Talitha Feenstra

Lifetime medical costs of obesity: Prevention no cure for increasing health expenditure

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.

A decision chart for assessing and improving the transferability of economic evaluation results between countries.

AbstractObjective: To develop a user-friendly tool for managing the transfer of economic evaluation results. Methods: Factors that may influence the transfer of health economic study results were systematically identified and the way they impact on transferability was investigated. A transferability decision chart was developed that includes: knock out criteria; a checklist based on the transferability factors; and methods for improving transferability and for assessing the uncertainty of transferred results. This approach was tested on various international cost-effectiveness studies in the areas of interventional cardiology, vaccination and screening. Results: The transfer of study results is possible pending the outcomes of the transferability check and necessary adjustments. Transferability factors can be grouped into areas of methodological, healthcare system and population characteristics. Different levels of effort are required for analysis of factors, ranging from very low (e.g. discount rate) to very high (e.g. practice variation). The impact of differences of most transferability factors can be estimated via the key health economic determinants: capacity utilisation, effectiveness, productivity loss and returns to scale.Depending on the outcomes of the transferability check a correction of the study results for inflation and for differences related to currencies or purchasing power might be sufficient. Otherwise, modelling-based adjustments might be necessary, requiring the (re-)building and sometimes structural modification of the study model. For determination of the most essential adjustments, a univariate sensitivity analysis seems appropriate. If not all relevant study parameters can be substituted with country-specific ones, multivariate or probabilistic sensitivity analysis seems to be a promising way to quantify the uncertainty associated with a transfer. If study results cannot be transferred, the transfer of study models or designs should be investigated as this can significantly save time when conducting a new study. Conclusions: Our transferability decision chart is a transparent and user-friendly tool for assessing and improving the transferability of economic evaluation results. A state of the art description of the methodology in a study, providing detailed components for calculation, is not only essential for determining its transferability but also for improving it via modelling adjustments.

Long-term effectiveness and cost-effectiveness of smoking cessation interventions in patients with COPD

Background The aim of this study was to estimate the long-term (cost-) effectiveness of smoking cessation interventions for patients with chronic obstructive pulmonary disease (COPD). Methods A systematic review was performed of randomised controlled trials on smoking cessation interventions in patients with COPD reporting 12-month biochemical validated abstinence rates. The different interventions were grouped into four categories: usual care, minimal counselling, intensive counselling and intensive counselling + pharmacotherapy (‘pharmacotherapy’). For each category the average 12-month continuous abstinence rate and intervention costs were estimated. A dynamic population model for COPD was used to project the long-term (cost-) effectiveness (25 years) of 1-year implementation of the interventions for 50% of the patients with COPD who smoked compared with usual care. Uncertainty and one-way sensitivity analyses were performed for variations in the calculation of the abstinence rates, the type of projection, intervention costs and discount rates. Results Nine studies were selected. The average 12-month continuous abstinence rates were estimated to be 1.4% for usual care, 2.6% for minimal counselling, 6.0% for intensive counselling and 12.3% for pharmacotherapy. Compared with usual care, the costs per quality-adjusted life year (QALY) gained for minimal counselling, intensive counselling and pharmacotherapy were €16 900, €8200 and €2400, respectively. The results were most sensitive to variations in the estimation of the abstinence rates and discount rates. Conclusion Compared with usual care, intensive counselling and pharmacotherapy resulted in low costs per QALY gained with ratios comparable to results for smoking cessation in the general population. Compared with intensive counselling, pharmacotherapy was cost saving and dominated the other interventions.

Unrelated medical costs in life-years gained: Should they be included in economic evaluations of healthcare interventions?

