title: Estimating diabetes prevalence in South Auckland: how accurate is a method that combines lists of linked health datasets?
abstract: OBJECTIVE
  To assess the accuracy of a method for estimating adult diabetes prevalence that combines linked, routine health datasets in South Auckland, New Zealand.
  
  
  METHODS
  We used a simple algorithm that combined records of laboratory testing, drug dispensing and hospital diagnoses applied to National Health Index-linked health data in South Auckland to estimate the prevalence of diabetes in 2007. We investigated the sensitivity of this 'combined list' algorithm against a gold standard of individuals with diagnosed diabetes enrolled in a Chronic Care Management programme (CCMP). We also assessed the sensitivity of this algorithm against an estimated diabetes population generated using capture-recapture methods.
  
  
  RESULTS
  From the combined-list algorithm, 25,797 (7.2%) South Aucklanders aged 15 years and over had diabetes. During this period, 10,725 patients were enrolled in the CCMP. The combined list algorithm correctly identified (sensitivity) 10,351/10,725 (96.5%) of those enrolled. When we used the capture-recapture estimated diabetes population as an alternative gold standard, 34,418 [9.5%] of South Aucklanders 15 years and over had diabetes, with the sensitivity of the combined list method falling to about 75% (25,797/34,418).
  
  
  CONCLUSIONS
  Linked health data provide reasonably accurate estimates of diabetes prevalence in a New Zealand population; particularly for cases with longstanding or complicated disease.
authors.affiliation: Section of Epidemiology and Biostatistics, School of Population Health, Tamaki Campus, University of Auckland, Auckland, New Zealand. s.thornley@auckland.ac.nz
authors.forename: Simon
authors.initials: S
authors.lastname: Thornley
authors.forename: Roger
authors.initials: R
authors.lastname: Marshall
authors.forename: Gary
authors.initials: G
authors.lastname: Jackson
authors.forename: James
authors.initials: J
authors.lastname: Smith
authors.forename: Wing-Cheuk
authors.initials: WC
authors.lastname: Chan
authors.forename: Craig
authors.initials: C
authors.lastname: Wright
authors.forename: Dudley
authors.initials: D
authors.lastname: Gentles
authors.forename: Rod
authors.initials: R
authors.lastname: Jackson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D016208:Databases, Factual; D003920:Diabetes Mellitus / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology*; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D008875:Middle Aged; D009520:New Zealand / Q000453:epidemiology; D015995:Prevalence; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult
chemical_list: D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; C517652:hemoglobin A1c protein, human