title: Diagnosis clusters for emergency medicine.
abstract: OBJECTIVE
  Aggregated emergency department (ED) data are useful for research, ED operations, and public health surveillance. Diagnosis data are widely available as The International Classification of Diseases, version, 9, Clinical Modification (ICD-9-CM) codes; however, there are over 24,000 ICD-9-CM code-descriptor pairs. Standardized groupings (clusters) of ICD-9-CM codes have been developed by other disciplines, including family medicine (FM), internal medicine (IM), inpatient care (Agency for Healthcare Research and Quality [AHRQ]), and vital statistics (NCHS). The purpose of this study was to evaluate the coverage of four existing ICD-9-CM cluster systems for emergency medicine.
  
  
  METHODS
  In this descriptive study, four cluster systems were used to group ICD-9-CM final diagnosis data from a southeastern university tertiary referral center. Included were diagnoses for all ED visits in July 2000 and January 2001. In the comparative analysis, the authors determined the coverage in the four cluster systems, defined as the proportion of final diagnosis codes that were placed into clusters and the frequencies of diagnosis codes in each cluster.
  
  
  RESULTS
  The final sample included 7,543 visits with 19,530 diagnoses. Coverage of the ICD-9-CM codes in the ED sample was: AHRQ, 99%; NCHS, 88%; FM, 71%; IM, 68%. Seventy-six percent of the AHRQ clusters were small, defined as grouping <1% of the diagnosis codes in the sample.
  
  
  CONCLUSIONS
  The AHRQ system provided the best coverage of ED ICD-9-CM codes. However, most of the clusters were small and not significantly different from the raw data.
authors.affiliation: Department of Emergency Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599-7594, USA. dtravers@med.unc.edu
authors.forename: Debbie A
authors.initials: DA
authors.lastname: Travers
authors.forename: Stephanie W
authors.initials: SW
authors.lastname: Haas
authors.forename: Anna E
authors.initials: AE
authors.lastname: Waller
authors.forename: Judith E
authors.initials: JE
authors.lastname: Tintinalli
mesh_terms: D016000:Cluster Analysis; D003933:Diagnosis; D004635:Emergency Medicine; D004636:Emergency Service, Hospital / Q000145:classification*; D006801:Humans; D038801:International Classification of Diseases / Q000145:classification