Misleading Results in Posttraumatic Stress Disorder Predictive Models Using Electronic Health Record Data: Algorithm Validation Study.
Ontology highlight
ABSTRACT: Electronic health record (EHR) data are increasingly used in predictive models of posttraumatic stress disorder (PTSD), but it is unknown how multivariable prediction of an EHR-based diagnosis might differ from prediction of a more rigorous diagnostic criterion. This distinction is important because EHR data are subject to multiple biases, including diagnostic misclassification and differential health care use resulting from factors such as illness severity. This study aims to compare predictive models using the same predictors to predict an EHR-based versus semistructured interview-based PTSD diagnostic criterion, quantify model performance discrepancies, and examine potential mechanisms that account for performance differences. We compared the performance of several machine learning mode
SUBMITTER: Crow TM
PROVIDER: S-EPMC12384688 | biostudies-literature | 2025 Aug
REPOSITORIES: biostudies-literature
ACCESS DATA