http://repub.eur.nl/res/aut/39826/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/39702/ 2013-03-25T00:00:00Z Background: Computed tomography (CT) is important in diagnosing and managing many conditions, including coronary artery disease (CAD) and congenital heart disease. Current CT scanners can very accurately diagnose CAD requiring revascularisation in most patients. However, imaging technologies have developed rapidly and new-generation computed tomography (NGCCT) scanners may benefit patients who are difficult to image (e.g. obese patients, patients with high or irregular heart beats and patients who have high levels of coronary calcium or a previous stent or bypass graft). Objective: To assess the clinical effectiveness and cost-effectiveness of NGCCT for diagnosing clinically significant CAD in patients who are difficult to image using 64-slice computed tomography and treatment planning in complex congenital heart disease. Data sources: Bibliographic databases were searched from 2000 to February/March 2011, including MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews (CDSR), Cochrane Central Register of Controlled Trials (CENTRAL), Database of Abstracts of Reviews of Effects (DARE), NHS Economic Evaluation Database (NHS EED), Health Technology Assessment (HTA) database and Science Citation Index (SCI). Trial registers and conference proceedings were searched. Review methods: Systematic review methods followed published guidance. Risk of bias was assessed using QUADAS-2. Results were stratified by patient group. Summary sensitivity and specificity were calculated using a bivariate summary receiver operating characteristic, or random effects model. Heterogeneity was assessed using the chisquared statistic and I2-statistic. Cost-effectiveness of NGCCT was modelled separately for suspected and known CAD, evaluating invasive coronary angiography (ICA) only, ICA after positive NGCCT (NGCCT-ICA), and NGCCT only. The cost-effectiveness of NGCCT, compared with 64-slice CT, in reducing imaging-associated radiation in congenital heart disease was assessed. Results: Twenty-four studies reported accuracy of NGCCT for diagnosing CAD in difficult-to-image patients. No clinical effectiveness studies of NGCCT in congenital heart disease were identified. The pooled per-patient estimates of sensitivity were 97.7% [95% confidence interval (CI) 88.0% to 99.9%], 97.7% (95% CI 93.2% to 99.3%) and 96.0% (95% CI 88.8% to 99.2%) for patients with arrhythmias, high heart rates and previous stent, respectively. The corresponding estimates of specificity were 81.7% (95% CI 71.6% to 89.4%), 86.3% (95% CI 80.2% to 90.7%) and 81.6% (95% CI 74.7% to 87.3%), respectively. In patients with high coronary calcium scores, previous bypass grafts or obesity, only per-segment or per-artery data were available. Sensitivity estimates remained high (> 90% in all but one study). In patients with suspected CAD, the NGCCTonly strategy appeared most cost-effective; the incremental cost-effectiveness ratio (ICER) of NGCCT-ICA compared with NGCCT only was £71,000. In patients with known CAD, the most cost-effective strategy was NGCCT-ICA (highest cost saving, dominates ICA only). The ICER of NGCCT only compared with NGCCT-ICA was £726,230. For radiation exposure only, the ICER for NGCCT compared with 64-slice CT in congenital heart disease ranged from £521,000 for the youngest patients to £90,000 for adults. Limitations: Available data were limited, particularly for obese patients and patients with previous bypass grafts. All studies of the accuracy of NGCCT assume that the reference standard (ICA) is 100% sensitive and specific; however, there is some evidence that ICA may sometimes underestimate the extent and severity of stenosis. Patients with more than one criterion that could contribute to difficulty in imaging were often excluded from studies; the effect on test accuracy of multiple difficult to image criteria remains uncertain. Conclusions: NGCCT may be sufficiently accurate to diagnose clinically significant CAD in some or all difficult-to-image patient groups. Economic analyses suggest that NGCCT is likely to be considered cost-effective for difficult-to-image patients with CAD, at current levels of willingness to pay in the NHS. For patients with suspected CAD, NGCCT only would be most favourable; for patients with known CAD, NGCCT-ICA would be most favourable. No studies assessing the effects of NGCCT on therapeutic decision making, or subsequent patient outcomes, were identified. The ideal study to address these questions would be a large multi-centre RCT. However, one possible alternative might be to establish a multicentre tracker study. High-quality test accuracy studies, particularly in obese patients, patients with high coronary calcium, and those with previous bypass grafts are needed to confirm the findings of our systematic review. These studies should include patients with multiple difficult to image criteria. Funding: The National Institute for Health Research Health Technology Assessment programme. This project was funded by the HTA programme, on behalf of NICE, as project number 10/107/01. 