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Background: Traumatic brain injury (TBI) is the main cause of mortality and severe morbidity in cyclists admitted to Dutch emergency departments (EDs). Although the use of bicycle helmets is an effective way of preventing TBI, this is uncommon in the Netherlands. An option to increase its use is through a legal enforcement. However, little is known about the cost-effectiveness of such mandatory use of helmets in the Dutch context. The current study aimed to assess the cost-effectiveness of a law that enforces helmet use to reduce TBI and TBI-related mortality., Methods: The cost-effectiveness was estimated through decision tree modelling. In this study, wearing bicycle helmets enforced by law was compared with the current situation of infrequent voluntary helmet use. The total Dutch cycling population, consisting of 13.5 million people, was included in the model. Model data and parameters were obtained from Statistics Netherlands, the National Road Traffic Database, Dutch Injury Surveillance System, and literature. Effects included were numbers of TBI, death, and disability-adjusted life years (DALY). Costs included were healthcare costs, costs of productivity losses, and helmet costs. Sensitivity analysis was performed to assess which parameter had the largest influence on the incremental cost-effectiveness ratio (ICER)., Results: The intervention would lead to an estimated reduction of 2942 cases of TBI and 46 deaths. Overall, the incremental costs per 1) death averted, 2) per TBI averted, and 3) per DALY averted were estimated at 1) € 2,002,766, 2) € 31,028 and 3) € 28,465, respectively. Most favorable were the incremental costs per DALY in the 65+ age group: € 17,775., Conclusions: The overall costs per DALY averted surpassed the Dutch willingness to pay threshold value of € 20,000 for cost-effectiveness of preventive interventions. However, the cost per DALY averted for the elderly was below this threshold, indicating that in this age group largest effects can be reached. If the price of a helmet would reduce by 20%, which is non-hypothetical in a situation of large-scale purchases and use of these helmets, the introduction of this regulation would result in an intervention that is almost cost-effective in all age groups.

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 €12.6 million, ranging from €6.7 to €22.5 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.

Health care costs have increased due to population ageing. It is often said that the majority of health care spending occurs in the last year of life and that, as a result, the total costs of population ageing are considerably lower than is usually predicted. With the Netherlands facing a rapidly ageing population, such statements are well-received by policy makers. Unfortunately they reflect only part of the truth and are therefore misleading. Nevertheless, health care costs in the last years of life are still interesting, but for a different reason than is widely believed. Taking a lifetime perspective, these costs shed new light on solidarity in health care.

Increasing healthcare costs force policy makers to make difficult choices in the insurance package. In order to make rational choices, there must be an understanding of the healthcare costs as well as the value of the health that the care provides. Health economists have in recent years carried out extensive research into the value that people attribute to health. Health is of great social value, and is difficult to express in concrete monetary terms. One extra life-year in good health ('quality-adjusted life year', QALY) seems to be valued on average at no less than 50,000 euros by people. Methodology needs to be developed in this area so that study results are more uniform and can be better compared. Physicians and policy makers will thus gain more insight into the value of health.

In this paper, we investigate the relationship between baseline health and costs of hospital use over a period of eight years. We combine cross-sectional survey data with information from the Dutch national hospital register. Four different indicators of health (self-perceived health, long-term impairments, ADL limitations and comorbidity) are considered. We find that for ages 50 to 70, differences in hospital costs between good health and bad health are substantial and persist during the whole time period. However, for higher ages expected hospital costs for individuals in bad health decline rapidly and become lower than those for people in good health after about six to seven years. The higher mortality rate among people in bad health is the primary cause here. Our results are confirmed for all four health indicators. We conclude that relying on better health to contain healthcare expenditures is too optimistic, and the interaction between health and mortality should be taken into account when projecting healthcare costs. Healthy ageing is important, but more for health gains than for cost savings., (Copyright © 2010 John Wiley & Sons, Ltd.)

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 © 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.

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.

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.

All Western health systems are in search of efficiency. Cost of illness (COI) studies can contribute to the efficiency debate by elucidating the relation between health expenditure and health status and population demography. Since the purpose of COI data being summarized in the OECD Health Data publications is to facilitate cross-national comparisons, it is important to assess the comparability. We compared COI data from six countries at macrolevel of total health expenditure and disaggregated the data from four countries to sectors such as hospitals, drugs, health professionals, and residential care. Although the distribution of health expenditure over major diseases showed similar patterns in all countries, overall comparability was bad. We conclude that the current scope of COI studies is bound to national levels because health care systems dominate the magnitude and distribution of health expenditure. Cross-national comparisons may be possible if data and methods are standardized, and COI estimates are made for a common comparable package.

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.

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 (> or = 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.

Objective: To estimate the costs of health care in 1994, the development of the costs assigned to specific diseases, and the future costs., Design: Descriptive., Setting: Erasmus University, Department of Public Health, Rotterdam, the Netherlands., Method: For each health care sector, costs were allocated to 62 diagnostic groups, age and sex making maximal use of national registries and other sources with data on health care use in the Netherlands., Results: More than 80% of the 60 billion Dutch guilders that were spent on health care in 1994 could be assigned to specific diseases. Most costs were made for non-fatal diseases like mental deficiency, dementia and musculoskeletal disease. Except for cardiovascular disease, the share of major causes of death in the total costs was not significant. Average costs per inhabitant were low during youth and adulthood but increased exponentially with age from age 50 onwards. Between 1988 en 1994, health care costs experienced an annual growth rate of 5.2%, caused by price and wage increases (one half), ageing (a quarter) and other effects on health care costs such as epidemiological and technological change (a quarter)., Conclusion: The main determinants of health care use in the Netherlands were old age and disabling conditions. Due to ageing and other influences, real health care costs in the years to come will increase by an average annual rate of 2.4%.