<b>Background:</b> In large cohort studies comorbidities are commonly self-reported by the patients. Although this is a feasible way to collect information, it only represents conditions memorized. In order to improve the use of all available information, we developed a detailed procedure to compare self-reported comorbidities with medication and applied this to the data of the German COPD cohort COSYCONET. <b>Methods:</b> Approach I was based solely on ICD-10-codes for the diseases and the indications of medications. To deal with the non-specificity of medications, Approach II focused on disease-specific medication and ATC-codes. The relationship between comorbidities and medication was expressed by a four-level concordance score. <b>Results:</b> Approach I and II demonstrated that the patterns of concordance scores markedly differed between diseases. On average, Approach I resulted in more than 50% concordance of all reported diseases to at least one medication. Approach II showed particularly large differences in its ability of matching with medications, due to large differences in the disease-specificity of drugs, e.g. for diabetes versus specific cardiovascular disorders. <b>Conclusion:</b> Both approaches provide defined strategies to confirm self-reported diagnoses via medication. Approach I covers a broad spectrum of diseases and medications but is limited regarding disease-specific information. Approach II is based on medications specific for a disease and can reach higher concordance. The strategies described are generally applicable in large studies to extract as much information as possible from the available data. <i>Funded by BMBF COSYCONET and Mundipharma GmbH</i>.