Abstract

Background With the increasing recognition of asthma and chronic obstructive pulmonary disease (COPD) overlap syndrome (ACOS) and its significant disease and economic burden, knowledge about real-world patient characteristics and how they are treated is needed to aid in better understanding this phenotype. However, ACOS patient identification is challenging. Currently, there is no validated claims-based ACOS patient selection algorithm available to assist this type of research. To assess the validity of a retrospective claims-based algorithm to identify high likelihood ACOS patients using patient medical records as the criterion.

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