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Electronically monitored medication adherence predicts hospitalization in heart failure patients
BACKGROUND: Hospitalization contributes enormously to health care costs associated with heart failure. Many investigators have attempted to predict hospitalization in these patients. None of these models has been highly effective in prediction, suggesting that important risk factors remain unidentif...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862652/ https://www.ncbi.nlm.nih.gov/pubmed/24353407 http://dx.doi.org/10.2147/PPA.S54520 |
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author | Riegel, Barbara Knafl, George J |
author_facet | Riegel, Barbara Knafl, George J |
author_sort | Riegel, Barbara |
collection | PubMed |
description | BACKGROUND: Hospitalization contributes enormously to health care costs associated with heart failure. Many investigators have attempted to predict hospitalization in these patients. None of these models has been highly effective in prediction, suggesting that important risk factors remain unidentified. PURPOSE: To assess prospectively collected medication adherence, objectively measured by the Medication Event Monitoring System, as a predictor of hospitalization in heart failure patients. MATERIALS AND METHODS: We used recently developed adaptive modeling methods to describe patterns of medication adherence in a sample of heart failure patients, and tested the hypothesis that poor medication adherence as determined by adaptive methods was a significant predictor of hospitalization within 6 months. RESULTS: Medication adherence was the best predictor of hospitalization. Besides two dimensions of poor adherence (adherence pattern type and low percentage of prescribed doses taken), four other single factors predicted hospitalization: low hemoglobin, depressed ejection fraction, New York Heart Association class IV, and 12 or more medications taken daily. Seven interactions increased the predictive capability of the model: 1) pattern of poor adherence type and lower score on the Letter–Number Sequencing test, a measure of short-term memory; 2) higher number of comorbid conditions and higher number of daily medications; 3) higher blood urea nitrogen and lower percentage of prescribed doses taken; 4) lower hemoglobin and much worse perceived health compared to last year; 5) older age and lower score on the Telephone Interview of Cognitive Status; 6) higher body mass index and lower hemoglobin; and 7) lower ejection fraction and higher fatigue. Patients with none of these seven interactions had a hospitalization rate of 9.7%. For those with five of these interaction risk factors, 100% were hospitalized. The C-index (the area under the receiver-operating characteristics [ROC] curve) for the model based on the seven interactions was 0.83, indicating excellent discrimination. CONCLUSION: Medication adherence adds important new information to the list of variables previously shown to predict hospitalization in adults with heart failure. |
format | Online Article Text |
id | pubmed-3862652 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-38626522013-12-18 Electronically monitored medication adherence predicts hospitalization in heart failure patients Riegel, Barbara Knafl, George J Patient Prefer Adherence Original Research BACKGROUND: Hospitalization contributes enormously to health care costs associated with heart failure. Many investigators have attempted to predict hospitalization in these patients. None of these models has been highly effective in prediction, suggesting that important risk factors remain unidentified. PURPOSE: To assess prospectively collected medication adherence, objectively measured by the Medication Event Monitoring System, as a predictor of hospitalization in heart failure patients. MATERIALS AND METHODS: We used recently developed adaptive modeling methods to describe patterns of medication adherence in a sample of heart failure patients, and tested the hypothesis that poor medication adherence as determined by adaptive methods was a significant predictor of hospitalization within 6 months. RESULTS: Medication adherence was the best predictor of hospitalization. Besides two dimensions of poor adherence (adherence pattern type and low percentage of prescribed doses taken), four other single factors predicted hospitalization: low hemoglobin, depressed ejection fraction, New York Heart Association class IV, and 12 or more medications taken daily. Seven interactions increased the predictive capability of the model: 1) pattern of poor adherence type and lower score on the Letter–Number Sequencing test, a measure of short-term memory; 2) higher number of comorbid conditions and higher number of daily medications; 3) higher blood urea nitrogen and lower percentage of prescribed doses taken; 4) lower hemoglobin and much worse perceived health compared to last year; 5) older age and lower score on the Telephone Interview of Cognitive Status; 6) higher body mass index and lower hemoglobin; and 7) lower ejection fraction and higher fatigue. Patients with none of these seven interactions had a hospitalization rate of 9.7%. For those with five of these interaction risk factors, 100% were hospitalized. The C-index (the area under the receiver-operating characteristics [ROC] curve) for the model based on the seven interactions was 0.83, indicating excellent discrimination. CONCLUSION: Medication adherence adds important new information to the list of variables previously shown to predict hospitalization in adults with heart failure. Dove Medical Press 2013-12-05 /pmc/articles/PMC3862652/ /pubmed/24353407 http://dx.doi.org/10.2147/PPA.S54520 Text en © 2014 Riegel and Knafl. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Riegel, Barbara Knafl, George J Electronically monitored medication adherence predicts hospitalization in heart failure patients |
title | Electronically monitored medication adherence predicts hospitalization in heart failure patients |
title_full | Electronically monitored medication adherence predicts hospitalization in heart failure patients |
title_fullStr | Electronically monitored medication adherence predicts hospitalization in heart failure patients |
title_full_unstemmed | Electronically monitored medication adherence predicts hospitalization in heart failure patients |
title_short | Electronically monitored medication adherence predicts hospitalization in heart failure patients |
title_sort | electronically monitored medication adherence predicts hospitalization in heart failure patients |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862652/ https://www.ncbi.nlm.nih.gov/pubmed/24353407 http://dx.doi.org/10.2147/PPA.S54520 |
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