http://repub.eur.nl/res/aut/7876/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/38889/ 2012-11-20T00:00:00Z 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. This approach allows users to simulate exposure in detail while avoiding the need for large simulated populations because of the relative rareness of chronic disease events. Further efficiency is gained by splitting the disease state space into smaller spaces, each of which contains a cluster of diseases that is independent of the other clusters. The challenge of feasible input data requirements is met by including parameter calculation routines, which use marginal population data to estimate the transitions between states. As an illustration, we present the recently developed model DYNAMO-HIA (DYNAMIC MODEL for Health Impact Assessment) that implements this approach. http://repub.eur.nl/res/pub/38680/ 2012-09-24T00:00:00Z Background: Counseling in combination with pedometer use has proven to be effective in increasing physical activity and improving health outcomes. We investigated the cost-effectiveness of this intervention targeted at one million insufficiently active adults who visit their general practitioner in the Netherlands.Methods: We used the RIVM chronic disease model to estimate the long-term effects of increased physical activity on the future health care costs and quality adjusted life years (QALY) gained, from a health care perspective.Results: The intervention resulted in almost 6000 people shifting to more favorable physical-activity levels, and in 5100 life years and 6100 QALYs gained, at an additional total cost of EUR 67.6 million. The incremental cost-effectiveness ratio (ICER) was EUR 13,200 per life year gained and EUR 11,100 per QALY gained. The intervention has a probability of 0.66 to be cost-effective if a QALY gained is valued at the Dutch informal threshold for cost-effectiveness of preventive intervention of EUR 20,000. A sensitivity analysis showed substantial uncertainty of ICER values.Conclusion: Counseling in combination with pedometer use aiming to increase physical activity may be a cost-effective intervention. However, the intervention only yields relatively small health benefits in the Netherlands. http://repub.eur.nl/res/pub/37874/ 2012-03-15T00:00:00Z A problem occurring in chronic disease modeling is the estimation of transition probabilities of moving from one state of a categorical risk factor to another. Transitions could be obtained from a cohort study, but often such data may not be available. However, under the assumption that transitions remain stable over time, age specific cross-sectional prevalence data could be used instead. Problems that then arise are parameter identifiability and the fact that age dependent cross-sectional data are often noisy or are given in age intervals. In this paper we propose a method to estimate so-called net annual transition probabilities from cross-sectional data, including their uncertainties. Net transitions only describe the net inflow or outflow into a certain risk factor state at a certain age. Our approach consists of two steps: first, smooth the data using multinomial P-splines, second, from these data estimate net transition probabilities. This second step can be formulated as a transportation problem, which is solved using the simplex algorithm from linear programming theory. A sensible specification of the cost matrix is crucial to get meaningful results. Uncertainties are assessed by parametric bootstrapping. We illustrate our method using data on body mass index. We conclude that this method provides a flexible way of estimating net transitions and that the use of net transitions has implications for model dynamics, for example when modeling interventions. http://repub.eur.nl/res/pub/31055/ 2011-09-01T00:00:00Z Background: The high prevalence of chronic diseases in Western countries implies that the presence of multiple chronic diseases within one person is common. Especially at older ages, when the likelihood of having a chronic disease increases, the co-occurrence of distinct diseases will be encountered more frequently. The aim of this study was to estimate the age-specific prevalence of multimorbidity in the general population. In particular, we investigate to what extent specific pairs of diseases cluster within people and how this deviates from what is to be expected under the assumption of the independent occurrence of diseases (i.e., sheer coincidence).Methods: We used data from a Dutch health survey to estimate the prevalence of pairs of chronic diseases specified by age. Diseases we focused on were diabetes, myocardial infarction, stroke, and cancer. Multinomial P-splines were fitted to the data to model the relation between age and disease status (single versus two diseases). To assess to what extent co-occurrence cannot be explained by independent occurrence, we estimated observed/expected co-occurrence ratios using predictions of the fitted regression models.Results: Prevalence increased with age for all disease pairs. For all disease pairs, prevalence at most ages was much higher than is to be expected on the basis of coincidence. Observed/expected ratios of disease combinations decreased with age.Conclusion: Common chronic diseases co-occur in one individual more frequently than is due to chance. In monitoring the occurrence of diseases among the population at large, such multimorbidity is insufficiently taken into account. http://repub.eur.nl/res/pub/25581/ 2011-04-01T00:00:00Z AimsMortality 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.Methods and resultsExcess mortality was defined as the difference in mortality rates between individuals with and those without HF. An epidemiological model was formulated that allowed deriving age-specific excess mortality rates in HF patients from HF incidence and prevalence. Incidence and prevalence were estimated from yearly collected cross-sectional data from four nationally representative General Practice registries in the Netherlands. The year 2007 was chosen as a reference. Next, excess mortality rates were used to calculate numbers of deaths among HF patients and compare the figures with national cause-of-death statistics. The latter were found to be more than three times smaller than the former (roughly 6000 vs. 21 000). Further, by applying HF prevalence and mortality rates to a life table of the Dutch population, average numbers of life years lost due to HF were calculated to be 6.9 years.ConclusionNational mortality statistics strongly underestimate the number of deaths associated with HF. Moreover, the high mortality rate in HF patients amounts to a remarkably large number of life years lost given the advanced age of disease onset. http://repub.eur.nl/res/pub/25523/ 2011-03-17T00:00:00Z Background: Estimates of disease incidence and prevalence are core indicators of public health. The manner in which these indicators stand out against each other provide guidance as to which diseases are most common and what health problems deserve priority. Our aim was to investigate how routinely collected data from different general practitioner registration networks (GPRNs) can be combined to estimate incidence and prevalence of chronic diseases and to explore the role of uncertainty when comparing diseases. Methods. Incidence and prevalence counts, specified by gender and age, of 18 chronic diseases from 5 GPRNs in the Netherlands from the year 2007 were used as input. Generalized linear mixed models were fitted with the GPRN identifier acting as random intercept, and age and gender as explanatory variables. Using predictions of the regression models we estimated the incidence and prevalence for 18 chronic diseases and calculated a stochastic ranking of diseases in terms of incidence and prevalence per 1,000. Results: Incidence was highest for coronary heart disease and prevalence was highest for diabetes if we looked at the point estimates. The between GPRN variance in general was higher for incidence than for prevalence. Since uncertainty intervals were wide for some diseases and overlapped, the ranking of diseases was subject to uncertainty. For incidence shifts in rank of up to twelve positions were observed. For prevalence, most diseases shifted maximally three or four places in rank. Conclusion: Estimates of incidence and prevalence can be obtained by combining data from GPRNs. Uncertainty in the estimates of absolute figures may lead to different rankings of diseases and, hence, should be taken into consideration when comparing disease incidences and prevalences. http://repub.eur.nl/res/pub/26029/ 2011-03-01T00:00:00Z The aim of our study was to estimate the case fatality of a severe exacerbation from long-term survival data presented in the literature. A literature search identified studies reporting ≥1.5 yr survival after a severe chronic obstructive pulmonary disease (COPD) exacerbation resulting in hospitalisation. The survival curve of each study was divided into a critical and a stable period. Mortality during the stable period was then estimated by extrapolating the survival curve during the stable period back to the time of exacerbation onset. Case fatality was defined as the excess mortality that results from an exacerbation and was calculated as 1 minus the (backwardly) extrapolated survival during the stable period at the time of exacerbation onset. The 95% confidence intervals (CI) of the estimated case fatalities were obtained by bootstrapping. A random effect model was used to combine all estimates into a weighted average with 95% CI. The meta-analysis based on six studies that fulfilled the inclusion criteria resulted in a weighted average case-fatality rate of 15.6% (95% CI 10.9-20.3), ranging from 11.4% to 19.0% for the individual studies. A severe COPD exacerbation requiring hospitalisation not only results in higher mortality risks during hospitalisation, but also in the time-period after discharge and contributes substantially to total COPD mortality. Copyright http://repub.eur.nl/res/pub/20172/ 2010-07-01T00:00:00Z http://repub.eur.nl/res/pub/19645/ 2010-06-01T00:00:00Z Background Smoking cessation can be encouraged by reimbursing the costs of smoking cessation support (SCS). The short-term efficiency of reimbursement has been evaluated previously. However, a thorough estimate of the long-term cost-utility is lacking. Objectives To evaluate long-term effects of reimbursement of SCS. Methods Results from a randomized controlled trial were extrapolated to long-term outcomes in terms of health care costs and (quality adjusted) life years (QALY) gained, using the Chronic Disease Model. Our first scenario was no reimbursement. In a second scenario, the short-term cessation rates from the trial were extrapolated directly. Sensitivity analyses were based on the trial's confidence intervals. In the third scenario the additional use of SCS as found in the trial was combined with cessation rates from international meta-analyses. Results Intervention costs per QALY gained compared to the reference scenario were approximately €1200 extrapolating the trial effects directly, and €4200 when combining the trial's use of SCS with the cessation rates