Predicting ICU transfers using text messages between nurses and doctors

Faiza Khan Khattak; Chloé Pou-Prom; Robert Wu; Frank Rudzicz

doi:10.18653/v1/W19-1911

Predicting ICU transfers using text messages between nurses and doctors

Faiza Khan Khattak, Chloé Pou-Prom, Robert Wu, Frank Rudzicz

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Abstract

We explore the use of real-time clinical information, i.e., text messages sent between nurses and doctors regarding patient conditions in order to predict transfer to the intensive care unit(ICU). Preliminary results, in data from five hospitals, indicate that, despite being short and full of noise, text messages can augment other visit information to improve the performance of ICU transfer prediction.

Anthology ID:: W19-1911
Volume:: Proceedings of the 2nd Clinical Natural Language Processing Workshop
Month:: June
Year:: 2019
Address:: Minneapolis, Minnesota, USA
Editors:: Anna Rumshisky, Kirk Roberts, Steven Bethard, Tristan Naumann
Venue:: ClinicalNLP
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 89–94
Language:
URL:: https://aclanthology.org/W19-1911/
DOI:: 10.18653/v1/W19-1911
Bibkey:
Cite (ACL):: Faiza Khan Khattak, Chloé Pou-Prom, Robert Wu, and Frank Rudzicz. 2019. Predicting ICU transfers using text messages between nurses and doctors. In Proceedings of the 2nd Clinical Natural Language Processing Workshop, pages 89–94, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):: Predicting ICU transfers using text messages between nurses and doctors (Khan Khattak et al., ClinicalNLP 2019)
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PDF:: https://aclanthology.org/W19-1911.pdf

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@inproceedings{khan-khattak-etal-2019-predicting,
    title = "Predicting {ICU} transfers using text messages between nurses and doctors",
    author = "Khan Khattak, Faiza  and
      Pou-Prom, Chlo{\'e}  and
      Wu, Robert  and
      Rudzicz, Frank",
    editor = "Rumshisky, Anna  and
      Roberts, Kirk  and
      Bethard, Steven  and
      Naumann, Tristan",
    booktitle = "Proceedings of the 2nd Clinical Natural Language Processing Workshop",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-1911/",
    doi = "10.18653/v1/W19-1911",
    pages = "89--94",
    abstract = "We explore the use of real-time clinical information, i.e., text messages sent between nurses and doctors regarding patient conditions in order to predict transfer to the intensive care unit(ICU). Preliminary results, in data from five hospitals, indicate that, despite being short and full of noise, text messages can augment other visit information to improve the performance of ICU transfer prediction."
}

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%0 Conference Proceedings
%T Predicting ICU transfers using text messages between nurses and doctors
%A Khan Khattak, Faiza
%A Pou-Prom, Chloé
%A Wu, Robert
%A Rudzicz, Frank
%Y Rumshisky, Anna
%Y Roberts, Kirk
%Y Bethard, Steven
%Y Naumann, Tristan
%S Proceedings of the 2nd Clinical Natural Language Processing Workshop
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F khan-khattak-etal-2019-predicting
%X We explore the use of real-time clinical information, i.e., text messages sent between nurses and doctors regarding patient conditions in order to predict transfer to the intensive care unit(ICU). Preliminary results, in data from five hospitals, indicate that, despite being short and full of noise, text messages can augment other visit information to improve the performance of ICU transfer prediction.
%R 10.18653/v1/W19-1911
%U https://aclanthology.org/W19-1911/
%U https://doi.org/10.18653/v1/W19-1911
%P 89-94

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Markdown (Informal)

[Predicting ICU transfers using text messages between nurses and doctors](https://aclanthology.org/W19-1911/) (Khan Khattak et al., ClinicalNLP 2019)

Predicting ICU transfers using text messages between nurses and doctors (Khan Khattak et al., ClinicalNLP 2019)

ACL

Faiza Khan Khattak, Chloé Pou-Prom, Robert Wu, and Frank Rudzicz. 2019. Predicting ICU transfers using text messages between nurses and doctors. In Proceedings of the 2nd Clinical Natural Language Processing Workshop, pages 89–94, Minneapolis, Minnesota, USA. Association for Computational Linguistics.