Evaluation of Electronic Health Record-Based Suicide Risk Prediction Models on Contemporary Data.

ABSTRACT:

Background

Suicide risk prediction models have been developed by using information from patients' electronic health records (EHR), but the time elapsed between model development and health system implementation is often substantial. Temporal changes in health systems and EHR coding practices necessitate the evaluation of such models in more contemporary data.

Objectives

A set of published suicide risk prediction models developed by using EHR data from 2009 to 2015 across seven health systems reported c-statistics of 0.85 for suicide attempt and 0.83 to 0.86 for suicide death. Our objective was to evaluate these models' performance with contemporary data (2014-2017) from these systems.

Methods

We evaluated performance using mental health visits (6,832,439 to mental hea

SUBMITTER: Walker RL 

PROVIDER: S-EPMC8373461 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature