Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation.

Journal: Journal of the American Medical Informatics Association : JAMIA

Published Date: Sep 1, 2016

OBJECTIVE: Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients.

R Scott Evans

Medical Informatics, Intermountain Healthcare Biomedical Informatics, University of Utah rscott.evans@imail.org.
Jose Benuzillo

Intermountain Healthcare Cardiovascular Clinical Program.
Benjamin D Horne

Cardiovascular Department, Intermountain Medical Center Heart Institute, Salt Lake City, UT, United States.
James F Lloyd

Medical Informatics, Intermountain Healthcare.
Alejandra Bradshaw

Enterprise Data Warehouse, Intermountain Healthcare.
Deborah Budge

Intermountain Heart Institute, Intermountain Medical Center.
Kismet D Rasmusson

Intermountain Heart Institute, Intermountain Medical Center.
Colleen Roberts

Intermountain Healthcare Cardiovascular Clinical Program.
Jason Buckway

McKay Dee Hospital Cardiovascular Program.
Norma Geer

McKay Dee Hospital Cardiovascular Program.
Teresa Garrett

Intermountain Healthcare Integrated Care Management.
Donald L Lappé

Intermountain Healthcare Cardiovascular Clinical Program Intermountain Heart Institute, Intermountain Medical Center.

Analysis of Variance Decision Making, Computer-Assisted Electronic Health Records Female Heart Failure Hospital Information Systems Hospitalization Humans Male Natural Language Processing Patient Readmission Pilot Projects Risk Assessment Sensitivity and Specificity Severity of Illness Index

View on PubMed Access via DOI PubMed (26911827)