BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data

James Hunter, Yvonne Freer, Albert Gatt, Ehud Reiter, Somayajulu Sripada, Cindy Sykes, Dave Westwater

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were also asked for free-text comments about the summaries. The nurses found the majority of the summaries to be understandable, accurate, and helpful (p<0.001 for all measures). However, nurses also pointed out many deficiencies, especially with regard to extra content they wanted to see in the computer-generated summaries. In conclusion, natural language NICU shift summaries can be automatically generated from an electronic patient record, but our proof-of-concept software needs considerable additional development work before it can be deployed.
Original languageEnglish
Pages (from-to)621-624
Number of pages4
JournalJournal of the American Medical Informatics Association
Volume18
Issue number5
DOIs
Publication statusPublished - 1 Sept 2011

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