Use of Natural Language Processing to Assess Frequency of Functional Status Documentation for Patients Newly Diagnosed With Colorectal Cancer

Nicole Agaronnik; Charlotta Lindvall; Areej El-Jawahri; Wei He; Lisa Iezzoni

doi:10.1001/jamaoncol.2020.2708

Use of Natural Language Processing to Assess Frequency of Functional Status Documentation for Patients Newly Diagnosed With Colorectal Cancer

JAMA Oncol. 2020 Oct 1;6(10):1628-1630. doi: 10.1001/jamaoncol.2020.2708.

Authors

Nicole Agaronnik¹, Charlotta Lindvall^{2

3}, Areej El-Jawahri^{4

5}, Wei He⁶, Lisa Iezzoni^{1

4}

Affiliations

¹ Health Policy Research Center-Mongan Institute, Massachusetts General Hospital, Boston.
² Department of Psychosocial Oncology and Palliative Care, Dana-Farber Cancer Institute, Boston, Massachusetts.
³ Division of Palliative Medicine, Brigham and Women's Hospital, Boston, Massachusetts.
⁴ Department of Medicine, Harvard Medical School, Boston, Massachusetts.
⁵ Division of Hematology and Oncology, Massachusetts General Hospital, Boston.
⁶ Division of General Internal Medicine, Massachusetts General Hospital, Boston.

Abstract

This cross-sectional study applies natural language processing to electronic health records from a large health care delivery system to examine performance status documentation among patients newly diagnosed with colorectal cancer.

MeSH terms

Adult
Aged
Colorectal Neoplasms / physiopathology*
Documentation*
Female
Functional Status*
Humans
Male
Middle Aged
Natural Language Processing*

Grants and funding

R21 HD095240/HD/NICHD NIH HHS/United States