title: Mining rich health data from Canadian physician claims: features and face validity.
abstract: BACKGROUND
  Physician claims data are one of the largest sources of coded health information unique to Canada. There is skepticism from data users about the quality of this data. This study investigated features of diagnostic codes used in the Alberta physician claims database.
  
  
  METHODS
  Alberta physician claims from January 1 to March 31, 2011 are analyzed. Claims contain coded diagnoses using the International Classification of Diseases, 9th revision (ICD-9), procedures, physician specialty and service-fee type. Descriptive statistics examined the diversity and frequency of unique ICD-9 diagnostic codes used and the level of code extension (e.g. 3- or 4-digit coding).
  
  
  RESULTS
  A total of 7,441,005 claims by 6,601 physicians were analyzed. The average number of claims per physician was 1,079, with ranges between 1,330 for family medicine, 690 for internal medicine, 722 for surgery, 516 for pediatrics and 409 for neurology. Family physicians used an average of 121 diagnostic codes, internal medicine physicians 32, surgery 36, pediatrics 46 and neurology 27. Overall, 43.5% of claims had a more detailed diagnosis (ICD code with >3 digits). Physicians on a fee-for-service plan submitted 1,184 claims and used 88 unique diagnosis codes on average compared to 438 claims and 44 unique diagnosis codes from physicians on an alternative payment plan (APP).
  
  
  CONCLUSIONS
  Face validity of diagnosis coded in physician claims is substantially high and the features of diagnosis codes seem to reasonably reflect the clinical specialty. Physicians submit a diverse array of ICD 9 diagnostic codes and nearly half of the ICD-9 diagnostic codes examined were more detailed than required (i.e. ICD code with >3 digits). Finally, guidelines and policies should be explored to assess the submission of shadow billings for physicians on APPs.
authors.forename: Ceara Tess
authors.initials: CT
authors.lastname: Cunningham
authors.forename: Pin
authors.initials: P
authors.lastname: Cai
authors.forename: David
authors.initials: D
authors.lastname: Topps
authors.forename: Lawrence W
authors.initials: LW
authors.lastname: Svenson
authors.forename: Nathalie
authors.initials: N
authors.lastname: Jetté
authors.affiliation: Department of Community Health Sciences, University of Calgary, 3280 Hospital Dr, NW, Calgary, Alberta T2N 4Z6, Canada. hquan@ucalgary.ca.
authors.forename: Hude
authors.initials: H
authors.lastname: Quan
mesh_terms: D000416:Alberta; D057225:Data Mining; D007344:Insurance Claim Reporting