title: The comparison of cardiovascular risk scores using two methods of substituting missing risk factor data in patient medical records.
abstract: BACKGROUND
  Targeted screening for cardiovascular disease (CVD) can be carried out using existing data from patient medical records. However, electronic medical records in UK general practice contain missing risk factor data for which values must be estimated to produce risk  scores.
  
  
  OBJECTIVE
  To compare two methods of substituting missing risk factor data; multiple imputation and the use of default National Health Survey values.
  
  
  METHODS
  We took patient-level data from patients in 70 general practices in Ealing, North West London. We substituted  missing risk factor data using the two methods, applied two risk scores (QRISK2 and JBS2) to the data and assessed differences between methods.
  
  
  RESULTS
  Using multiple imputation, mean CVD risk scores were similar to those using default national survey values, a simple method of  imputation. There were fewer patients designated as high risk (>20%) using multiple imputation, although differences were again small (10.3% compared with 11.7%; 3.0% compared with 3.4% in women). Agreement in high-risk classification between methods was high (Kappa = 0.91 in men; 0.90  in women).
  
  
  CONCLUSIONS
  A simple method of substituting missing risk factor data can produce reliable estimates of CVD risk scores. Targeted screening for high CVD risk, using pre-existing electronic medical record data, does not require multiple imputation methods in risk estimation.
authors: Department of Primary Care and Public Health, Imperial College, London, UK. andrew.dalton@imperial.ac.uk
authors: Andrew R H
authors: AR
authors: Dalton
authors: Alex
authors: A
authors: Bottle
authors: Michael
authors: M
authors: Soljak
authors: Cyprian
authors: C
authors: Okoro
authors: Azeem
authors: A
authors: Majeed
authors: Christopher
authors: C
authors: Millett
mesh_terms: D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000517:prevention & control; D015897:Comorbidity; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D006262:Health; D006305:Health Status Indicators; D006801:Humans; D008297:Male; D018570:Risk Assessment; D012307:Risk Factors; D012959:Socioeconomic Factors; D006113:United Kingdom