title: Identification and Use of Frailty Indicators from Text to Examine Associations with Clinical Outcomes Among Patients with Heart Failure.
abstract: Frailty is an important health outcomes indicator and valuable for guiding healthcare decisions in older adults, but is rarely collected in a quantitative, systematic fashion in routine healthcare. Using a cohort of 12,000 Veterans with heart failure, we investigated the feasibility of topic modeling to identify frailty topics in clinical notes. Topics were generated through unsupervised learning and then manually reviewed by an expert. A total of 53 frailty topics were identified from 100,000 notes. We further examined associations of frailty with age-, sex-, and Charlson Comorbidity Index-adjusted 1-year hospitalizations and mortality (composite outcome) using logistic regression. Frailty (≤ 4 topics versus <4) was associated with twice the risk of the composite outcome, Odds Ratio: 2.2, 95% Confidence Interval: (2.0-2.4). This study demonstrates the feasibility of identifying frailty indicators from clinical notes and linking these to clinically relevant outcomes. Future work includes integrating frailty indicators into validated predictive tools.
authors.affiliation: Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA.
authors.forename: Yijun
authors.initials: Y
authors.lastname: Shao
authors.affiliation: Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center, George E. Wahlen Department; Veterans Affairs Medical Center, Salt Lake City, UT, USA.
authors.forename: April F
authors.initials: AF
authors.lastname: Mohanty
authors.affiliation: Washington DC VA Medical Center, Washington, DC, USA.
authors.forename: Ali
authors.initials: A
authors.lastname: Ahmed
authors.affiliation: Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA;; Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center, George E. Wahlen Department; Veterans Affairs Medical Center, Salt Lake City, UT, USA.
authors.forename: Charlene R
authors.initials: CR
authors.lastname: Weir
authors.affiliation: Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA.
authors.forename: Bruce E
authors.initials: BE
authors.lastname: Bray
authors.affiliation: University of Utah, Division of Cardiovascular Medicine, Salt Lake City, UT, USA.
authors.forename: Rashmee U
authors.initials: RU
authors.lastname: Shah
authors.affiliation: Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA;; Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center, George E. Wahlen Department; Veterans Affairs Medical Center, Salt Lake City, UT, USA;; Washington DC VA Medical Center, Washington, DC, USA;; Department of Clinical Research and Leadership, George Washington University, Washington, DC, USA.
authors.forename: Douglas
authors.initials: D
authors.lastname: Redd
authors.affiliation: Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, USA;; Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center, George E. Wahlen Department; Veterans Affairs Medical Center, Salt Lake City, UT, USA;; Washington DC VA Medical Center, Washington, DC, USA;; Department of Clinical Research and Leadership, George Washington University, Washington, DC, USA.
authors.forename: Qing
authors.initials: Q
authors.lastname: Zeng-Treitler
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D057286:Electronic Health Records; D005240:Feasibility Studies; D005260:Female; D016330:Frail Elderly; D006333:Heart Failure; D006760:Hospitalization; D006801:Humans; D016247:Information Storage and Retrieval; D016015:Logistic Models; D008297:Male; D011379:Prognosis; D014481:United States; D014493:United States Department of Veterans Affairs