title: Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors.
abstract: OBJECTIVE
  We sought to determine which ICD-9-CM codes in Medicare Part A data identify cardiovascular and stroke risk factors.
  
  
  METHODS
  This was a cross-sectional study comparing ICD-9-CM data to structured medical record review from 23,657 Medicare beneficiaries aged 20 to 105 years who had atrial fibrillation.
  
  
  METHODS
  Quality improvement organizations used standardized abstraction instruments to determine the presence of 9 cardiovascular and stroke risk factors. Using the chart abstractions as the gold standard, we assessed the accuracy of ICD-9-CM codes to identify these risk factors.
  
  
  RESULTS
  ICD-9-CM codes for all risk factors had high specificity (>0.95) and low sensitivity (< or =0.76). The positive predictive values were greater than 0.95 for 5 common, chronic risk factors-coronary artery disease, stroke/transient ischemic attack, heart failure, diabetes, and hypertension. The sixth common risk factor, valvular heart disease, had a positive predictive value of 0.93. For all 6 common risk factors, negative predictive values ranged from 0.52 to 0.91. The rare risk factors-arterial peripheral embolus, intracranial hemorrhage, and deep venous thrombosis-had high negative predictive value (> or =0.98) but moderate positive predictive values (range, 0.54-0.77) in this population.
  
  
  CONCLUSIONS
  Using ICD-9-CM codes alone, heart failure, coronary artery disease, diabetes, hypertension, and stroke can be ruled in but not necessarily ruled out. Where feasible, review of additional data (eg, physician notes or imaging studies) should be used to confirm the diagnosis of valvular disease, arterial peripheral embolus, intracranial hemorrhage, and deep venous thrombosis.
authors.affiliation: Division of General Medical Sciences, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
authors.forename: Elena
authors.initials: E
authors.lastname: Birman-Deych
authors.forename: Amy D
authors.initials: AD
authors.lastname: Waterman
authors.forename: Yan
authors.initials: Y
authors.lastname: Yan
authors.forename: David S
authors.initials: DS
authors.lastname: Nilasena
authors.forename: Martha J
authors.initials: MJ
authors.lastname: Radford
authors.forename: Brian F
authors.initials: BF
authors.lastname: Gage
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001281:Atrial Fibrillation / Q000150:complications* / Q000453:epidemiology; D002318:Cardiovascular Diseases / Q000145:classification / Q000175:diagnosis / Q000517:prevention & control*; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D016344:Medicare Part A; D008875:Middle Aged; D011237:Predictive Value of Tests; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity; D020521:Stroke / Q000145:classification / Q000175:diagnosis / Q000517:prevention & control*; D014481:United States / Q000453:epidemiology