Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program

The purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on psychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the impact of weight fluctuations and other factors on hospi...

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Main Authors: Adrian H. Zai, Jeremiah G. Ronquillo, Regina Nieves, Henry C. Chueh, Joseph C. Kvedar, Kamal Jethwani
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:International Journal of Telemedicine and Applications
Online Access:http://dx.doi.org/10.1155/2013/305819
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spelling doaj-968d5b36f32a4083b939940e235037f52020-11-25T00:59:58ZengHindawi LimitedInternational Journal of Telemedicine and Applications1687-64151687-64232013-01-01201310.1155/2013/305819305819Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring ProgramAdrian H. Zai0Jeremiah G. Ronquillo1Regina Nieves2Henry C. Chueh3Joseph C. Kvedar4Kamal Jethwani5Laboratory of Computer Science, Massachusetts General Hospital of Harvard Medical School, Boston, MA 02114, USALaboratory of Computer Science, Massachusetts General Hospital of Harvard Medical School, Boston, MA 02114, USAPartners Center for Connected Health, Partners Healthcare, Boston, MA 02114, USALaboratory of Computer Science, Massachusetts General Hospital of Harvard Medical School, Boston, MA 02114, USAPartners Center for Connected Health, Partners Healthcare, Boston, MA 02114, USAPartners Center for Connected Health, Partners Healthcare, Boston, MA 02114, USAThe purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on psychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the impact of weight fluctuations and other factors on hospital readmission. Clinical, demographic, and telemonitoring data was collected from 100 patients enrolled in the Partners Connected Cardiac Care Program between July 2008 and November 2011. 38% of study participants were readmitted to the hospital within 30 days. Ten different heart-failure-related symptoms were reported 17,389 times, with the top three contributing approximately 50% of the volume. The psychosocial readmission model yielded an AUC of 0.67, along with sensitivity 0.87, specificity 0.32, positive predictive value 0.44, and negative predictive value 0.8 at a cutoff value of 0.30. In summary, hospital readmission models based on psychosocial characteristics, standardized changes in weight, or patient-reported symptoms can be developed and validated in heart failure patients participating in an institutional telemonitoring program. However, more robust models will need to be developed that use a comprehensive set of factors in order to have a significant impact on population health.http://dx.doi.org/10.1155/2013/305819
collection DOAJ
language English
format Article
sources DOAJ
author Adrian H. Zai
Jeremiah G. Ronquillo
Regina Nieves
Henry C. Chueh
Joseph C. Kvedar
Kamal Jethwani
spellingShingle Adrian H. Zai
Jeremiah G. Ronquillo
Regina Nieves
Henry C. Chueh
Joseph C. Kvedar
Kamal Jethwani
Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program
International Journal of Telemedicine and Applications
author_facet Adrian H. Zai
Jeremiah G. Ronquillo
Regina Nieves
Henry C. Chueh
Joseph C. Kvedar
Kamal Jethwani
author_sort Adrian H. Zai
title Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program
title_short Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program
title_full Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program
title_fullStr Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program
title_full_unstemmed Assessing Hospital Readmission Risk Factors in Heart Failure Patients Enrolled in a Telemonitoring Program
title_sort assessing hospital readmission risk factors in heart failure patients enrolled in a telemonitoring program
publisher Hindawi Limited
series International Journal of Telemedicine and Applications
issn 1687-6415
1687-6423
publishDate 2013-01-01
description The purpose of this study was to validate a previously developed heart failure readmission predictive algorithm based on psychosocial factors, develop a new model based on patient-reported symptoms from a telemonitoring program, and assess the impact of weight fluctuations and other factors on hospital readmission. Clinical, demographic, and telemonitoring data was collected from 100 patients enrolled in the Partners Connected Cardiac Care Program between July 2008 and November 2011. 38% of study participants were readmitted to the hospital within 30 days. Ten different heart-failure-related symptoms were reported 17,389 times, with the top three contributing approximately 50% of the volume. The psychosocial readmission model yielded an AUC of 0.67, along with sensitivity 0.87, specificity 0.32, positive predictive value 0.44, and negative predictive value 0.8 at a cutoff value of 0.30. In summary, hospital readmission models based on psychosocial characteristics, standardized changes in weight, or patient-reported symptoms can be developed and validated in heart failure patients participating in an institutional telemonitoring program. However, more robust models will need to be developed that use a comprehensive set of factors in order to have a significant impact on population health.
url http://dx.doi.org/10.1155/2013/305819
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