholic liver and mental disorders due to alcohol abuse (observed/expected=39.2). Septicemia was found to cluster most frequently with other diseases. The consistency of the ratios over time depended on the number of observed cases. Furthermore, the ratios also depend on the length of the time frame considered. Conclusion Using observed/expected ratios calculated from the administrative data set, we were able to (1) better quantify known morbidity pairings while also revealing hitherto unnoticed associations, (2) find out which pairings cluster most strongly, and (3) gain insight into which diseases cluster frequently with other diseases. Caveats with this method are finding spurious associations on the basis of too few observed cases and the dependency of the ratio magnitude on the length of the time frame observed.

Background Long-term care is often associated with high health care expenditures. In the Netherlands, an ageing population will likely increase the demand for long-term care within the near future. The development of risk profiles will not only be useful for projecting future demand, but also for providing clues that may prevent or delay long-term care utilization. Here, we report our identification of predictors of long-term care utilization in a cohort of hospital patients aged 65+ following their discharge from hospital discharge and who, prior to hospital admission, were living at home. Methods The data were obtained from three national databases in the Netherlands: the national hospital discharge register, the long-term care expenses register and the population register. Multinomial logistic regression was applied to determine which variables were the best predictors of long-term care utilization. The model included demographic characteristics and several medical diagnoses. The outcome variables were discharge to home with no formal care (reference category), discharge to home with home care, admission to a nursing home and admission to a home for the elderly. Results The study cohort consisted of 262,439 hospitalized patients. A higher age, longer stay in the hospital and absence of a spouse were found to be associated with a higher risk of all three types of long-term care. Individuals with a child had a lower risk of requiring residential care. Cerebrovascular diseases [relative risk ratio (RRR) = 11.5] were the strongest disease predictor of nursing home admission, and fractures of the ankle or lower leg (RRR = 6.1) were strong determinants of admission to a home for the elderly. Lung cancer (RRR = 4.9) was the strongest determinant of discharge to the home with home care. Conclusions These results emphasize the impact of age, absence/presence of a spouse and disease on long-term care utilization. In an era of demographic and epidemiological changes, not only will hospital use change, but also the need for long-term care following hospital discharge. The results of this study can be used by policy-makers for planning health care utilization services and anticipating future health care needs.

It is under debate whether healthcare costs related to death and in life years gained (LysG) due to life saving interventions should be included in economic evaluations. We estimated the impact of including these costs on cost-effectiveness of cancer screening. We obtained health insurance, home care, nursing homes, and mortality data for 2.1 million inhabitants in the Netherlands in 1998-1999. Costs related to death were approximated by the healthcare costs in the last year of life (LastYL), by cause and age of death. Costs in LYsG were estimated by calculating the healthcare costs in any life year. We calculated the change in cost-effectiveness ratios (CERs) if unrelated healthcare costs in the LastYL or in LYsG would be included. Costs in the LastYL were on average 33% higher for persons dying from cancer than from any cause. Including costs in LysG increased the CER by 4040 euro in women, and by 4100 euro in men. Of these, 660 euro in women, and 890 euro in men, were costs in the LastYL. Including unrelated healthcare costs in the LastYL or in LYsG will change the comparative cost-effectiveness of healthcare programmes. The CERs of cancer screening programmes will clearly increase, with approximately 4000 euro. However, because of the favourable CER's, including unrelated healthcare costs will in general have limited policy implications.

To assess international comparability of general cost of illness (COI) studies and to examine the extent to which COI estimates differ and why.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.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.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.

It is widely assumed that health care costs can be reduced considerably by providing care in appropriate health care institutions without unnecessary technological overhead. This assumption has been tested in a prospective study. Conventional discharge after hip fracture surgery was compared with an early discharge policy in which patients were discharged to a nursing home with specialised facilities for rehabilitation. We compared costs for both strategies from a societal perspective, using comprehensive and detailed data on type of residence and all kinds of medical consumption during a 4-month follow-up period. As expected, early discharge reduced the hospital stay (with 13 days, p=0.001). More patients were discharged to a nursing home (76% versus 53%). Total medical costs during follow-up were reduced from an average of €15 338 to €14 281, representing relatively small and not significant savings (p=0.3). There are two explanations for this unexpected result. First, costs incurred by hip fracture patients were relatively less while in hospital. Hence, nursing home costs almost equalled hospital costs per admission day. Second, compared with the conventionally discharged group early discharged patients were subjected to more medical procedures during the first post-operative days. We conclude that: (1) early discharge shifted rather than reduced costs; (2) the details of costing have a major influence on the cost-effectiveness of alternative discharge policies. Copyright © 2002 John Wiley & Sons, Ltd.

