Identifying Mentions of Life Stressors in Clinical Notes

被引：0

作者：

Datar, Shreya ^{[1
]}

Lindemann, Elizabeth A. ^{[2
]}

Silverman, Greg ^{[2
]}

McEwan, Reed ^{[3
]}

Finzel, Raymond ^{[4
]}

Kotlyar, Michael ^{[4
]}

Melton, Genevieve B. ^{[5
]}

Pakhomov, Serguei V. S. ^{[6
]}

机构：

[1] Univ Minnesota, Coll Pharm, Dept Comp Sci, Minneapolis, MN 55455 USA

[2] Univ Minnesota, Dept Surg, Minneapolis, MN USA

[3] Univ Minnesota, Acad Hlth Ctr Off Informat Syst, Minneapolis, MN USA

[4] Univ Minnesota, Coll Pharm, Minneapolis, MN USA

[5] Univ Minnesota, Dept Surg, Inst Hlth Informat, Minneapolis, MN USA

[6] Univ Minnesota, Coll Pharm, Inst Hlth Informat, Minneapolis, MN USA

来源：

2021 IEEE 9TH INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI 2021) | 2021年

基金：

美国医疗保健研究与质量局;

关键词：

knowledge representation; text mining; informatics; medical information systems; ELECTRONIC HEALTH RECORDS; SOCIAL DETERMINANTS; INTERVENTIONS; INVENTORY; SYSTEM; TEXT;

D O I：

10.1109/ICHI52183.2021.00033

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The impact of social determinants on individual health has increasingly been recognized. In this study, we aimed to understand the representation of stressful life events occurring in clinical reports generated outside of mental health specialties. We present a conceptual schema for the representation of stressful events and associated linguistic attributes within free-text clinical notes. We also evaluated existing "off-the-shelf" clinical Natural Language Processing (NLP) systems for the detection of stress related concepts in clinical notes. We found that mentions of stressful events are prevalent even in non-mental health specialties, and that capturing details of stress mentions is challenging. Our results further indicate that existing NLP systems can serve as a reasonable starting point for developing models trained specifically for extracting stress associated information from clinical narratives.

引用

页码：153 / 160

页数：8

共 46 条

[1] Addressing Social Determinants of Health and Health Inequalities
Adler, Nancy E.
Glymour, M. Maria
Fielding, Jonathan
[J]. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2016, 316 (16): : 1641 - 1642
[2] Towards comprehensive syntactic and semantic annotations of the clinical narrative
Albright, Daniel
Lanfranchi, Arrick
Fredriksen, Anwen
Styler, William F.
Warner, Colin
Hwang, Jena D.
Choi, Jinho D.
Dligach, Dmitriy
Nielsen, Rodney D.
Martin, James
Ward, Wayne
Palmer, Martha
Savova, Guergana K.
[J]. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2013, 20 (05) : 922 - 930
[3] Meanings and Misunderstandings: A Social Determinants of Health Lexicon for Health Care Systems
Alderwick, Hugh
Gottlieb, Laura M.
[J]. MILBANK QUARTERLY, 2019, 97 (02) : 407 - 419
[4] Social Determinants of Mental Health: Where We Are and Where We Need to Go
Alegria, Margarita
NeMoyer, Amanda
Bague, Irene Falgas
Wang, Ye
Alvarez, Kiara
[J]. CURRENT PSYCHIATRY REPORTS, 2018, 20 (11)
[5] [Anonymous], 2019, U MINNESOTA BIOMEDIC
[6] [Anonymous], UNIFIED MED LANGUAGE
[7] [Anonymous], 2019, U MINNESOTA
[8] Aronson AR, 2001, J AM MED INFORM ASSN, P17
[9] "Community vital signs": incorporating geocoded social determinants into electronic records to promote patient and population health
Bazemore, Andrew W.
Cottrell, Erika K.
Gold, Rachel
Hughes, Lauren S.
Phillips, Robert L.
Angier, Heather
Burdick, Timothy E.
Carrozza, Mark A.
Devoe, Jennifer E.
[J]. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2016, 23 (02) : 407 - 412
[10] Comparing NLP Systems to Extract Entities of Eligibility Criteria in Dietary Supplements Clinical Trials Using NLP-ADAPT
Bompelli, Anusha
Silverman, Greg
Finzel, Raymond
Vasilakes, Jake
Knoll, Benjamin
Pakhomov, Serguei
Zhang, Rui
[J]. ARTIFICIAL INTELLIGENCE IN MEDICINE (AIME 2020), 2020, : 67 - 77

← 1 2 3 4 5 →