title: The impact of ICD-9-CM code rank order on the estimated prevalence of Clostridium difficile infections.
abstract: BACKGROUND
  US estimates of the Clostridium difficile infection (CDI) burden have utilized International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Whether ICD-9-CM code rank order affects CDI prevalence estimates is important because the National Hospital Discharge Survey (NHDS) and the Nationwide Inpatient Sample (NIS) have varying limits on the number of ICD-9-CM codes collected.
  
  
  METHODS
  ICD-9-CM codes for CDI (008.45), C. difficile toxin assay results, and dates of admission and discharge were collected from electronic hospital databases for adult patients admitted to 4 hospitals in the United States from July 2000 through June 2006. CDI prevalence per 1000 discharges was calculated and compared for NHDS and NIS limits and toxin assay results from the same hospitals. CDI prevalence estimates were compared using the χ(2) test, and the test of equality was used to compare slopes.
  
  
  RESULTS
  CDI prevalence measured by NIS criteria was significantly higher than that measured using NHDS criteria (10.7 cases per 1000 discharges versus 9.4 cases per 1000 discharges; P<.001) in the 4 hospitals. CDI prevalence measured by toxin assay results was 9.4 cases per 1000 discharges (P=.57 versus NHDS). However, the CDI prevalence increased more rapidly over time when measured according to the NHDS criteria than when measured according to toxin assay results (β=1.09 versus 0.84; P=.008).
  
  
  CONCLUSIONS
  Compared with the NHDS definition, the NIS definition captured 12% more CDI cases and reported significantly higher CDI rates. Rates calculated using toxin assay results were not different from rates calculated using NHDS criteria, but CDI prevalence appeared to increase more rapidly when measured by NHDS criteria than when measured by toxin assay results.
authors.affiliation: Department of Medicine, Washington University School of Medicine, St Louis, Missouri 63110, USA. edubberk@im.wustl.edu
authors.forename: Erik R
authors.initials: ER
authors.lastname: Dubberke
authors.forename: Anne M
authors.initials: AM
authors.lastname: Butler
authors.forename: Humaa A
authors.initials: HA
authors.lastname: Nyazee
authors.forename: Kimberly A
authors.initials: KA
authors.lastname: Reske
authors.forename: Deborah S
authors.initials: DS
authors.lastname: Yokoe
authors.forename: Jeanmarie
authors.initials: J
authors.lastname: Mayer
authors.forename: Julie E
authors.initials: JE
authors.lastname: Mangino
authors.forename: Yosef M
authors.initials: YM
authors.lastname: Khan
authors.forename: Victoria J
authors.initials: VJ
authors.lastname: Fraser
mesh_terms: D001427:Bacterial Toxins; D016009:Chi-Square Distribution; D016360:Clostridioides difficile / Q000302:isolation & purification*; D003015:Clostridium Infections / Q000145:classification / Q000175:diagnosis* / Q000453:epidemiology*; D003430:Cross-Sectional Studies; D003601:Cytotoxicity Tests, Immunologic; D004797:Enzyme-Linked Immunosorbent Assay; D019538:Health Care Surveys; D006801:Humans; D038801:International Classification of Diseases; D015995:Prevalence; D014481:United States / Q000453:epidemiology
chemical_list: D001427:Bacterial Toxins