Development and Validation of Machine Models Using Natural Language Processing to Classify Substances Involved in Overdose Deaths

Source:

Goodman-Meza D, Shover CL, Medina JA, Tang AB, Shoptaw S, Bui AAT. Development and Validation of Machine Models Using Natural Language Processing to Classify Substances Involved in Overdose Deaths. JAMA Netw Open. 2022;5(8):e2225593. doi:10.1001/jamanetworkopen.2022.25593

Key Points

Question  What is the most accurate machine learning and natural language processing model to identify substances related to overdose deaths in medical examiner data?

Findings  In this diagnostic study of 35 433 death records, machine learning models were able to classify with perfect or near perfect performance deaths related to any opioids, heroin, fentanyl, prescription opioids, methamphetamine, cocaine, and alcohol. Classification of benzodiazepines was suboptimal.

Meaning  In this study, a natural language processing workflow was able to automate identification of substances related to overdose deaths in medical examiner data.