title: Differentiation of ileostomy from colostomy procedures: assessing the accuracy of current procedural terminology codes and the utility of natural language processing.
abstract: BACKGROUND
  Large databases provide a wealth of information for researchers, but identifying patient cohorts often relies on the use of current procedural terminology (CPT) codes. In particular, studies of stoma surgery have been limited by the accuracy of CPT codes in identifying and differentiating ileostomy procedures from colostomy procedures. It is important to make this distinction because the prevalence of complications associated with stoma formation and reversal differ dramatically between types of stoma. Natural language processing (NLP) is a process that allows text-based searching. The Automated Retrieval Console is an NLP-based software that allows investigators to design and perform NLP-assisted document classification. In this study, we evaluated the role of CPT codes and NLP in differentiating ileostomy from colostomy procedures.
  
  
  METHODS
  Using CPT codes, we conducted a retrospective study that identified all patients undergoing a stoma-related procedure at a single institution between January 2005 and December 2011. All operative reports during this time were reviewed manually to abstract the following variables: formation or reversal and ileostomy or colostomy. Sensitivity and specificity for validation of the CPT codes against the mastery surgery schedule were calculated. Operative reports were evaluated by use of NLP to differentiate ileostomy- from colostomy-related procedures. Sensitivity and specificity for identifying patients with ileostomy or colostomy procedures were calculated for CPT codes and NLP for the entire cohort.
  
  
  RESULTS
  CPT codes performed well in identifying stoma procedures (sensitivity 87.4%, specificity 97.5%). A total of 664 stoma procedures were identified by CPT codes between 2005 and 2011. The CPT codes were adequate in identifying stoma formation (sensitivity 97.7%, specificity 72.4%) and stoma reversal (sensitivity 74.1%, specificity 98.7%), but they were inadequate in identifying ileostomy (sensitivity 35.0%, specificity 88.1%) and colostomy (75.2% and 80.9%). NLP performed with greater sensitivity, specificity, and accuracy than CPT codes in identifying stoma procedures and stoma types. Major differences where NLP outperformed CPT included identifying ileostomy (specificity 95.8%, sensitivity 88.3%, and accuracy 91.5%) and colostomy (97.6%, 90.5%, and 92.8%, respectively).
  
  
  CONCLUSIONS
  CPT codes can identify effectively patients who have had stoma procedures and are adequate in distinguishing between formation and reversal; however, CPT codes cannot differentiate ileostomy from colostomy. NLP can be used to differentiate between ileostomy- and colostomy-related procedures. The role of NLP in conjunction with electronic medical records in data retrieval warrants further investigation.
authors.affiliation: Michael E. DeBakey Department of Surgery, Michael E. DeBakey VA Medical Center, Baylor College of Medicine, Houston, TX 77030, USA.
authors.forename: Elaine
authors.initials: E
authors.lastname: Vo
authors.forename: Jessica A
authors.initials: JA
authors.lastname: Davila
authors.forename: Jason
authors.initials: J
authors.lastname: Hou
authors.forename: Krystle
authors.initials: K
authors.lastname: Hodge
authors.forename: Linda T
authors.initials: LT
authors.lastname: Li
authors.forename: James W
authors.initials: JW
authors.lastname: Suliburk
authors.forename: Lillian S
authors.initials: LS
authors.lastname: Kao
authors.forename: David H
authors.initials: DH
authors.lastname: Berger
authors.forename: Mike K
authors.initials: MK
authors.lastname: Liang
mesh_terms: D000465:Algorithms; D003125:Colostomy / Q000379:methods*; D006801:Humans; D007081:Ileostomy / Q000379:methods*; D009323:Natural Language Processing; D009626:Terminology as Topic