mlsanityData to 7 Oct 2026

Is In-hospital Meta-information Useful for Abstractive Discharge Summary Generation?

arXiv 2303.06002 ↗First posted 10 Mar 2023cs.CLcited by 0

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Abstract (arXiv)

During the patient's hospitalization, the physician must record daily observations of the patient and summarize them into a brief document called "discharge summary" when the patient is discharged. Automated generation of discharge summary can greatly relieve the physicians' burden, and has been addressed recently in the research community. Most previous studies of discharge summary generation using the sequence-to-sequence architecture focus on only inpatient notes for input. However, electric health records (EHR) also have rich structured metadata (e.g., hospital, physician, disease, length of stay, etc.) that might be useful. This paper investigates the effectiveness of medical meta-information for summarization tasks. We obtain four types of meta-information from the EHR systems and encode each meta-information into a sequence-to-sequence model. Using Japanese EHRs, meta-information encoded models increased ROUGE-1 by up to 4.45 points and BERTScore by 3.77 points over the vanilla Longformer. Also, we found that the encoded meta-information improves the precisions of its related terms in the outputs. Our results showed the benefit of the use of medical meta-information.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 21 of its 38 references that are in the map. First posted on arXiv 10 Mar 2023.

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21 of 38 references.

References · 21

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9 more
  1. 2021What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarizationcited by 35
  2. 2019Ontology-Aware Clinical Abstractive Summarizationcited by 33
  3. 2018Patient2Vec: A Personalized Interpretable Deep Representation of the Longitudinal Electronic Health Recordcited by 30
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  5. 2020Reducing Quantity Hallucinations in Abstractive Summarizationcited by 22
  6. 2021Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notescited by 18
  7. 2018Extractive Summarization of EHR Discharge Notescited by 12
  8. 2018Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Recordscited by 6
  9. 2022Exploring Optimal Granularity for Extractive Summarization of Unstructured Health Records: Analysis of the Largest Multi-Institutional Archive of Health Records in Japancited by 3

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