Portability of natural language processing methods to detect suicidality from clinical text in US and UK electronic health records.

ABSTRACT:

Background

In the global effort to prevent death by suicide, many academic medical institutions are implementing natural language processing (NLP) approaches to detect suicidality from unstructured clinical text in electronic health records (EHRs), with the hope of targeting timely, preventative interventions to individuals most at risk of suicide. Despite the international need, the development of these NLP approaches in EHRs has been largely local and not shared across healthcare systems.

Methods

In this study, we developed a process to share NLP approaches that were individually developed at King's College London (KCL), UK and Weill Cornell Medicine (WCM), US - two academic medical centers based in different countries with vastly different healthcare systems. We tested an

SUBMITTER: Cusick M 

PROVIDER: S-EPMC9835770 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature