@inproceedings{fd13a0659a5b488ba97b739d065a090a,
title = "Prediction of Future Health Care Utilization",
abstract = "Psychosocial factors are known to have adverse health impacts, but are rarely measured; using natural language processing, we extracted factors that identified a higher risk segment of older adults with multimorbidity. We find these extracted features are highly predictive of future emergency department visits and hospitalizations, although only marginal prediction gains are seen compared to other models without these factors. Combining these extraction techniques with other measures of social determinants may help catalyze population health efforts to mitigate these health impacts.",
keywords = "biopsychosocial, multimorbidity, psychosocial",
author = "Dorr, {David A.} and Taylor King and Ana Qui{\~n}ones",
note = "Publisher Copyright: {\textcopyright} 2022 International Medical Informatics Association (IMIA) and IOS Press.; 18th World Congress on Medical and Health Informatics: One World, One Health - Global Partnership for Digital Innovation, MEDINFO 2021 ; Conference date: 02-10-2021 Through 04-10-2021",
year = "2022",
month = jun,
day = "6",
doi = "10.3233/SHTI220282",
language = "English (US)",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "1090--1091",
editor = "Paula Otero and Philip Scott and Martin, {Susan Z.} and Elaine Huesing",
booktitle = "MEDINFO 2021",
address = "Netherlands",
}