To develop a stochastic population model of disease progression in chronic obstructive pulmonary disease (COPD) that includes the effects of COPD exacerbations on health-related quality of life, costs, disease progression, and mortality and can be used to assess the effects of a wide range of interventions. The model is a multistate Markov model with time varying transition rates specified by age, sex, smoking status, COPD disease severity, and/or exacerbation type. The model simulates annual changes in COPD prevalence due to COPD incidence, exacerbations, disease progression (annual decline in the forced expiratory volume in 1 second as percentage of the predicted value), and mortality. The main outcome variables are quality-adjusted life years, total exacerbations, and COPD-related health care costs. Exacerbation-related input parameters were based on quantitative meta-analysis. All important model parameters are entered into the model as probability distributions. To illustrate the potential use of the model, costs and effects were calculated for 3-year implementation of three different COPD interventions, one pharmacologic, one on smoking cessation, and one on pulmonary rehabilitation using a time horizon of 10 years for reporting outcomes. Compared with minimal treatment the cost/quality-adjusted life year was €8,300 for the pharmacologic intervention, €10,800 for the smoking cessation therapy, €8,700 for the combination of the pharmacologic intervention and the smoking cessation therapy, and €17,200 for the pulmonary rehabilitation program. The probability of the interventions to be cost-effective at a ceiling ratio of €20,000 varied from 58% to 100%. The COPD model provides policy makers with information about the long-term costs and effects of interventions over the entire chain of care, from primary prevention to care for very severe COPD and includes uncertainty around the outcomes.

Additional Metadata
Keywords chronic obstructive pulmonary disease, exacerbations, model, probabilistic, progression
Persistent URL dx.doi.org/10.1016/j.jval.2011.06.008, hdl.handle.net/1765/68330
Journal Value in Health
Citation
Hoogendoorn, M, Rutten-van Mölken, M.P.M.H, Hoogenveen, R.T, Al, M.J, & Feenstra, T.L. (2011). Developing and applying a stochastic dynamic population model for chronic obstructive pulmonary disease. Value in Health, 14(8), 1039–1047. doi:10.1016/j.jval.2011.06.008