Predicting ICU transfers using text messages between nurses and doctors

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


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
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)
Copy Citation:
PDF:
https://aclanthology.org/W19-1911.pdf