title: Validity of hospital discharge diagnosis codes for stroke: the Atherosclerosis Risk in Communities Study.
abstract: OBJECTIVE
  Characterizing International Classification of Disease 9th Revision, Clinical Modification (ICD-9-CM) code validity is essential given widespread use of hospital discharge databases in research. Using the Atherosclerosis Risk in Communities (ARIC) Study, we estimated the accuracy of ICD-9-CM stroke codes.
  
  
  METHODS
  Hospitalizations with ICD-9-CM codes 430 to 438 or stroke keywords in the discharge summary were abstracted for ARIC cohort members (1987-2010). A computer algorithm and physician reviewer classified definite and probable ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage. Using ARIC classification as a gold standard, we calculated the positive predictive value (PPV) and sensitivity of ICD-9-CM codes grouped according to the American Heart Association/American Stroke Association (AHA/ASA) 2013 categories and an alternative code grouping for comparison.
  
  
  RESULTS
  Thirty-three percent of 4260 hospitalizations were validated as strokes (1251 ischemic, 120 intracerebral hemorrhage, 46 subarachnoid hemorrhage). The AHA/ASA code groups had PPV 76% and 68% sensitivity compared with PPV 72% and 83% sensitivity for the alternative code groups. The PPV of the AHA/ASA code group for ischemic stroke was slightly higher among blacks, individuals <65 years, and at teaching hospitals. Sensitivity was higher among older individuals and increased over time. The PPV of the AHA/ASA code group for intracerebral hemorrhage was higher among blacks, women, and younger individuals. PPV and sensitivity varied across study sites.
  
  
  CONCLUSIONS
  A new AHA/ASA discharge code grouping to identify stroke had similar PPV and lower sensitivity compared with an alternative code grouping. Accuracy varied by patient characteristics and study sites.
authors.affiliation: From the Department of Epidemiology (S.A.J., W.D.R.) and Department of Biostatistics (L.W.), Gillings School of Global Public Health, University of North Carolina at Chapel Hill; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD (R.F.G.); and Epidemiology and Biostatistics Division, the University of Arizona College of Public Health, Tucson (E.S.).
authors.forename: Sydney A
authors.initials: SA
authors.lastname: Jones
authors.affiliation: From the Department of Epidemiology (S.A.J., W.D.R.) and Department of Biostatistics (L.W.), Gillings School of Global Public Health, University of North Carolina at Chapel Hill; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD (R.F.G.); and Epidemiology and Biostatistics Division, the University of Arizona College of Public Health, Tucson (E.S.).
authors.forename: Rebecca F
authors.initials: RF
authors.lastname: Gottesman
authors.affiliation: From the Department of Epidemiology (S.A.J., W.D.R.) and Department of Biostatistics (L.W.), Gillings School of Global Public Health, University of North Carolina at Chapel Hill; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD (R.F.G.); and Epidemiology and Biostatistics Division, the University of Arizona College of Public Health, Tucson (E.S.).
authors.forename: Eyal
authors.initials: E
authors.lastname: Shahar
authors.affiliation: From the Department of Epidemiology (S.A.J., W.D.R.) and Department of Biostatistics (L.W.), Gillings School of Global Public Health, University of North Carolina at Chapel Hill; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD (R.F.G.); and Epidemiology and Biostatistics Division, the University of Arizona College of Public Health, Tucson (E.S.).
authors.forename: Lisa
authors.initials: L
authors.lastname: Wruck
authors.affiliation: From the Department of Epidemiology (S.A.J., W.D.R.) and Department of Biostatistics (L.W.), Gillings School of Global Public Health, University of North Carolina at Chapel Hill; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD (R.F.G.); and Epidemiology and Biostatistics Division, the University of Arizona College of Public Health, Tucson (E.S.).
authors.forename: Wayne D
authors.initials: WD
authors.lastname: Rosamond
mesh_terms: D050197:Atherosclerosis / Q000175:diagnosis / Q000628:therapy*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D038801:International Classification of Diseases / Q000592:standards* / Q000639:trends; D008297:Male; D008875:Middle Aged; D010351:Patient Discharge / Q000592:standards* / Q000639:trends; D012111:Residence Characteristics; D020521:Stroke / Q000175:diagnosis / Q000628:therapy*
keywords: ICD-9-CM; cerebrovascular disease; predictive value; sensitivity