Background:

Establishing trends of drug overdoses requires the identification of individual drugs in death certificates, not supported by coding with the International Classification of Diseases. However, identifying drug mentions from the literal portion of death certificates remains challenging due to the variability of drug names. Objectives:

To automatically identify individual drugs in death certificates. Methods:

We use RxNorm to collect variants for drug names (generic names, synonyms, brand names) and we algorithmically generate common misspellings. We use this automatically compiled list to identify drug mentions from 703,106 death certificates and compare the performance of our automated approach to that of a manually curated list of drug names. Results:

Our automated approach shows a slight loss in recall (4.3%) compared to the manual approach (for individual drugs), due in part to acronyms. Conclusions:

Maintenance of a manually curated list of drugs is not sustainable and our approach offers a viable alternative.