289679
Improving measures of AI/an mortality and cancer incidence through data linkages
Methods: Data from the linkage of IHS registration records with all NPCR/SEER cancer registry records (variable years) and linkage with death certificate data from 1990 to 2008 in the National Death Index (NDI) were used to improve race classification.
Results: Cancer registry records revealed 106,033 AI/AN cases over the time period. Matching IHS records with cancer registry records indicated 21,273 additional cases coded by the registry as non-AI/AN to bring the total AI/AN cancer cases to 127,306, a misclassification (underreporting) rate of 17.1%. Similarly NDI records indicated 217,391 AI/AN deaths over the 19-year period. When IHS database was matched against 44,660,888 death records from NDI. Of these, 33,287 did not have AI/AN race recoded on the death certificate to bring the total AI/AN deaths to 250,678; a misclassification rate of 13.3%.
Conclusions: Routine linkages of death records and cancer registry records with IHS data improve data quality and allow more accurate descriptions of mortality patterns and cancer incidence in AI/AN populations.
Program planning
Learning Objectives:
Describe the problem of race mis-classification for AI/AN in 2 key public health databases
Discuss methods for addressing race mis-classification for AI/AN in mortality and cancer data.
Keywords: Mortality, American Indians
Qualified on the content I am responsible for because: I am the principal analyst for the data being presented and have intimate knowledge of the problem of race misclassification being addressed
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.