title: Validation of chronic obstructive pulmonary disease recording in the Clinical Practice Research Datalink (CPRD-GOLD).
abstract: OBJECTIVE
  The optimal method of identifying people with chronic obstructive pulmonary disease (COPD) from electronic primary care records is not known. We assessed the accuracy of different approaches using the Clinical Practice Research Datalink, a UK electronic health record database.
  
  
  METHODS
  951 participants registered with a CPRD practice in the UK between 1 January 2004 and 31 December 2012. Individuals were selected for ≥1 of 8 algorithms to identify people with COPD. General practitioners were sent a brief questionnaire and additional evidence to support a COPD diagnosis was requested. All information received was reviewed independently by two respiratory physicians whose opinion was taken as the gold standard.
  
  
  METHODS
  The primary measure of accuracy was the positive predictive value (PPV), the proportion of people identified by each algorithm for whom COPD was confirmed.
  
  
  RESULTS
  951 questionnaires were sent and 738 (78%) returned. After quality control, 696 (73.2%) patients were included in the final analysis. All four algorithms including a specific COPD diagnostic code performed well. Using a diagnostic code alone, the PPV was 86.5% (77.5-92.3%) while requiring a diagnosis plus spirometry plus specific medication; the PPV was slightly higher at 89.4% (80.7-94.5%) but reduced case numbers by 10%. Algorithms without specific diagnostic codes had low PPVs (range 12.2-44.4%).
  
  
  CONCLUSIONS
  Patients with COPD can be accurately identified from UK primary care records using specific diagnostic codes. Requiring spirometry or COPD medications only marginally improved accuracy. The high accuracy applies since the introduction of an incentivised disease register for COPD as part of Quality and Outcomes Framework in 2004.
authors: Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
authors: Jennifer K
authors: JK
authors: Quint
authors: Department of Respiratory Epidemiology, GlaxoSmithKline R&D, Uxbridge, UK.
authors: Hana
authors: H
authors: Müllerova
authors: Department of Respiratory Epidemiology, GlaxoSmithKline R&D, ResearchTriangle Park, North Carolina, USA.
authors: Rachael L
authors: RL
authors: DiSantostefano
authors: Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
authors: Harriet
authors: H
authors: Forbes
authors: Clinical Practice Research Datalink Group, Medicines and Healthcare Products Regulatory Agency, London, UK.
authors: Susan
authors: S
authors: Eaton
authors: Department of UCL Respiratory Medicine, Royal Free Campus, University College London Medical School, London, UK.
authors: John R
authors: JR
authors: Hurst
authors: Department of Respiratory Epidemiology, GlaxoSmithKline R&D, Uxbridge, UK.
authors: Kourtney
authors: K
authors: Davis
authors: Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
authors: Liam
authors: L
authors: Smeeth
mesh_terms: D000368:Aged; D000465:Algorithms; D035843:Biomedical Research; D016208:Databases, Factual; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011320:Primary Health Care; D029424:Pulmonary Disease, Chronic Obstructive
keywords: RESPIRATORY MEDICINE (see Thoracic Medicine); THORACIC MEDICINE