The use of automated data to identify complications and comorbidities of diabetes: A validation study

We evaluated the accuracy of administrative data for identifying complicati ons and comorbidities of diabetes using International Classification of Dis eases, 9th edition, Clinical Modification and Current Procedural Terminolog y codes. The records of 471 randomly selected diabetic patients were review ed for complications from January 1, 1993 to December 31, 1995; chart data served to validate automated data. The complications with the highest sensi tivity determined by a diagnosis in the medical records identified within /-60 days of the database date were myocardial infarction (95.2%); amputati on (94.4%); ischemic heart disease (90.3%); stroke (91.2%); osteomyelitis ( 79.2%); and retinal detachment, vitreous hemorrhage, and vitrectomy (73.5%) . With the exception of amputation (82.9%), positive predictive value was l ow when based on a diagnosis identified within +/-60 days of the database d are but increased with relaxation of the time constraints to include confir mation of the condition at any time during 1993-1995: ulcers (88.5%); amput ation (85.4%); and retinal detachment, vitreous hemorrhage and vitrectomy ( 79.8%). Automated data are useful for ascertaining potential cases of some diabetic complications but require confirmatory evidence when they are to b e used for research purposes. J CLIN EPIDEMIOL 52;3:199-207, 1999. (C) Else vier Science Inc.