Science and Research

Systematic Analysis of Self-Reported Comorbidities in Large Cohort Studies - A Novel Stepwise Approach by Evaluation of Medication

OBJECTIVE: In large cohort studies comorbidities are usually self-reported by the patients. This way to collect health information only represents conditions known, memorized and openly reported by the patients. Several studies addressed the relationship between self-reported comorbidities and medical records or pharmacy data, but none of them provided a structured, documented method of evaluation. We thus developed a detailed procedure to compare self-reported comorbidities with information on comorbidities derived from medication inspection. This was applied to the data of the German COPD cohort COSYCONET. METHODS: Approach I was based solely on ICD10-Codes for the diseases and the indications of medications. To overcome the limitations due to potential non-specificity of medications, Approach II was developed using more detailed information, such as ATC-Codes specific for one disease. The relationship between reported comorbidities and medication was expressed by a four-level concordance score. RESULTS: Approaches I and II demonstrated that the patterns of concordance scores markedly differed between comorbidities in the COSYCONET data. On average, Approach I resulted in more than 50% concordance of all reported diseases to at least one medication. The more specific Approach II showed larger differences in the matching with medications, due to large differences in the disease-specificity of drugs. The highest concordance was achieved for diabetes and three combined cardiovascular disorders, while it was substantial for dyslipidemia and hyperuricemia, and low for asthma. CONCLUSION: Both approaches represent feasible strategies to confirm self-reported diagnoses via medication. Approach I covers a broad spectrum of diseases and medications but is limited regarding disease-specificity. Approach II uses the information from medications specific for a single disease and therefore can reach higher concordance scores. The strategies described in a detailed and reproducible manner are generally applicable in large studies and might be useful to extract as much information as possible from the available data.

  • Lucke, T.
  • Herrera, R.
  • Wacker, M.
  • Holle, R.
  • Biertz, F.
  • Nowak, D.
  • Huber, R. M.
  • Sohler, S.
  • Vogelmeier, C.
  • Ficker, J. H.
  • Muckter, H.
  • Jorres, R. A.
  • Cosyconet Consortium

Keywords

  • Aged
  • Cohort Studies
  • *Comorbidity
  • Data Collection
  • Drug Therapy/statistics & numerical data
  • Humans
  • International Classification of Diseases
  • Middle Aged
  • Pulmonary Disease, Chronic Obstructive/drug therapy/epidemiology
  • *Self Report
Publication details
DOI: 10.1371/journal.pone.0163408
Journal: PLoS One
Pages: e0163408 
Number: 10
Work Type: Original
Location: BREATH, CPC-M
Disease Area: General Lung and Other
Partner / Member: HMGU, KUM, LMU
Access-Number: 27792735
See publication on PubMed

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