Cognitive analysis of the summarization of longitudinal patient records

Daniel Reichert, David Kaufman, Benjamin Bloxham, Herbert Chase, Noémie Elhadad

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Electronic health records contain an abundance of valuable information that can be used to guide patient care. However, the large volume of information embodied in these records also renders access to relevant information a time-consuming and inefficient process. Our ultimate objective is to develop an automated summarizer that succinctly captures all relevant information in the patient record. In this paper, we present a cognitive study of 8 clinicians who were asked to create summaries based on data contained in the patients' electronic health record. The study characterized the primary sources of information that were prioritized by clinicians, the temporal strategies used to develop a summary and the cognitive operations used to guide the summarization process. Although we would not expect the automated summarizer to emulate human performance, we anticipate that this study will inform its development in instrumental ways.

Original languageEnglish (US)
Pages (from-to)667-671
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Volume2010
StatePublished - 2010

ASJC Scopus subject areas

  • General Medicine

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