Deep learning algorithms to identify documentation of serious illness conversations during intensive care unit admissions

Palliat Med. 2019 Feb;33(2):187-196. doi: 10.1177/0269216318810421. Epub 2018 Nov 14.

Alex Chan^{1

2}, Isabel Chien^{1

3}, Edward Moseley⁴, Saad Salman², Sarah Kaminer Bourland², Daniela Lamas⁵, Anne M Walling^{6

7}, James A Tulsky^{1

8}, Charlotta Lindvall^{1

8}

¹ 1 Department of Psychosocial Oncology and Palliative Care, Dana-Farber Cancer Institute, Boston, MA, USA.
² 2 Harvard T. H. Chan School of Public Health, Boston, MA, USA.
³ 3 Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴ 4 College of Science and Mathematics, University of Massachusetts Boston, Boston, MA, USA.
⁵ 5 Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
⁶ 6 Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
⁷ 7 Palliative Care, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
⁸ 8 Division of Palliative Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.

No abstract available

Keywords: Quality indicators (healthcare); advance care planning; end-of-life care; intensive care units; machine learning.

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