Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse. Hunter, J., Freer, Y., Gatt, A., Reiter, E., Sripada, S., & Sykes, C. Artificial Intelligence in Medicine, 56(3):157–172, November, 2012. ![Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{hunter_automatic_2012,
title = {Automatic generation of natural language nursing shift summaries in neonatal intensive care: {BT}-{Nurse}},
volume = {56},
issn = {0933-3657},
shorttitle = {Automatic generation of natural language nursing shift summaries in neonatal intensive care},
url = {https://www.sciencedirect.com/science/article/pii/S0933365712001170},
doi = {10.1016/j.artmed.2012.09.002},
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.},
number = {3},
urldate = {2023-08-15},
journal = {Artificial Intelligence in Medicine},
author = {Hunter, James and Freer, Yvonne and Gatt, Albert and Reiter, Ehud and Sripada, Somayajulu and Sykes, Cindy},
month = nov,
year = {2012},
keywords = {Data to text, Health informatics, Natural language generation, Natural language processing, Neonatal intensive care, notion},
pages = {157--172},
}
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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.","number":"3","urldate":"2023-08-15","journal":"Artificial Intelligence in Medicine","author":[{"propositions":[],"lastnames":["Hunter"],"firstnames":["James"],"suffixes":[]},{"propositions":[],"lastnames":["Freer"],"firstnames":["Yvonne"],"suffixes":[]},{"propositions":[],"lastnames":["Gatt"],"firstnames":["Albert"],"suffixes":[]},{"propositions":[],"lastnames":["Reiter"],"firstnames":["Ehud"],"suffixes":[]},{"propositions":[],"lastnames":["Sripada"],"firstnames":["Somayajulu"],"suffixes":[]},{"propositions":[],"lastnames":["Sykes"],"firstnames":["Cindy"],"suffixes":[]}],"month":"November","year":"2012","keywords":"Data to text, Health informatics, Natural language generation, Natural language processing, Neonatal intensive care, notion","pages":"157–172","bibtex":"@article{hunter_automatic_2012,\n\ttitle = {Automatic generation of natural language nursing shift summaries in neonatal intensive care: {BT}-{Nurse}},\n\tvolume = {56},\n\tissn = {0933-3657},\n\tshorttitle = {Automatic generation of natural language nursing shift summaries in neonatal intensive care},\n\turl = {https://www.sciencedirect.com/science/article/pii/S0933365712001170},\n\tdoi = {10.1016/j.artmed.2012.09.002},\n\tabstract = {Introduction\nOur 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).\nMethods\nA 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.\nResults\nIn 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.\nConclusions\nIt is technically possible automatically to generate limited natural language NICU shift summaries from an electronic patient record. 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