Data integration of structured and unstructured sources for assigning clinical codes to patient stays.
Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation.
Author(s): Scheurwegs, Elyne, Luyckx, Kim, Luyten, Léon, Daelemans, Walter, Van den Bulcke, Tim
DOI: 10.1093/jamia/ocv115