A Systematic Review of Health Economics Simulation Models of Chronic Obstructive Pulmonary Disease

Abstract

Background: Many decision-analytic models with varying structures have been developed to inform resource allocation in chronic obstructive pulmonary disease (COPD).

Objectives: To review COPD models for their adherence to the best practice modeling recommendations and their assumptions regarding important aspects of the natural history of COPD.

Methods: A systematic search of English articles reporting on the development or application of a decision-analytic model in COPD was performed in MEDLINE, Embase, and citations within reviewed articles. Studies were summarized and evaluated on the basis of their adherence to the Consolidated Health Economic Evaluation Reporting Standards. They were also evaluated for the underlying assumptions about disease progression, heterogeneity, comorbidity, and treatment effects.

Results: Forty-nine models of COPD were included. Decision trees and Markov models were the most popular techniques (43 studies). Quality of reporting and adherence to the guidelines were generally high, especially in more recent publications. Disease progression was modeled through clinical staging in most studies. Although most studies (n = 43) had incorporated some aspects of COPD heterogeneity, only 8 reported the results across subgroups. Only 2 evaluations explicitly considered the impact of comorbidities. Treatment effect had been mostly modeled (20) as both reduction in exacerbation rate and improvement in lung function.

Conclusions: Many COPD models have been developed, generally with similar structural elements. COPD is highly heterogeneous, and comorbid conditions play an important role in its burden. These important aspects, however, have not been adequately addressed in most of the published models.

Keywords: Markov models; chronic obstructive pulmonary disease; cost-effectiveness; discrete-event simulation; modeling.