title: Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records.
abstract: BACKGROUND
  Many cardiovascular epidemiologic studies rely on diagnosis codes in health care claims databases. Despite important changes in the care and diagnosis of acute myocardial infarction (AMI), the validity of hospital discharge diagnosis codes for AMI in the US Medicare system has not been recently examined. Our objective was to examine the accuracy of International Classification of Diseases--ninth revision--Clinical Modifications (ICD-9-CM) discharge diagnosis codes and diagnosis-related groups (DRG) codes for AMI in a Medicare claims database.
  
  
  METHODS
  We sampled hospitalization episodes from Medicare beneficiaries in Pennsylvania during 1999, 2000, or both. We used Medicare data to identify patients with hospitalizations containing indicators of AMI (ICD-9-CM diagnosis codes 410.X0 and 410.X1 or DRG codes 121, 122, and 123). Hospital records for these episodes were reviewed by trained abstractors using World Health Organization criteria for diagnosing AMI. We then calculated the positive predictive value of Medicare claims-based definitions of AMI.
  
  
  RESULTS
  Of 2200 hospitalization episodes with Medicare diagnosis codes suggestive of AMI, 2022 hospital records (91.9%) were obtained. The positive predictive value for a primary Medicare claims-based definition was 94.1% (95% CI, 93.0%-95.2%). Positive predictive values for alternative claims-based definitions ranged slightly, with the definition including DRG codes and length-of-stay restrictions yielding the highest positive predictive value, 95.4% (95% CI, 94.3%-96.4%). Subjects with a history of myocardial infarction had a significantly lower positive predictive value than subjects without a history of myocardial infarction (88.1% vs 94.6%, P <.001).
  
  
  CONCLUSIONS
  In this study, we observed high positive predictive values for a Medicare claims-based diagnosis of AMI and a diagnosis based on structured hospital record review.
authors.affiliation: Division of Pharmacoepidemiology and Pharmacoeconomics, Boston, Mass USA.
authors.forename: Yuka
authors.initials: Y
authors.lastname: Kiyota
authors.forename: Sebastian
authors.initials: S
authors.lastname: Schneeweiss
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Glynn
authors.forename: Carolyn C
authors.initials: CC
authors.lastname: Cannuscio
authors.forename: Jerry
authors.initials: J
authors.lastname: Avorn
authors.forename: Daniel H
authors.initials: DH
authors.lastname: Solomon
mesh_terms: D000368:Aged; D003402:Creatine Kinase / Q000097:blood; D052279:Creatine Kinase, MB Form; D003953:Diagnosis-Related Groups; D005260:Female; D006753:Hospital Records; D006760:Hospitalization; D006801:Humans; D007344:Insurance Claim Reporting; D038801:International Classification of Diseases; D007527:Isoenzymes / Q000097:blood; D008297:Male; D008485:Medical Audit; D006278:Medicare; D009203:Myocardial Infarction / Q000097:blood / Q000145:classification / Q000175:diagnosis*; D010351:Patient Discharge; D010414:Pennsylvania; D011237:Predictive Value of Tests; D012015:Reference Standards; D014336:Troponin / Q000097:blood
chemical_list: D007527:Isoenzymes; D014336:Troponin; D003402:Creatine Kinase; D052279:Creatine Kinase, MB Form