Ontology highlight
ABSTRACT: Background
Prior suicide attempts are a relatively strong risk factor for future suicide attempts. There is growing interest in using longitudinal electronic health record (EHR) data to derive statistical risk prediction models for future suicide attempts and other suicidal behavior outcomes. However, model performance may be inflated by a largely unrecognized form of "data leakage" during model training: diagnostic codes for suicide attempt outcomes may refer to prior attempts that are also included in the model as predictors.Objective
We aimed to develop an automated rule for determining when documented suicide attempt diagnostic codes identify distinct suicide attempt events.Methods
From a large health care system's EHR, we randomly sampled suicide attempt codes
SUBMITTER: Bentley KH
PROVIDER: S-EPMC10804255 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature