MSR37 Methods for Recovering Missing Longitudinal Biomarker Values from Electronic Health Record Data

Abstract

Longitudinal biomarker values in EHR data measure patient health and are typically correlated with important adverse events. These data can be valuable in healthcare research (e.g. risk prediction) but are often subject to a high degree of missingness. We develop an imputation approach that leverages and preserves the relationship of the biomarker with adverse events. We demonstrate our approach using carcinoembryonic antigen (CEA) biomarker values in the setting of colorectal cancer (CRC) surveillance, where elevated CEA is associated with recurrence.