AbstractWhich costs and benefits to consider in economic evaluations of healthcare interventions remains an area of much controversy. Unrelated medical costs in life-years gained is an important cost category that is normally ignored in economic evaluations, irrespective of the perspective chosen for the analysis. National guidelines for pharmacoeconomic research largely endorse this practice, either by explicitly requiring researchers to exclude these costs from the analysis or by leaving inclusion or exclusion up to the discretion of the analyst. However, the inclusion of unrelated medical costs in life-years gained appears to be gaining support in the literature.This article provides an overview of the discussions to date. The inclusion of unrelated medical costs in life-years gained seems warranted, in terms of both optimality and internal and external consistency. We use an example of a smoking-cessation intervention to highlight the consequences of different practices of accounting for costs and effects in economic evaluations. Only inclusion of all costs and effects of unrelated medical care in life-years gained can be considered both internally and externally consistent. Including or excluding unrelated future medical costs may have important distributional consequences, especially for interventions that substantially increase length of life. Regarding practical objections against inclusion of future costs, it is important to note that it is becoming increasingly possible to accurately estimate unrelated medical costs in life-years gained. We therefore conclude that the inclusion of unrelated medical costs should become the new standard.

Dynamic effects of smoking cessation on disease incidence, mortality and quality of life: The role of time since cessation

BackgroundTo support health policy makers in setting priorities, quantifying the potential effects of tobacco control on the burden of disease is useful. However, smoking is related to a variety of diseases and the dynamic effects of smoking cessation on the incidence of these diseases differ. Furthermore, many people who quit smoking relapse, most of them within a relatively short period.MethodsIn this paper, a method is presented for calculating the effects of smoking cessation interventions on disease incidence that allows to deal with relapse and the effect of time since quitting. A simulation model is described that links smoking to the incidence of 14 smoking related diseases. To demonstrate the model, health effects are estimated of two interventions in which part of current smokers in the Netherlands quits smoking.To illustrate the advantages of the model its results are compared with those of two simpler versions of the model. In one version we assumed no relapse after quitting and equal incidence rates for all former smokers. In the second version, incidence rates depend on time since cessation, but we assumed still no relapse after quitting.ResultsNot taking into account time since smoking cessation on disease incidence rates results in biased estimates of the effects of interventions. The immediate public health effects are overestimated, since the health risk of quitters immediately drops to the mean level of all former smokers. However, the long-term public health effects are underestimated since after longer periods of time the effects of past smoking disappear and so surviving quitters start to resemble never smokers. On balance, total health gains of smoking cessation are underestimated if one does not account for the effect of time since cessation on disease incidence rates. Not taking into account relapse of quitters overestimates health gains substantially.ConclusionThe results show that simulation models are sensitive to assumptions made in specifying the model. The model should be specified carefully in accordance with the questions it is supposed to answer. If the aim of the model is to estimate effects of smoking cessation interventions on mortality and morbidity, one should include relapse of quitters and dependency on time since cessation of incidence rates of smoking-related chronic diseases. A drawback of such models is that data requirements are extensive.

Association between lung function and exacerbation frequency in patients with COPD.

Purpose: To quantify the relationship between severity of chronic obstructive pulmonary disease (COPD) as expressed by Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage and the annual exacerbation frequency in patients with COPD. Methods: We performed a systematic literature review to identify randomized controlled trials and cohort studies reporting the exacerbation frequency in COPD patients receiving usual care or placebo. Annual frequencies were determined for total exacerbations defined by an increased use of health care (event-based), total exacerbations defined by an increase of symptoms, and severe exacerbations defined by a hospitalization. The association between the mean forced expiratory volume in one second (FEV1)% predicted of study populations and the exacerbation frequencies was estimated using weighted log linear regression with random effects. The regression equations were applied to the mean FEV1% predicted for each GOLD stage to estimate the frequency per stage. Results: Thirty-seven relevant studies were found, with 43 reports of total exacerbation frequency (event-based, n = 19; symptom-based, n = 24) and 14 reports of frequency of severe exacerbations. Annual event-based exacerbation frequencies per GOLD stage were estimated at 0.82 (95% confidence interval 0.46–1.49) for mild, 1.17 (0.93–1.50) for moderate, 1.61 (1.51–1.74) for severe, and 2.10 (1.51–2.94) for very severe COPD. Annual symptom-based frequencies were 1.15 (95% confidence interval 0.67–2.07), 1.44 (1.14–1.87), 1.76 (1.70–1.88), and 2.09 (1.57–2.82), respectively. For severe exacerbations, annual frequencies were 0.11 (95% confidence interval 0.02–0.56), 0.16 (0.07–0.33), 0.22 (0.20–0.23), and 0.28 (0.14–0.63), respectively. Study duration or type of study (cohort versus trial) did not significantly affect the outcomes. Conclusion: This study provides an estimate of the exacerbation frequency per GOLD stage, which can be used for health economic and modeling purposes.

