ArXiv Preprint
Brief Hospital Course (BHC) summaries are succinct summaries of an entire
hospital encounter, embedded within discharge summaries, written by senior
clinicians responsible for the overall care of a patient. Methods to
automatically produce summaries from inpatient documentation would be
invaluable in reducing clinician manual burden of summarising documents under
high time-pressure to admit and discharge patients. Automatically producing
these summaries from the inpatient course, is a complex, multi-document
summarisation task, as source notes are written from various perspectives (e.g.
nursing, doctor, radiology), during the course of the hospitalisation. We
demonstrate a range of methods for BHC summarisation demonstrating the
performance of deep learning summarisation models across extractive and
abstractive summarisation scenarios. We also test a novel ensemble extractive
and abstractive summarisation model that incorporates a medical concept
ontology (SNOMED) as a clinical guidance signal and shows superior performance
in 2 real-world clinical data sets.
Thomas Searle, Zina Ibrahim, James Teo, Richard Dobson
2022-11-14
