title: Patients with diagnosed diabetes mellitus can be accurately identified in an Indian Health Service patient registration database.
abstract: OBJECTIVE
  The computerized patient registration databases maintained by the Indian Health Service (IHS) represent a potentially important source of data about the epidemic of diabetes among American Indian and Alaskan Native people. The purpose of this study is to determine the accuracy of this data source, and to identify the optimal search criteria to identify patients with a diagnosis of diabetes in an IHS patient registration database.
  
  
  METHODS
  The authors compared the results of a series of computerized searches to a "gold standard" sample of 465 manually reviewed charts from a large IHS facility.
  
  
  RESULTS
  Among patients ages 15 years and older, the best criterion for identifying patients diagnosed with diabetes was the presence of at least one purpose of visit narrative identified by a 250.00 to 250.93 ICD-9 code. The presence of a single computerized code for diabetes identified patients with diagnosed diabetes with a sensitivity of 92% (95% confidence interval [CI] 81, 97), a specificity of 99% (95% CI 98, 99), and a calculated positive predictive value of 94% (95% CI 85, 99). In a separate chart review of 462 charts of patients who had at least one 250.00 to 250.93 ICD-9 code recorded in the database, 435 had a diagnosis of diabetes for an observed positive predictive value of 94%. Because the prevalence of diabetes varies by age of the patient, the positive predictive value of the ability to identify patients with diabetes also varies by age.
  
  
  CONCLUSIONS
  A computerized search of an IHS patient database can identify patients with a diagnosis of diabetes with an accuracy that is similar to the reported accuracy from other health care system databases.
authors.affiliation: Diabetes Center of Excellence, Phoenix Indian Medical Center, Phoenix, AZ 85016, USA. charlton.wilson@pimc.ihs.gov
authors.forename: C
authors.initials: C
authors.lastname: Wilson
authors.forename: L
authors.initials: L
authors.lastname: Susan
authors.forename: A
authors.initials: A
authors.lastname: Lynch
authors.forename: R
authors.initials: R
authors.lastname: Saria
authors.forename: D
authors.initials: D
authors.lastname: Peterson
mesh_terms: D000043:Abstracting and Indexing / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D001130:Arizona / Q000453:epidemiology; D016208:Databases, Factual / Q000592:standards*; D003920:Diabetes Mellitus / Q000175:diagnosis* / Q000453:epidemiology*; D003953:Diagnosis-Related Groups / Q000145:classification / Q000706:statistics & numerical data; D006302:Health Services Research; D006801:Humans; D007198:Indians, North American / Q000706:statistics & numerical data*; D016247:Information Storage and Retrieval / Q000379:methods / Q000592:standards; D016347:Medical Records Systems, Computerized / Q000592:standards; D011159:Population Surveillance / Q000379:methods*; D012042:Registries / Q000592:standards*; D012680:Sensitivity and Specificity; D014481:United States; D016549:United States Indian Health Service / Q000706:statistics & numerical data*