Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Study

作者：Zhong Victor W; Pfaff Emily R; Beavers Daniel P; Thomas Joan; Jaacks Lindsay M; Bowlby Deborah A; Carey Timothy S; Lawrence Jean M; Dabelea Dana; Hamman Richard F; Pihoker Catherine; Saydah Sharon H; Mayer Davis Elizabeth J^*

来源：Pediatric Diabetes, 2014, 15(8): 573-584.

DOI：10.1111/pedi.12152

• administrative data
• case ascertainment
• childhood diabetes
• electronic health record
• type classification

BackgroundThe performance of automated algorithms for childhood diabetes case ascertainment and type classification may differ by demographic characteristics. %26lt;br%26gt;ObjectiveThis study evaluated the potential of administrative and electronic health record (EHR) data from a large academic care delivery system to conduct diabetes case ascertainment in youth according to type, age, and race/ethnicity. %26lt;br%26gt;SubjectsOf 57767 children aged %26lt;20yr as of 31 December 2011 seen at University of North Carolina Health Care System in 2011 were included. %26lt;br%26gt;MethodsUsing an initial algorithm including billing data, patient problem lists, laboratory test results, and diabetes related medications between 1 July 2008 and 31 December 2011, presumptive cases were identified and validated by chart review. More refined algorithms were evaluated by type (type 1 vs. type 2), age (%26lt;10 vs. 10yr) and race/ethnicity (non-Hispanic White vs. other%26apos;). Sensitivity, specificity, and positive predictive value were calculated and compared. %26lt;br%26gt;ResultsThe best algorithm for ascertainment of overall diabetes cases was billing data. The best type 1 algorithm was the ratio of the number of type 1 billing codes to the sum of type 1 and type 2 billing codes 0.5. A useful algorithm to ascertain youth with type 2 diabetes with other%26apos; race/ethnicity was identified. Considerable age and racial/ethnic differences were present in type-non-specific and type 2 algorithms. %26lt;br%26gt;ConclusionsAdministrative and EHR data may be used to identify cases of childhood diabetes (any type), and to identify type 1 cases. The performance of type 2 case ascertainment algorithms differed substantially by race/ethnicity.

• 出版日期2014-12