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...
Main Authors: | , , , , , |
---|---|
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 |
id |
doaj-968d5b36f32a4083b939940e235037f5 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT adrianhzai assessinghospitalreadmissionriskfactorsinheartfailurepatientsenrolledinatelemonitoringprogram AT jeremiahgronquillo assessinghospitalreadmissionriskfactorsinheartfailurepatientsenrolledinatelemonitoringprogram AT reginanieves assessinghospitalreadmissionriskfactorsinheartfailurepatientsenrolledinatelemonitoringprogram AT henrycchueh assessinghospitalreadmissionriskfactorsinheartfailurepatientsenrolledinatelemonitoringprogram AT josephckvedar assessinghospitalreadmissionriskfactorsinheartfailurepatientsenrolledinatelemonitoringprogram AT kamaljethwani assessinghospitalreadmissionriskfactorsinheartfailurepatientsenrolledinatelemonitoringprogram |
_version_ |
1725215066624622592 |