Validation of general practitioner-diagnosed COPD in the UK General Practice Research Database
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Background: Information in large, automated databases can be useful to study the natural history of respiratory diseases in the community, but the validity of definitions needs to be demonstrated. Aim: To compare a simple computer algorithm that identifies patients diagnosed with chronic obstructive pulmonary disease (COPD) and severity of COPD in the UK General Practice Research Database (GPRD) with general practitioner (GP) clinical records, to evaluate the utility of this algorithm for identifying COPD patients and for distinguishing COPD from asthma. Methods: Using a computer algorithm identifying patients by diagnostic codes and allotting three grades of severity by drug use, a sample of 225 patients in the GPRD with a diagnosis of COPD and an age–sex matched group of 75 patients with asthma were randomly selected. Questionnaires were posted to the GPs of the 300 selected patients who were asked to state diagnosis and to grade severity based on the individual's medical record. Agreement was quantified with the κ index, an estimator that accounts for agreement that occurs by chance. Results: Response rate was 85.7%. The concordance between COPD diagnosis by the GPRD algorithm with that of the GP was quantified as a κ of 0.52, and the concordance between COPD severity by the GPRD algorithm with that of the GP was quantified as a κ of 0.54. The κ index for COPD diagnosis increased with increasing severity of COPD (0.46, 0.59, and 0.68 for mild, moderate and severe COPD, respectively), but similar good agreement was observed in a stratified analysis by sex, age, smoking status and number of comorbidities. Conclusions: It is concluded that the GPRD algorithms used for diagnosis and severity of COPD are a good screening tool for COPD in the UK general population, and satisfactorily differentiate COPD from asthma patients, particularly when disease is moderate or severe.
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European Journal of Epidemiology
Volume 17, Issue 12 , pp 1075-1080
- Cover Date
- Print ISSN
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- Kluwer Academic Publishers
- Additional Links
- Automated database
- κ index
- Industry Sectors
- Author Affiliations
- 1. Worldwide Epidemiology, GlaxoSmithKline Research and Development, Greenford, Middlesex, London, UK
- 2. Health Promotion Research Unit, London School of Hygiene and Tropical Medicine, London, UK