Publications by authors named "Pieter H M Van Baal"

Adopting a societal perspective in cost-effectiveness analysis (CEA) requires including all societal costs and benefits even if they fall outside of the realm of health and healthcare. While some benefits are not explicitly included, they might be implicitly included when people value quality-adjusted life-years (QALYs) in monetary terms. An example is utility of consumption (UoC) which has played a crucial role in discussions regarding the welfare economic underpinnings of CEA.

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Introduction: Studies reporting on the cost-effectiveness of cancer screening usually account for quality of life losses and healthcare costs owing to cancer but do not account for future costs and quality of life losses related to competing risks. This study aims to demonstrate the impact of medical costs and quality of life losses of other diseases in the life years gained on the cost-effectiveness of U.S.

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Background: Although a myriad of novel treatments entered the treatment paradigm for advanced melanoma, there is lack of head-to-head evidence. We conducted a network meta-analysis (NMA) to estimate each treatment's relative effectiveness and safety.

Methods: A systematic literature review (SLR) was conducted in Embase, MEDLINE and Cochrane to identify all phase III randomised controlled trials (RCTs) with a time frame from January 1, 2010 to March 11, 2019.

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There has been considerable debate on the extent to which future costs should be included in cost-effectiveness analyses of health technologies. In this article, we summarize the theoretical debates and empirical research in this area and highlight the conclusions that can be drawn for current practice. For future related and future unrelated medical costs, the literature suggests that inclusion is required to obtain optimal outcomes from available resources.

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Mortality rates in Markov models, as used in health economic studies, are often estimated from summary statistics that allow limited adjustment for confounders. If interventions are targeted at multiple diseases and/or risk factors, these mortality rates need to be combined in a single model. This requires them to be mutually adjusted to avoid 'double counting' of mortality.

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Background: Quality-adjusted life expectancy (QALE) has been proposed as a summary measure of population health because it encompasses multiple health domains as well as length of life. However, trends in QALE by education or other socio-economic measure have not yet been reported. This study investigates changes in QALE stratified by educational level for the Dutch population in the period 2001-2011.

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Background: Preventing dementia has been proposed to increase population health as well as reduce the demand for health and social care. Our aim was to evaluate whether preventing dementia by promoting physical activity (PA) a) improves population health or b) reduces expenditure for both health and social care if one takes into account the additional demand in health and social care caused by increased life expectancy.

Methods: A simulation model was developed that models the relation between PA, dementia, mortality, and the use of health care and social care in England.

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This article explores the implications of the relation between quality of life (QoL) and time to death (TTD) for economic evaluations of preventive interventions. By using health survey data on QoL for the general Dutch population linked to the mortality registry, we quantify the magnitude of this relationship. For addressing specific features of the nonstandard QoL distribution such as boundness, skewness, and heteroscedasticity, we modeled QoL using a generalized additive model for location, scale, and shape (GAMLSS) with a β inflated outcome distribution.

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Although many countries' populations have experienced increasing life expectancy in recent decades, quality of life (QoL) trends in the general population have yet to be investigated. This paper investigates whether QoL changed for the general Dutch population over the period 2001-2008. A beta regression model was employed to address specific features of the QoL distribution (i.

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Background: Disease prevention has been claimed to reduce health care costs. However, preventing lethal diseases increases life expectancy and, thereby, indirectly increases the demand for health care. Previous studies have argued that on balance preventing diseases that reduce longevity increases health care costs while preventing non-fatal diseases could lead to health care savings.

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Objectives: Productivity losses usually have a considerable impact on cost-effectiveness estimates while their estimated values are often relatively uncertain. Therefore, parameters related to these indirect costs play a role in setting priorities for future research from a societal perspective. Until now, however, value of information analyses have usually applied a health care perspective for economic evaluations.

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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.

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Life expectancy continues to grow in most Western countries; however, a major remaining question is whether longer life expectancy will be associated with more or fewer life years spent with poor health. Therefore, complementing forecasts of life expectancy with forecasts of health expectancies is useful. To forecast health expectancy, an extension of the stochastic extrapolative models developed for forecasting total life expectancy could be applied, but instead of projecting total mortality and using regular life tables, one could project transition probabilities between health states simultaneously and use multistate life table methods.

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In Health Impact Assessment (HIA), or priority-setting for health policy, effects of risk factors (exposures) on health need to be modeled, such as with a Markov model, in which exposure influences mortality and disease incidence rates. Because many risk factors are related to a variety of chronic diseases, these Markov models potentially contain a large number of states (risk factor and disease combinations), providing a challenge both technically (keeping down execution time and memory use) and practically (estimating the model parameters and retaining transparency). To meet this challenge, we propose an approach that combines micro-simulation of the exposure information with macro-simulation of the diseases and survival.

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In this paper, we report a case study on a technical generalization of the Lee-Carter model, originally developed to project mortality, to forecast body mass index (BMI, kg/m2). We present the method on an annually repeated cross-sectional data set, the Dutch Health Survey, covering years between 1981 and 2008. We applied generalized additive models for location, scale and shape semi-parametric regression models to estimate the probability distribution of BMI for each combination of age, gender and year assuming that BMI follows a Box-Cox power exponential distribution.

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

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

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Background: Depression causes a large burden of disease worldwide. Effective prevention has the potential to reduce that burden considerably. This study aimed to investigate the cost-effectiveness of minimal contact psychotherapy, based on Lewinsohn's 'Coping with depression' course, targeted at opportunistically screened individuals with sub-threshold depression.

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Aims: Mortality attributed to a disease is an important public health measure of the 'burden' of that disease. A discrepancy has been noted between the high mortality rates associated with heart failure (HF) and the share of deaths ascribed to HF in official mortality statistics. It was our main aim to estimate excess mortality associated with HF and use the estimates to better understand the burden of HF.

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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.

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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.

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The impact of weight change on diabetes incidence remains unclear. To clarify the role of weight change as a risk factor for diabetes, the authors assessed the association between weight change and diabetes incidence conditional upon either initial or attained body mass index (BMI). They used 7,837 observations available from repeated measurements of 4,259 participants (men and women aged 20-59 years) in the Dutch population-based Doetinchem Cohort Study (1987-2007) to analyze the association between 5-year weight change and diabetes incidence (n = 124) in the subsequent 5 years.

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It has been demonstrated repeatedly that time to death is a much better predictor of health care expenditures than age. This is known as the 'red herring' hypothesis. In this article, we investigate whether this is also the case regarding disease-specific hospital expenditures.

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Background: Obesity is a major contributor to the overall burden of disease (also reducing life expectancy) and associated with high medical costs due to obesity-related diseases. However, obesity prevention, while reducing obesity-related morbidity and mortality, may not result in overall healthcare cost savings because of additional costs in life-years gained. Sector-specific financial consequences of preventing obesity are less well documented, for pharmaceutical spending as well as for other healthcare segments.

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Objective: To estimate the number of people with diagnosed diabetes mellitus in the Netherlands in 2007 using a new method; to describe trends in the past; to predict the situation in 2025.

Design: Model calculations.

Methods: Based on five general practice records (Nijmegen Continuous Morbidity Registration [CMR], Netherlands Information Network of General Practice [LINH], Limburg Family Practice Registration Network [RNH-Limburg], Registration Network University Family Practices, Leiden and its environs [RNUH-LEO], and the transition project) the prevalence and incidence of diagnosed diabetes in the Netherlands in 2007 was estimated.

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