What puts heart failure patients at risk for poor medication adherence?
George J Knafl,1 Barbara Riegel2,31School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 2School of Nursing, University of Pennsylvania, Philadelphia, PA, USA; 3Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA, USABackground: Medication nonadheren...
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| Format: | Article |
| Language: | English |
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Dove Medical Press
2014-07-01
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| Series: | Patient Preference and Adherence |
| Online Access: | http://www.dovepress.com/what-puts-heart-failure-patients-at-risk-for-poor-medication-adherence-peer-reviewed-article-PPA |
| _version_ | 1818473708802539520 |
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| author | Knafl GJ Riegel B |
| author_facet | Knafl GJ Riegel B |
| author_sort | Knafl GJ |
| collection | DOAJ |
| description | George J Knafl,1 Barbara Riegel2,31School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 2School of Nursing, University of Pennsylvania, Philadelphia, PA, USA; 3Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA, USABackground: Medication nonadherence is a major cause of hospitalization in patients with heart failure (HF), which contributes enormously to health care costs. We previously found, using the World Health Organization adherence dimensions, that condition and patient level factors predicted nonadherence in HF. In this study, we assessed a wider variety of condition and patient factors and interactions to improve our ability to identify those at risk for hospitalization. Materials and methods: Medication adherence was measured electronically over the course of 6 months, using the Medication Event Monitoring System (MEMS). A total of 242 HF patients completed the study, and usable MEMS data were available for 218 (90.1%). Participants were primarily white (68.3%), male (64.2%), and retired (44.5%). Education ranged from 8–29 years (mean, 14.0 years; standard deviation, 2.9 years). Ages ranged from 30–89 years (mean, 62.8 years; standard deviation, 11.6 years). Analyses used adaptive methods based on heuristic searches controlled by cross-validation scores. First, individual patient adherence patterns over time were used to categorize patients in poor versus better adherence types. Then, risk factors for poor adherence were identified. Finally, an effective model for predicting poor adherence was identified based on identified risk factors and possible pairwise interactions between them. Results: A total of 63 (28.9%) patients had poor adherence. Three interaction risk factors for poor adherence were identified: a higher number of comorbid conditions with a higher total number of daily medicines, older age with poorer global sleep quality, and fewer months since diagnosis of HF with poorer global sleep quality. Patients had between zero and three risk factors. The odds for poor adherence increased by 2.6 times with a unit increase in the number of risk factors (odds ratio, 2.62; 95% confidence interval, 1.78–3.86; P<0.001).Conclusion: Newly diagnosed, older HF patients with comorbid conditions, polypharmacy, and poor sleep are at risk for poor medication adherence. Interventions addressing these specific barriers are needed.Keywords: heart failure, medication adherence, multiple chronic conditions, risk factors, self-care, sleep quality |
| first_indexed | 2024-04-14T04:26:09Z |
| format | Article |
| id | doaj.art-4ac2d4cdaefd400e9416a3b85e89b5df |
| institution | Directory Open Access Journal |
| issn | 1177-889X |
| language | English |
| last_indexed | 2024-04-14T04:26:09Z |
| publishDate | 2014-07-01 |
| publisher | Dove Medical Press |
| record_format | Article |
| series | Patient Preference and Adherence |
| spelling | doaj.art-4ac2d4cdaefd400e9416a3b85e89b5df2022-12-22T02:12:17ZengDove Medical PressPatient Preference and Adherence1177-889X2014-07-012014default1007101817643What puts heart failure patients at risk for poor medication adherence?Knafl GJRiegel BGeorge J Knafl,1 Barbara Riegel2,31School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 2School of Nursing, University of Pennsylvania, Philadelphia, PA, USA; 3Leonard Davis Institute, University of Pennsylvania, Philadelphia, PA, USABackground: Medication nonadherence is a major cause of hospitalization in patients with heart failure (HF), which contributes enormously to health care costs. We previously found, using the World Health Organization adherence dimensions, that condition and patient level factors predicted nonadherence in HF. In this study, we assessed a wider variety of condition and patient factors and interactions to improve our ability to identify those at risk for hospitalization. Materials and methods: Medication adherence was measured electronically over the course of 6 months, using the Medication Event Monitoring System (MEMS). A total of 242 HF patients completed the study, and usable MEMS data were available for 218 (90.1%). Participants were primarily white (68.3%), male (64.2%), and retired (44.5%). Education ranged from 8–29 years (mean, 14.0 years; standard deviation, 2.9 years). Ages ranged from 30–89 years (mean, 62.8 years; standard deviation, 11.6 years). Analyses used adaptive methods based on heuristic searches controlled by cross-validation scores. First, individual patient adherence patterns over time were used to categorize patients in poor versus better adherence types. Then, risk factors for poor adherence were identified. Finally, an effective model for predicting poor adherence was identified based on identified risk factors and possible pairwise interactions between them. Results: A total of 63 (28.9%) patients had poor adherence. Three interaction risk factors for poor adherence were identified: a higher number of comorbid conditions with a higher total number of daily medicines, older age with poorer global sleep quality, and fewer months since diagnosis of HF with poorer global sleep quality. Patients had between zero and three risk factors. The odds for poor adherence increased by 2.6 times with a unit increase in the number of risk factors (odds ratio, 2.62; 95% confidence interval, 1.78–3.86; P<0.001).Conclusion: Newly diagnosed, older HF patients with comorbid conditions, polypharmacy, and poor sleep are at risk for poor medication adherence. Interventions addressing these specific barriers are needed.Keywords: heart failure, medication adherence, multiple chronic conditions, risk factors, self-care, sleep qualityhttp://www.dovepress.com/what-puts-heart-failure-patients-at-risk-for-poor-medication-adherence-peer-reviewed-article-PPA |
| spellingShingle | Knafl GJ Riegel B What puts heart failure patients at risk for poor medication adherence? Patient Preference and Adherence |
| title | What puts heart failure patients at risk for poor medication adherence? |
| title_full | What puts heart failure patients at risk for poor medication adherence? |
| title_fullStr | What puts heart failure patients at risk for poor medication adherence? |
| title_full_unstemmed | What puts heart failure patients at risk for poor medication adherence? |
| title_short | What puts heart failure patients at risk for poor medication adherence? |
| title_sort | what puts heart failure patients at risk for poor medication adherence |
| url | http://www.dovepress.com/what-puts-heart-failure-patients-at-risk-for-poor-medication-adherence-peer-reviewed-article-PPA |
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