Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review.
Canan C, Polinski JM, Alexander C, et al. Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review. J Am Med Inform Assoc. 2017;24(6):1204-1210. doi:10.1093/jamia/ocx066.
Safer opioid prescribing requires that providers and systems are able to identify patients who misuse or divert opioids. This systematic review assessed different automated algorithms to detect population-level nonmedical opioid use. The authors suggest that algorithms that integrate claims data with natural language processing or other advanced informatics techniques yield the best results.
Canan C, Polinski JM, Alexander C, et al. Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review. J Am Med Inform Assoc. 2017;24(6):1204-1210. doi:10.1093/jamia/ocx066.