Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

ABSTRACT:

Background

Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding. Autopsy reports contain narrative text describing scene evidence and medical history (similar to preliminary death scene investigation reports) and may serve as early data sources for identifying fatal drug overdoses. To facilitate timely fatal overdose reporting, natural language processing was applied to narrative texts from autopsies.

Objective

This study aimed to develop a natural language processing-based model that predicts the likelihood that an autopsy report narrative describes an accidental or undetermined fatal drug overdose.

Methods

Autopsy reports of all manners of death (2019-2021) were obtained from the T

SUBMITTER: Tang LA 

PROVIDER: S-EPMC10238956 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature