Using Electronically Archived Medical Information for Public Health: Analysis of American Indian/Alaska Native Communicable Disease Diagnoses from the Indian Health Service National Data Warehouse — Oregon 2007–2011

Marcinkevage, Jessica

INTRODUCTION: American Indian/Alaska Native (AI/AN) communities experience disproportionate disease burdens. No system provides aggregate health or disease surveillance data of Oregon AI/AN communities to tribal public health authorities; state health department data are inaccessible to these organizations, and national surveys are not representative of AI/AN populations. We evaluated performance of the Indian Health Service (IHS) National Data Warehouse (NDW), an electronic repository of clinical data from IHS, tribal, and urban Indian (I/T/U) clinics, for surveillance of 6 communicable diseases: hepatitis A, B, and C; gonorrhea; chlamydia; and pertussis.

METHODS: We determined the number of Oregon AI/AN persons in the NDW having a diagnosis of each condition during 2007-2011, according to International Classification of Diseases, 9^thRev., (ICD-9) codes. To validate results, we compared these diagnoses with laboratory-confirmed cases identified through medical records review of the 2 largest IHS/Tribal clinics in Oregon, calculating NDW sensitivity and predictive value positive (PVP). We also compared NDW case counts with counts of AI/AN persons in the Oregon notifiable diseases system (NDS) for each condition.

RESULTS: Eleven Oregon I/T/U clinics reported to the NDW at least once during 2007–2011. Of 621 diagnoses identified at the 2 clinics, 3 (0.5%) were absent from the NDW. Sensitivity was higher for sexually transmitted infections than other conditions (e.g., chlamydia: 67%; hepatitis B: 12%); the opposite was observed for PVP (hepatitis B: 50%; chlamydia: 17%). Compared with Oregon NDS, diagnoses missed by the NDW were among younger AI/AN persons and those living in urban counties.

CONCLUSIONS: The NDW can be useful for AI/AN-specific public health surveillance for detecting trends in reportable communicable diseases, guiding development of future AI/AN-specific public health surveillance systems.