title: Positive predictive value of computerized medical records for uncomplicated and complicated upper gastrointestinal ulcer.
abstract: OBJECTIVE
  Computerized databases can be an efficient resource to study the epidemiology of peptic ulcer (PU) and upper gastrointestinal complications (UGIC) if we achieve a high positive predictive value (PPV) of outcome definitions. We assessed the PPV of diagnosis codes in THIN, a primary-care medical-record database, to ascertain individuals with uncomplicated PU, and to identify UGIC and Helicobacter pylori infection status (HPIS) among these patients.
  
  
  METHODS
  We identified: (1) patients with codes suggesting a first episode of uncomplicated PU; (2) episodes of UGIC among them. The computerized profiles with free-text comments of these individuals were reviewed and classified as definite, possible, or excluded cases. Dates and HPIS were also ascertained. For a sample of definite and possible PU, and for all UGIC cases, primary care physicians were sent a questionnaire for confirmation.
  
  
  RESULTS
  The 5296 individuals with codes suggesting PU were classified as definite (49%), possible (25%), and excluded (26%) cases. The PPV for definite/possible PU was 94% (99% for definite, 84% for possible cases). Of the questionnaires with information on HPIS (62%), the PPV and NPV were 100%. The 97 individuals with codes suggesting UGIC were classified as definite (48%), possible (27%), and excluded (22%) cases; the PPV for definite/possible was 95% (100% for definite, 88% for possible cases). Code dates were generally later than medical-record dates.
  
  
  CONCLUSIONS
  The identification of PU cases and their HPIS and UGIC requires careful review of the computerized clinical information with free-text comments. The validation of a sample is needed to confirm the accuracy of the diagnoses.
authors.affiliation: Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA. andreamargulis@post.harvard.edu
authors.forename: Andrea V
authors.initials: AV
authors.lastname: Margulis
authors.forename: Luis A
authors.initials: LA
authors.lastname: García Rodríguez
authors.forename: Sonia
authors.initials: S
authors.lastname: Hernández-Díaz
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016481:Helicobacter Infections / Q000175:diagnosis / Q000382:microbiology; D016480:Helicobacter pylori / Q000302:isolation & purification; D006801:Humans; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data; D008875:Middle Aged; D010437:Peptic Ulcer / Q000175:diagnosis* / Q000453:epidemiology / Q000382:microbiology; D011237:Predictive Value of Tests; D011320:Primary Health Care / Q000706:statistics & numerical data; D015203:Reproducibility of Results