from the literature. Taking all health care effects into account, even costs in life years gained, resulted in an estimated incremental cost-utility of €4500 and €7400, respectively. In both scenarios costs per QALY remained below €16 000 in sensitivity analyses using a life-time horizon. Conclusions Extrapolating the higher use of SCS due to reimbursement led to more successful quitters and a gain in life years and QALYs. Accounting for overheads, administration costs and the costs of SCS, these health gains could be obtained at relatively low cost, even when including costs in life years gained. Hence, reimbursement of SCS seems to be cost-effective from a health care perspective. http://repub.eur.nl/res/pub/23202/ 2010-05-01T00:00:00Z http://repub.eur.nl/res/pub/23169/ 2010-04-01T00:00:00Z Abstract: 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. http://repub.eur.nl/res/pub/35777/ 2007-07-01T00:00:00Z Introduction: Several studies have estimated health effects resulting from tobacco tax increases. However, studies on the cost effectiveness of tobacco taxes are scarce. The aim of this study was to estimate the cost effectiveness of tobacco tax increases from a health care perspective, explicitly considering medical costs in life years gained. Methods: The effects of a tax increase were translated into effects on smoking quit rates. A dynamic population model then projected incidence, prevalence and health care costs of the major chronic diseases conditional on smoking status over time. Comparing to a current practice scenario, the differences in healthcare costs, tax revenues, life years and QALYs from a tobacco tax increase resulting in a price increase of 10% increase were estimated. Results: Including effects on health care costs in life years gained, the tax increase costs about €2500 per QALY gained. Only 3% of additional tax revenues are enough to compensate additional health care costs in life years gained. Conclusions: Even if the health care costs in life years gained are taken into account and even if additional tax revenues do not flow to the health care sector a tax increase is a cost-effective intervention to increase public health from a health care perspective. http://repub.eur.nl/res/pub/36677/ 2007-04-01T00:00:00Z An important subject of debate in cost-utility analysis of health care programmes is whether to include costs of unrelated medical care in life years gained. The inclusion of such costs is likely to be of consequence in the case of primary prevention. This paper presents different strategies regarding the inclusion not only of the costs, but also of the health effects of unrelated medical care in economic evaluations. Four different cost-utility ratios are presented and related to the criterion of internal consistency. In addition, the possibility to relate the ratios to a well-posed decision problem is analysed. An example computes the different ratios for smoking cessation interventions in different age groups. Including health care costs of unrelated medical care in life years gained increases cost utility ratios, but excluding unrelated medical costs favours smoking cessation interventions targeted at older smokers over those at younger smokers. We conclude that for primary prevention only a cost utility ratio that includes both the costs and effects of unrelated medical care meets the criterion of internal consistency and is related to a meaningful decision problem. Therefore, this type of cost-utility ratio should be preferred even if the data requirements may be substantial. Copyright http://repub.eur.nl/res/pub/1343/ 2003-01-01T00:00:00Z Objectives: To estimate the cost-effectiveness of five face-to-face smoking cessation interventions: 1) Telephone Counseling (TC), 2) Minimal counseling by a general practitioner (H-MIS), 3) Minimal counseling by a general practitioner combined with Nicotine Replacement Therapy (H-MIS+NRT), 4) Intensive Counseling combined with Nicotine Replacement Therapy (IC+NRT) and 5) Intensive Counseling combined with Bupropion (IC+Bupr), in terms of costs per quitter, costs per life-year gained and costs per quality-adjusted life-year (QALY) gained. Methods: Scenarios on increased implementation of smoking cessation interventions were compared to current practice. Base-case scenarios assumed that one of the five interventions was implemented for a period of either 1 year, 10 years or 75 years and reached 25% of the smokers. A computer simulation model, the RIVM Chronic Disease Model, was used to project future gains in life-years and Quality Adjusted Life Years (QALYs), and savings of health care costs from a decrease in the incidence of smoking-related diseases. Regardless of the duration for which the intervention was implemented, our time horizon was 75 years, i.e. costs and effects were studied over a period of 75 years. Intervention costs were computed based on bottom up estimates of resource use and costs per unit of resource use. Cost calculations of smoking cessation interventions were carried out from a health care perspective, i.e. total direct medical costs were calculated based on estimates of real resource use. Effectiveness in terms of cessation rates was obtained from Cochrane meta-analyses. For the base-case scenarios, future costs and effects were discounted at an annual percentage of 4%. Incremental cost-effectiveness ratios were calculated as: (additional intervention costs minus the savings from a reduced incidence of smoking related diseases) / (gain in health outcomes). A series of one-way sensitivity analyses were performed to assess the robustness of the