R Scott Evans1, Abdallah G Kfoury2, Benjamin D Horne3, James F Lloyd4, Jose Benuzillo5, Kismet D Rasmusson2, Colleen Roberts5, Donald L Lappé2. 1. Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah; Biomedical Informatics, University of Utah, Salt Lake City, Utah;; Intermountain Healthcare Cardiovascular Clinical Program, Salt Lake City, Utah;. Electronic address: rscott.evans@imail.org. 2. Intermountain Healthcare Cardiovascular Clinical Program, Salt Lake City, Utah;; Intermountain Heart Institute, Intermountain Medical Center. Salt Lake City, Utah. 3. Biomedical Informatics, University of Utah, Salt Lake City, Utah;; Intermountain Heart Institute, Intermountain Medical Center. Salt Lake City, Utah. 4. Medical Informatics, Intermountain Healthcare, Salt Lake City, Utah. 5. Intermountain Healthcare Cardiovascular Clinical Program, Salt Lake City, Utah.
Abstract
BACKGROUND: Patients who need and receive timely advanced heart failure (HF) therapies have better long-term survival. However, many of these patients are not identified and referred as soon as they should be. METHODS: A clinical decision support (CDS) application sent secure email notifications to HF patients' providers when they transitioned to advanced disease. Patients identified with CDS in 2015 were compared with control patients from 2013 to 2014. Kaplan-Meier methods and Cox regression were used in this intention-to-treat analysis to compare differences between visits to specialized and survival. RESULTS: Intervention patients were referred to specialized heart facilities significantly more often within 30 days (57% vs 34%; P < .001), 60 days (69% vs 44%; P < .0001), 90 days (73% vs 49%; P < .0001), and 180 days (79% vs 58%; P < .0001). Age and sex did not predict heart facility visits, but renal disease did and patients of nonwhite race were less likely to visit specialized heart facilities. Significantly more intervention patients were found to be alive at 30 (95% vs 92%; P = .036), 60 (95% vs 90%; P = .0013), 90 (94% vs 87%; P = .0002), and 180 days (92% vs 84%; P = .0001). Age, sex, and some comorbid diseases were also predictors of mortality, but race was not. CONCLUSIONS: We found that CDS can facilitate the early identification of patients needing advanced HF therapy and that its use was associated with significantly more patients visiting specialized heart facilities and longer survival.
BACKGROUND:Patients who need and receive timely advanced heart failure (HF) therapies have better long-term survival. However, many of these patients are not identified and referred as soon as they should be. METHODS: A clinical decision support (CDS) application sent secure email notifications to HF patients' providers when they transitioned to advanced disease. Patients identified with CDS in 2015 were compared with control patients from 2013 to 2014. Kaplan-Meier methods and Cox regression were used in this intention-to-treat analysis to compare differences between visits to specialized and survival. RESULTS: Intervention patients were referred to specialized heart facilities significantly more often within 30 days (57% vs 34%; P < .001), 60 days (69% vs 44%; P < .0001), 90 days (73% vs 49%; P < .0001), and 180 days (79% vs 58%; P < .0001). Age and sex did not predict heart facility visits, but renal disease did and patients of nonwhite race were less likely to visit specialized heart facilities. Significantly more intervention patients were found to be alive at 30 (95% vs 92%; P = .036), 60 (95% vs 90%; P = .0013), 90 (94% vs 87%; P = .0002), and 180 days (92% vs 84%; P = .0001). Age, sex, and some comorbid diseases were also predictors of mortality, but race was not. CONCLUSIONS: We found that CDS can facilitate the early identification of patients needing advanced HF therapy and that its use was associated with significantly more patients visiting specialized heart facilities and longer survival.
Authors: Kelly J Thomas Craig; Nicole Fusco; Kristina Lindsley; Jane L Snowdon; Van C Willis; Yull E Arriaga; Irene Dankwa-Mullan Journal: Cardiovasc Digit Health J Date: 2020-11-06
Authors: Matthew W Segar; Kershaw V Patel; Anne S Hellkamp; Muthiah Vaduganathan; Yuliya Lokhnygina; Jennifer B Green; Siu-Hin Wan; Ahmed A Kolkailah; Rury R Holman; Eric D Peterson; Vaishnavi Kannan; Duwayne L Willett; Darren K McGuire; Ambarish Pandey Journal: J Am Heart Assoc Date: 2022-06-03 Impact factor: 6.106