Literature DB >> 23068882

Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse.

James Hunter1, Yvonne Freer, Albert Gatt, Ehud Reiter, Somayajulu Sripada, Cindy Sykes.   

Abstract

INTRODUCTION: Our objective was to determine whether and how a computer system could automatically generate helpful natural language nursing shift summaries solely from an electronic patient record system, in a neonatal intensive care unit (NICU).
METHODS: A system was developed which automatically generates partial NICU shift summaries (for the respiratory and cardiovascular systems), using data-to-text technology. It was evaluated for 2 months in the NICU at the Royal Infirmary of Edinburgh, under supervision.
RESULTS: In an on-ward evaluation, a substantial majority of the summaries was found by outgoing and incoming nurses to be understandable (90%), and a majority was found to be accurate (70%), and helpful (59%). The evaluation also served to identify some outstanding issues, especially with regard to extra content the nurses wanted to see in the computer-generated summaries.
CONCLUSIONS: It is technically possible automatically to generate limited natural language NICU shift summaries from an electronic patient record. However, it proved difficult to handle electronic data that was intended primarily for display to the medical staff, and considerable engineering effort would be required to create a deployable system from our proof-of-concept software.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Mesh:

Year:  2012        PMID: 23068882     DOI: 10.1016/j.artmed.2012.09.002

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  6 in total

1.  Electronic health records and transgender patients--practical recommendations for the collection of gender identity data.

Authors:  Madeline B Deutsch; David Buchholz
Journal:  J Gen Intern Med       Date:  2015-01-06       Impact factor: 5.128

2.  Data-to-text summarisation of patient records: using computer-generated summaries to access patient histories.

Authors:  Donia Scott; Catalina Hallett; Rachel Fettiplace
Journal:  Patient Educ Couns       Date:  2013-06-05

Review 3.  Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges.

Authors:  Hadi Banaee; Mobyen Uddin Ahmed; Amy Loutfi
Journal:  Sensors (Basel)       Date:  2013-12-17       Impact factor: 3.576

4.  Effects of Individual Differences in Working Memory on Plan Presentational Choices.

Authors:  Nava Tintarev; Judith Masthoff
Journal:  Front Psychol       Date:  2016-11-16

5.  Natural language generation for electronic health records.

Authors:  Scott H Lee
Journal:  NPJ Digit Med       Date:  2018-11-19

6.  Deep Multi-Objective Learning from Low-Dose CT for Automatic Lung-RADS Report Generation.

Authors:  Yung-Chun Chang; Yan-Chun Hsing; Yu-Wen Chiu; Cho-Chiang Shih; Jun-Hong Lin; Shih-Hsin Hsiao; Koji Sakai; Kai-Hsiung Ko; Cheng-Yu Chen
Journal:  J Pers Med       Date:  2022-03-08
  6 in total

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