Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.

Journal: Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing

PMID: 39601443

Abstract

INTRODUCTION: Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this information is predominantly contained in clinical notes. Natural language processing can uncover symptom information among older adults with urinary incontinence to promote holistic, equitable care.

Authors

Danielle Scharp

Columbia University School of Nursing, New York, NY.
Jiyoun Song

School of Nursing, Columbia University, New York, New York, USA.
Mollie Hobensack

Columbia University School of Nursing, United States. Electronic address: mxh2000@cumc.columbia.edu.
Mary Happel Palmer

University of North Carolina School of Nursing, Chapel Hill, North Carolina, USA.
Veronica Barcelona

School of Nursing, Columbia University, 560 West 168th St, Mail Code 6, New York, NY, 10032, USA. vb2534@cumc.columbia.edu.
Maxim Topaz

Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA.

Keywords

Aged Aged, 80 and over Cross-Sectional Studies Female Home Care Services Humans Male Natural Language Processing Urinary Incontinence

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View on PubMed Access via DOI PubMed (39601443)

Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.

Abstract

Authors

Keywords

External Resources

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