title: An algorithm to identify incident myocardial infarction using Medicaid data.
abstract: OBJECTIVE
  Studies of non-steroidal anti-inflammatory drugs (NSAIDs) and cardiovascular events using administrative data require identification of incident acute myocardial infarctions (AMIs) and information on whether confounders differ by NSAID status.
  
  
  METHODS
  We identified patients with a first AMI hospitalization from Tennessee Medicaid files as those with primary ICD-9 discharge diagnosis 410.x and hospitalization stay of > 2 calendar days. Eligible persons were non-institutionalized, aged 50-84 years between 1999-2004, had continuous enrollment and no AMI, stroke, or non-cardiovascular serious medical illness in the prior year. Of 5524 patients with a potential first AMI, a systematic sample (n = 350) was selected for review. Using defined criteria, we classified events using chest pain history, EKG, and cardiac enzymes, and calculated the positive predictive value (PPV) for definite or probable AMI.
  
  
  RESULTS
  337 of 350 (96.3%) charts were abstracted and 307 (91.1%), 6 (1.8%), and 24 (7.1%) events were categorized as definite, probable, and no AMI, respectively. PPV for any definite or probable AMI was 92.8% (95% CI 89.6-95.2); for an AMI without an event in the past year 91.7% (95% CI 88.3-94.2), and for an incident AMI was 72.7% (95% CI 67.7-77.2). Age-adjusted prevalence of current smoking (46.4% vs. 39.1%, p = 0.35) and aspirin use (36.9% vs. 35.9%, p = 0.90) was similar among NSAID users and non-users
  
  
  CONCLUSIONS
  ICD-9 code 410.x had high predictive value for identifying AMI. Among those with AMI, smoking and aspirin use was similar in NSAID exposure groups, suggesting these factors will not confound the relationship between NSAIDs and cardiovascular outcomes.
authors.affiliation: Veterans Administration, Tennessee Valley Healthcare System, Tennessee Valley Geriatric Research Education Clinical Center (GRECC), Nashville, TN 37212, USA.
authors.forename: Neesha N
authors.initials: NN
authors.lastname: Choma
authors.forename: Marie R
authors.initials: MR
authors.lastname: Griffin
authors.forename: Robert L
authors.initials: RL
authors.lastname: Huang
authors.forename: Edward F
authors.initials: EF
authors.lastname: Mitchel
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Kaltenbach
authors.forename: Patricia
authors.initials: P
authors.lastname: Gideon
authors.forename: Shannon M
authors.initials: SM
authors.lastname: Stratton
authors.forename: Christianne L
authors.initials: CL
authors.lastname: Roumie
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000008:administration & dosage / Q000009:adverse effects*; D015331:Cohort Studies; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D008875:Middle Aged; D009203:Myocardial Infarction / Q000139:chemically induced / Q000453:epidemiology*; D012189:Retrospective Studies; D013714:Tennessee / Q000453:epidemiology; D014481:United States / Q000453:epidemiology
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal