Background: Chronic obstructive pulmonary disease (COPD) is currently the fourth leading cause of death worldwide. It has serious health effects and causes substantial costs for society.
Objectives: The aim of the present paper was to develop a state-of-the-art decision-analytic model of COPD whereby the cost effectiveness of interventions in Germany can be estimated. To demonstrate the applicability of the model, a smoking cessation programme was evaluated against usual care.
Methods: A seven-stage Markov model (disease stages I to IV according to the GOLD [Global Initiative for Chronic Obstructive Lung Disease] classification, states after lung-volume reduction surgery and lung transplantation, death) was developed to conduct a cost-utility analysis from the societal perspective over a time horizon of 10, 40 and 60 years. Patients entered the cohort model at the age of 45 with mild COPD. Exacerbations were classified into three levels: mild, moderate and severe. Estimation of stage-specific probabilities (for smokers and quitters), utilities and costs was based on German data where possible. Data on effectiveness of the intervention was retrieved from the literature. A discount rate of 3% was applied to costs and effects. Probabilistic sensitivity analysis was used to assess the robustness of the results.
Results: The smoking cessation programme was the dominant strategy compared with usual care, and the intervention resulted in an increase in health effects of 0.54 QALYs and a cost reduction of &U20AC;1115 per patient (year 2007 prices) after 60 years. In the probabilistic analysis, the intervention dominated in about 95% of the simulations. Sensitivity analyses showed that uncertainty primarily originated from data on disease progression and treatment cost in the early stages of disease.
Conclusions: The model developed allows the long-term cost effectiveness of interventions to be estimated, and has been adapted to Germany. The model suggests that the smoking cessation programme evaluated was more effective than usual care as well as being cost-saving. Most patients had mild or moderate COPD, stages for which parameter uncertainty was found to be high. This raises the need to improve data on the early stages of COPD.