Cost effectiveness of preventive interventions in type 2 diabetes mellitus: a systematic literature review.

A systematic review of the literature was conducted to give an overview of economic evaluations of preventive interventions in type 2 diabetes mellitus. The interventions were sorted by type of preventive intervention (primary, secondary or tertiary) and by category (e.g. education, medication for hypertension). Several databases were searched for studies published between January 1990 and May 2004 on the three types of preventive intervention. For each study selected, inclusion of specific components from a standardised list of items, including quality, was recorded in a database. Summary tables were generated based on the database.A number of conclusions were drawn from this review. The most important was that strict blood pressure control was a more cost-effective intervention than less strict control, as shown by six studies reporting cost savings to very low costs per life-year gained. Primary and secondary prevention of type 2 diabetes were also highly cost effective, but these results were based on very few studies. Medications to reduce weight and hyperglycaemia together were cost effective compared with conventional interventions. Finally, the separate results regarding medications to reduce weight, hyperglycaemia and hypercholesterolaemia varied enormously, thus no conclusion could be drawn and further economic analysis is required.

AdViSHE: A Validation-Assessment Tool of Health-Economic Models for Decision Makers and Model Users.

BackgroundA trade-off exists between building confidence in health-economic (HE) decision models and the use of scarce resources. We aimed to create a practical tool providing model users with a structured view into the validation status of HE decision models, to address this trade-off.MethodsA Delphi panel was organized, and was completed by a workshop during an international conference. The proposed tool was constructed iteratively based on comments from, and the discussion amongst, panellists. During the Delphi process, comments were solicited on the importance and feasibility of possible validation techniques for modellers, their relevance for decision makers, and the overall structure and formulation in the tool.ResultsThe panel consisted of 47 experts in HE modelling and HE decision making from various professional and international backgrounds. In addition, 50 discussants actively engaged in the discussion at the conference workshop and returned 19 questionnaires with additional comments. The final version consists of 13 items covering all relevant aspects of HE decision models: the conceptual model, the input data, the implemented software program, and the model outcomes.ConclusionsAssessment of the Validation Status of Health-Economic decision models (AdViSHE) is a validation-assessment tool in which model developers report in a systematic way both on validation efforts performed and on their outcomes. Subsequently, model users can establish whether confidence in the model is justified or whether additional validation efforts should be undertaken. In this way, AdViSHE enhances transparency of the validation status of HE models and supports efficient model validation.

The burden of asthma and chronic obstructive pulmonary disease: data from The Netherlands

It is important to consider all aspects of the burden of a disease using a range of outcome measures — not only morbidity and mortality — but also the effect on patient lifestyle and healthcare resources, and the economic impact on the patient, healthcare system and society. Only with this complete appraisal can the full extent of the disease burden be assessed. It is also useful to look to the future to see how the number of patients affected by the disease is likely to change — this information is useful to place in context the consequences of any proposed interventions.The burden of asthma and chronic obstructive pulmonary disease (COPD) is considerable. The main cost element of asthma is medication, whereas hospitalisation accounts for the largest proportion of costs for COPD. Consequently, in The Netherlands, the annual cost per patient of managing COPD is almost 3 times as high as that of asthma. Together, the two respiratory conditions cost theDutch healthcare system

Cost-Effectiveness of Lifestyle Modification in Diabetic Patients

US346 million for direct medical costs in 1993, amounting to 1.3% of the total healthcare budget.The burden of COPD is expected to increase considerably in the future, reflecting the previous smoking habits of an aging population. Even if the current decline in the prevalence of smoking continues, by 2015 there will be a 76% increase in the prevalence of COPD (with the increase higher among women than men), compared with the prevalence in 1994. This is largely due to the aging of the population. This will need to be considered by decision-makers allocating funds to healthcare services. It also further underlines the need to maximise the value gained from limited resources available to manage asthma and COPD.