title: Applying Classification Trees to Hospital Administrative Data to Identify Patients with Lower Gastrointestinal Bleeding.
abstract: BACKGROUND
  Lower gastrointestinal bleeding (LGIB) is a common cause of acute hospitalization. Currently, there is no accepted standard for identifying patients with LGIB in hospital administrative data. The objective of this study was to develop and validate a set of classification algorithms that use hospital administrative data to identify LGIB.
  
  
  METHODS
  Our sample consists of patients admitted between July 1, 2001 and June 30, 2003 (derivation cohort) and July 1, 2003 and June 30, 2005 (validation cohort) to the general medicine inpatient service of the University of Chicago Hospital, a large urban academic medical center. Confirmed cases of LGIB in both cohorts were determined by reviewing the charts of those patients who had at least 1 of 36 principal or secondary International Classification of Diseases, Ninth revision, Clinical Modification (ICD-9-CM) diagnosis codes associated with LGIB. Classification trees were used on the data of the derivation cohort to develop a set of decision rules for identifying patients with LGIB. These rules were then applied to the validation cohort to assess their performance.
  
  
  RESULTS
  Three classification algorithms were identified and validated: a high specificity rule with 80.1% sensitivity and 95.8% specificity, a rule that balances sensitivity and specificity (87.8% sensitivity, 90.9% specificity), and a high sensitivity rule with 100% sensitivity and 91.0% specificity.
  
  
  CONCLUSIONS
  These classification algorithms can be used in future studies to evaluate resource utilization and assess outcomes associated with LGIB without the use of chart review.
authors.affiliation: Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.
authors.forename: Juned
authors.initials: J
authors.lastname: Siddique
authors.affiliation: Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Ruhnke
authors.affiliation: Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Andrea
authors.initials: A
authors.lastname: Flores
authors.affiliation: Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Micah T
authors.initials: MT
authors.lastname: Prochaska
authors.affiliation: Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Paesch
authors.affiliation: Department of Medicine, University of Chicago, Chicago, Illinois, United States of America.
authors.forename: David O
authors.initials: DO
authors.lastname: Meltzer
authors.affiliation: Department of Medicine, Loyola University Stritch School of Medicine, Maywood, Illinois, United States of America.
authors.forename: Chad T
authors.initials: CT
authors.lastname: Whelan
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D002641:Chicago; D005260:Female; D006471:Gastrointestinal Hemorrhage / Q000175:diagnosis*; D006760:Hospitalization; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D012680:Sensitivity and Specificity