What health records data are required for accurate prediction of suicidal behavior?

ABSTRACT:

Objective

The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.

Materials and methods

Records from 7 large health systems identified 19 061 056 outpatient visits to mental health specialty or general medical providers between 2009 and 2015. Machine learning models (logistic regression with penalized LASSO [least absolute shrinkage and selection operator] variable selection) were developed to predict suicide death (n = 1240) or probable suicide attempt (n = 24 133) in the following 90 days. Base models were used only historical insurance claims data and were then augmented with data regarding sociodemographic characteristics (race, ethnicity, and neighborhood charact

SUBMITTER: Simon GE 

PROVIDER: S-EPMC6857508 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature