Identifying the Severity of Heart Valve Stenosis and Regurgitation Among a Diverse Population Within an Integrated Health Care System: Natural Language Processing Approach.

Journal: JMIR cardio

PMID: 39348175

Abstract

BACKGROUND: Valvular heart disease (VHD) is a leading cause of cardiovascular morbidity and mortality that poses a substantial health care and economic burden on health care systems. Administrative diagnostic codes for ascertaining VHD diagnosis are incomplete.

Authors

Fagen Xie

Kaiser Permanente Southern California, Pasadena, CA, USA.
Ming-Sum Lee

Department of Cardiology, Los Angeles Medical Center, Kaiser Permanente Southern California, Pasadena, CA, United States.
Salam Allahwerdy

Department of Clinical Science, Kaiser Permanente Bernard J Tyson School of Medicine, Pasadena, CA, United States.
Darios Getahun

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California.
Benjamin Wessler

Division of Cardiology, Tufts Medical Center, Boston, MA, United States.
Wansu Chen

Kaiser Permanente Southern California, Pasadena, CA, USA.

Keywords

Adult Aged Algorithms California Delivery of Health Care, Integrated Echocardiography Female Heart Valve Diseases Humans Male Middle Aged Natural Language Processing Severity of Illness Index

External Resources

View on PubMed Access via DOI PubMed (39348175)

Identifying the Severity of Heart Valve Stenosis and Regurgitation Among a Diverse Population Within an Integrated Health Care System: Natural Language Processing Approach.

Abstract

Authors

Keywords

External Resources

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