title: Accuracy of administrative billing codes to detect urinary tract infection hospitalizations.
abstract: BACKGROUND
  Hospital billing data are frequently used for quality measures and research, but the accuracy of the use of discharge codes to identify urinary tract infections (UTIs) is unknown.
  
  
  OBJECTIVE
  To determine the accuracy of International Classification of Diseases, 9th revision (ICD-9) discharge codes to identify children hospitalized with UTIs.
  
  
  METHODS
  This multicenter study conducted in 5 children's hospitals included children aged 3 days to 18 years who had been admitted to the hospital, undergone a urinalysis or urine culture, and discharged from the hospital. Data were obtained from the pediatric health information system database and medical record review. With the use of 2 gold-standard methods, the positive predictive value (PPV) was calculated for individual and combined UTI codes and for common UTI identification strategies. PPV was measured for all groupings for which the UTI code was the principal discharge diagnosis.
  
  
  RESULTS
  There were 833 patients in the study. The PPV was 50.3% with the use of the gold standard of laboratory-confirmed UTIs but increased to 85% with provider confirmation. Restriction of the study cohort to patients with a principle diagnosis of UTI improved the PPV for laboratory-confirmed UTI (61.2%) and provider-confirmed UTI (93.2%), as well as the ability to benchmark performance. Other common identification strategies did not markedly affect the PPV.
  
  
  CONCLUSIONS
  ICD-9 codes can be used to identify patients with UTIs but are most accurate when UTI is the principal discharge diagnosis. The identification strategies reported in this study can be used to improve the accuracy and applicability of benchmarking measures.
authors.affiliation: Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 98105-0371, USA. joel.tieder@seattlechildrens.org
authors.forename: Joel S
authors.initials: JS
authors.lastname: Tieder
authors.forename: Matthew
authors.initials: M
authors.lastname: Hall
authors.forename: Katherine A
authors.initials: KA
authors.lastname: Auger
authors.forename: Paul D
authors.initials: PD
authors.lastname: Hain
authors.forename: Karen E
authors.initials: KE
authors.lastname: Jerardi
authors.forename: Angela L
authors.initials: AL
authors.lastname: Myers
authors.forename: Suraiya S
authors.initials: SS
authors.lastname: Rahman
authors.forename: Derek J
authors.initials: DJ
authors.lastname: Williams
authors.forename: Samir S
authors.initials: SS
authors.lastname: Shah
mesh_terms: D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D059019:Clinical Coding / Q000191:economics* / Q000592:standards; D057286:Electronic Health Records / Q000191:economics / Q000592:standards; D005260:Female; D006739:Hospital Administration / Q000191:economics* / Q000592:standards; D017722:Hospital Charges / Q000592:standards; D006760:Hospitalization / Q000191:economics*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D012189:Retrospective Studies; D014552:Urinary Tract Infections / Q000191:economics* / Q000628:therapy*