title: Validity of administrative coding in identifying patients with upper urinary tract calculi.
abstract: OBJECTIVE
  Administrative databases are increasingly used for epidemiological investigations. We performed a study to assess the validity of ICD-9 codes for upper urinary tract stone disease in an administrative database.
  
  
  METHODS
  We retrieved the records of all inpatients and outpatients at Johns Hopkins Hospital between November 2007 and October 2008 with an ICD-9 code of 592, 592.0, 592.1 or 592.9 as one of the first 3 diagnosis codes. A random number generator selected 100 encounters for further review. We considered a patient to have a true diagnosis of an upper tract stone if the medical records specifically referenced a kidney stone event, or included current or past treatment for a kidney stone. Descriptive and comparative analyses were performed.
  
  
  RESULTS
  A total of 8,245 encounters coded as upper tract calculus were identified and 100 were randomly selected for review. Two patients could not be identified within the electronic medical record and were excluded from the study. The positive predictive value of using all ICD-9 codes for an upper tract calculus (592, 592.0, 592.1) to identify subjects with renal or ureteral stones was 95.9%. For 592.0 only the positive predictive value was 85%. However, although the positive predictive value for 592.1 only was 100%, 26 subjects (76%) with a ureteral stone were not appropriately billed with this code.
  
  
  CONCLUSIONS
  ICD-9 coding for urinary calculi is likely to be sufficiently valid to be useful in studies using administrative data to analyze stone disease. However, ICD-9 coding is not a reliable means to distinguish between subjects with renal and ureteral calculi.
authors.affiliation: James Buchanan Brady Urological Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA.
authors.forename: Michelle J
authors.initials: MJ
authors.lastname: Semins
authors.forename: Bruce J
authors.initials: BJ
authors.lastname: Trock
authors.forename: Brian R
authors.initials: BR
authors.lastname: Matlaga
mesh_terms: D015142:Baltimore / Q000453:epidemiology; D016208:Databases, Factual; D057286:Electronic Health Records; D006801:Humans; D038801:International Classification of Diseases; D011237:Predictive Value of Tests; D014514:Ureteral Calculi / Q000145:classification / Q000453:epidemiology; D014545:Urinary Calculi / Q000145:classification* / Q000453:epidemiology