Healthcare costs are continuously increasing, and impose a strong responsibility on governments for an adequate allocation of resources among healthcare provisions and patients. The aims of the present study were to describe the healthcare costs of intellectual disability (ID) and other mental disorders in the context of the total costs of all other diseases, and to determinate the future need of healthcare resources, especially for ID and mental disorders. The present authors performed a top-down cost-of-illness study comprising all healthcare costs of the Netherlands in 1994. Data on healthcare use were obtained for all 22 healthcare sectors, and used to ascribe costs to disease groups, age and sex. Costs of mental disorders are by far the largest in the Dutch healthcare system. Some 25.8% of total disease-specific costs could be ascribed to mental disorders: psychiatric conditions, 10.6%; ID, 9.0%; and dementia, 6.2%. There are large differences between age and sex groups. The costs of ID and schizophrenia are higher among men, and the costs of dementia and depression are higher among women. The age pattern shows two peaks: the first occurs at 25-35 years of age (ID and psychiatric conditions); and the second at 75-85 years of age (dementia). Time trends between 1988 and 1994 show an average annual growth rate of 5.2% for total healthcare costs: psychiatric conditions, 4.8%; ID, 5.4%; and dementia, 9.4%. Demographic projections suggest a less-than-average cost increase for ID and psychiatric disorders (with annual growth rates of 0.2% and 0.4%, respectively) compared to the costs of dementia and total healthcare (with annual growth rates of 1.6% and 0.9%, respectively). Intellectual disability and mental disorders represent a large part of healthcare use in the Netherlands. The costs will inevitably increase because of the ageing of the population and increasing life expectancy among people with disabilities. Non-specific cost containment measures may endanger the quality of care for vulnerable people at younger and older ages.

ObjectiveFragile X syndrome is the most common cause of mental retardation from a single gene defect, transmitted in an X-linked semidominant fashion. Cloning of the gene responsible for fragile X syndrome has made it possible to identify carriers who are at risk of giving birth to a child with fragile X syndrome. One of the proposed strategies for identifying carriers is cascade testing, in which relatives of a patient with fragile X syndrome (the index case) are tested. Because the effectiveness of this type of testing is unknown, the objective of this study was to develop a simulation model for studying the consequences of cascade testing for fragile X syndrome. MethodsWith this model, 100 000 five-generation pedigrees were simulated to assess the maximum number of carriers that would be detected for three scenarios: (a) only first degree relatives of the index case are tested; (b) relatives up to the third degree are tested; (c) relatives up to the fifth degree are tested. ResultsIn the start-up phase of the testing programme, 18% of couples who will have a fragile X syndrome child are detected. After this phase the (stabilised) cascade testing programme detects 7% of undetected couples who would have a fragile X syndrome child if only first degree relatives were tested, 12% if first to third degree relatives were tested, and 15% if first to fifth degree relatives were tested. To detect 90% of all premutation and full mutation carriers at least eight consecutive generations need to be tested. ConclusionsThe results of our analysis show that cascade testing is not very effective in detecting carriers.

During the 1980s and 1990s life expectancy at birth has risen only slowly in the Netherlands. In 2002, however, the rise in life expectancy suddenly accelerated. We studied the possible causes of this remarkable development. Mortality data by age, gender and cause of death were analyzed using life table methods and age-period-cohort modeling. Trends in determinants of mortality (including health care delivery) were compared with trends in mortality. Two-thirds of the increase in life expectancy at birth since 2002 were due to declines in mortality among those aged 65 and over. Declines in mortality reflected a period rather than a cohort effect, and were seen for a wide range of causes of death. Favorable changes in mortality determinants coinciding with the acceleration of mortality decline were mainly seen within the health care system. Health care expenditure rose rapidly after 2001, and was accompanied by a sharp rise of specialist visits, drug prescriptions, hospital admissions and surgical procedures among the elderly. A decline of deaths following non-treatment decisions suggests a change towards more active treatment of elderly patients. Our findings are consistent with the idea that the sharp upturn of life expectancy in the Netherlands was at least partly due to a sharp increase in health care for the elderly, and has been facilitated by a relaxation of budgetary constraints in the health care system. Electronic supplementary material The online version of this article (doi:10.1007/s10654-011-9633-y) contains supplementary material, which is available to authorized users.

BackgroundThe effect of population aging on future health services use depends on the relationship between longevity gains and health. Whether further gains in life expectancy will be paired by improvements in health is uncertain. We therefore analyze the effect of population ageing on health services use under different health scenarios. We focus on the possibly diverging trends between different dimensions of health and their effect on health services use.MethodsUsing longitudinal data on health and health services use, a latent Markov model has been estimated that includes different dimensions of health. We use this model to perform a simulation study and analyze the health dynamics that drive the effect of population aging. We simulate three health scenarios on the relationship between longevity and health (expansion of morbidity, compression of morbidity, and the dynamic equilibrium scenario). We use the scenarios to predict costs of health services use in the Netherlands between 2010 and 2050.ResultsHospital use is predicted to decline after 2040, whereas long-term care will continue to rise up to 2050. Considerable differences in expenditure growth rates between scenarios with the same life expectancy but different trends in health are found. Compression of morbidity generally leads to the lowest growth. The effect of additional life expectancy gains within the same health scenario is relatively small for hospital care, but considerable for long-term care.ConclusionsBy comparing different health scenarios resulting in the same life expectancy, we show that health improvements do contain costs when they decrease morbidity but not mortality. This suggests that investing in healthy aging can contribute to containing health expenditure growth.