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/37723/ 2012-09-01T00:00:00Z Objective: Western Europe has high levels of alcohol consumption, with corresponding adverse health effects. Currently, a major revision of the EU excise tax regime is under discussion. We quantify the health impact of alcohol price increases across the EU. Data and method: We use alcohol consumption data for 11 member states, covering 80% of the EU-27 population, and corresponding country-specific disease data (incidence, prevalence, and case-fatality rate of alcohol related diseases) taken from the 2010 published Dynamic Modelling for Health Impact Assessment (DYNAMO-HIA) database to dynamically project the changes in population health that might arise from changes in alcohol price. Results: Increasing alcohol prices towards those of Finland (the highest in the EU) would postpone approximately 54,000 male and approximately 26,100 female deaths over 10. years. Moreover, the prevalence of a number of chronic diseases would be reduced: in men by approximately 97,800 individuals with diabetes, 65,800 with stroke and 62,200 with selected cancers, and in women by about 19,100, 23,500, and 27,100, respectively. Conclusion: Curbing excessive drinking throughout the EU completely would lead to substantial gains in population health. Harmonisiation of prices to the Finnish level would, for selected diseases, achieve more than 40% of those gains. http://repub.eur.nl/res/pub/37852/ 2011-11-18T00:00:00Z Health Impact Assessment (HIA) – the evaluation policies, projects, or proposals concerning their effects on human health – becomes increasingly common practice at the local, national, and EU-level. So far, no standard tool exists to aid the quantification step in HIA. This thesis proposes dynamic population health modeling as a methodological foundation for quantitative HIA by motivating and introducing a ready-to-use software tool for this purpose: DYNAMO-HIA. This tool is equipped with a unique and novel data-set, covering the most important life-style risk factors (alcohol, smoking, obesity) and a number of related chronic diseases enabling to conduct HIAs for most EU countries. In addition, selected applications are presented ranging from the health consequences of an EU-wide tax increase on alcohol to the quantification of the life-long health benefits of reducing obesity when entering adulthood. http://repub.eur.nl/res/pub/28038/ 2010-01-01T00:00:00Z Background: The health impact assessment (HIA) of policy proposals is becoming common practice. HIA represents a broad approach with quantification of the impact of policy options at its core. However, no standard tool is available and it remains unclear whether any current model can serve as a standard for the field. Purpose: The aim of this study is to assess whether already existing models can be used as a standard tool for the quantification step in an HIA. Methods: A search in 2008 identified 20 models for HIA, of which six are sufficiently generic to allow for various and multiple diseases and different risk factors: Age-Related Morbidity and Death Analysis, Global Burden of Disease, Population Health Modeling, PREVENT, Proportional Life Table Method, and the National Institute for Public Health and the Environment (the Netherlands) Chronic Disease Model. These were evaluated along three proposed model structure criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) developed to address the needs and requirements of the HIA framework. Results: Of the six generic models investigated, none fulfills all the proposed criteria as a standard HIA tool. The models are either technically advanced with no or limited accessibility, or they are accessible but oversimplified. Conclusions: Further work on models for HIA with equal emphasis on technical appropriateness, availability of data, and end-user-friendly implementation is warranted if the field is to move forward.