cost-effectiveness ratios with regard to variations in cessation rates, intervention costs, discount rates, time horizon, and the percentage of smokers reached by the intervention. Results: Base-case estimates for costs per quitter ranged from Euro 443 for H-MIS to Euro 2800 for IC+NRT. Compared to current practice H-MIS is a dominant intervention regardless of the duration of implementation. This means that H-MIS not only generates gains in life years and QALYs but its saving are higher than its intervention costs. The four other interventions had relatively low cost-effectiveness ratios when compared to many other preventive interventions. When implementing each of the interventions for a period of 75 years, their ratios varied from about Euro 1400 per life year gained for TC to Euro 6200 per life year gained for IC+NRT. Incremental costs per QALY gained were Euro 1100 for TC, Euro 1400 for H-MIS+NRT, Euro 3400 for IC+Bupr, and Euro 4,900 for IC+NRT. Results were most sensitive to the rate of discounting. Conclusions: All five smoking-cessation interventions are very cost-effective, with ratios far below Euro 20000. H-MIS is even cost saving. http://repub.eur.nl/res/pub/1344/ 2003-01-01T00:00:00Z Objectives: 1) To improve an existing COPD model by incorporating the distinction between mild, moderate, severe and very severe COPD and by quantifying the progression of COPD over these stages 2) To use the improved model to estimate the potential impact of smoking cessation programs offered to COPD patients and project their effect on the future burden of COPD. Methods: An existing population model for COPD, which is a module of the RIVM Chronic Disease model, was extended with disease progression over time. Prevalent cases in the starting year were distributed over 4 severity stages mild (28%), moderate (54%), severe (15%) and very severe (3%) (GOLD-classification). The severity distribution was based on data from GP registrations. The COPD incidence was 41% in mild, 55% in moderate and 4% in severe. Disease progression was modelled as annual decline in lung function in FEV1% predicted. The Lung Health Study was used to estimate gender, age, smoking and baseline FEV1% predicted dependent values of lung function decline and one-time increase in lung function associated with smoking cessation. A meta-analysis was done to obtain severity stage specific mortality rates. The new model was used to project COPD prevalence, mortality and costs by COPD severity stage over the period 2000-2025 (the base-case scenario). A series of sensitivity analyses was performed to assess the robustness of the results to changes in input data and assumptions. The new model was used to compare two scenarios on increased implementation of two smoking cessation interventions, minimal counselling by the general practioner (H-MIS) and intensive counselling with bupropion (IC+Bupr). They were compared to the base-case scenario in terms of life-years, QALYs, interventions costs and savings of COPD-related costs. In the scenarios H-MIS or IC+Bupr was implemented for a period of either 1 year, 10 years or 25 years and reached 25% of the smokers. Smoking cessation results in a one-time increase in lung function and a lower annual decline in FEV1% predicted, which results in less disease progression and less mortality among COPD patients who quit smoking. Future costs and effects of these scenarios were discounted at 4%. Incremental cost-effectiveness ratios were calculated as (additional intervention costs minus the savings in COPD-related health care costs)/ gain in health outcomes. Results: In the base-case scenario, the total number of COPD patients increases from 300 thousand in 2000 to 490 thousand patients in 2025. Between 2000 and 2025 the prevalence rate of mild COPD increases from 5 to 11 per 1000 inhabitants. The prevalence rate of moderate COPD increases from 11 to 14. For severe COPD the rate increases from 3.0 to 3.9 and for very severe COPD the rate increases from 0.5 to 1.3. In absolute numbers the increase is highest in mild COPD, but the largest relative increase in prevalence rate is seen in very severe COPD. As a result of the increase in COPD prevalence and aging of the COPD population, all-cause mortality rates per 1000 inhabitants increase in all severity stages. In 2000, total COPD-related health care costs are estimated to be 280 million Euros. In 2025 total costs are projected to be 495 million Euros. Costs for very severe COPD have the highest relative increase. The sensitivity analyses show that the model projections were most sensitive to assumptions about the severity distribution of incidence. Implementation of H-MIS and IC+Bupr results in more mild and moderate and less severe and very severe COPD patients compared to the base-case scenario after 25 years. Costs per additional quitter are 700 for H-MIS and 2700 for IC+Bupr. Irrespective of the duration of implementation, H-MIS generates net savings, which indicates that the intervention costs of H-MIS are offset by the savings in COPD-related costs. For IC+Bupr savings do not outweigh the interventions costs. For the years 2000 to 2025 the costs per life-year gained of implementing IC+Bupr for 10 years are estimated to be 12000 Euros. Conclusions: Modelling COPD progression over time proves feasible. The model showed that implementation of H-MIS among COPD patients results in better health outcomes and is cost saving. Implementation of IC+Bupr has higher costs than savings, but is still cost-effective with costs per life-year ranging from 10600 to 24500 depending on the duration of implementation.