Patient-reported medication adherence barriers among patients with cardiovascular risk factors.
| dc.contributor.author | Zullig, Leah L | |
| dc.contributor.author | Stechuchak, Karen M | |
| dc.contributor.author | Goldstein, Karen M | |
| dc.contributor.author | Olsen, Maren K | |
| dc.contributor.author | McCant, Felicia M | |
| dc.contributor.author | Danus, Susanne | |
| dc.contributor.author | Crowley, Matthew J | |
| dc.contributor.author | Oddone, Eugene Z | |
| dc.contributor.author | Bosworth, Hayden B | |
| dc.date.accessioned | 2024-02-01T15:15:32Z | |
| dc.date.available | 2024-02-01T15:15:32Z | |
| dc.date.issued | 2015-06 | |
| dc.description.abstract | BackgroundMany patients experience barriers that make it difficult to take cardiovascular disease (CVD)-related medications as prescribed. The Cardiovascular Intervention Improvement Telemedicine Study (CITIES) was a tailored behavioral pharmacist-administered and telephone-based intervention for reducing CVD risk.ObjectivesTo (a) describe patient-reported barriers to taking their medication as prescribed and (b) evaluate patient-level characteristics associated with reporting medication barriers.MethodsWe recruited patients receiving care at primary care clinics affiliated with Durham Veterans Affairs Medical Center. Eligible patients were diagnosed with hypertension and/or hyperlipidemia that were poorly controlled (blood pressure of > 150/100 mmHg and/or low-density lipoprotein value > 130 mg/dL). At the time of enrollment, patients completed an interview with 7 questions derived from a validated medication barriers measure. Patient characteristics and individual medication treatment barriers are described. Multivariable linear regression was used to examine the association between a medication barrier score and patient characteristics.ResultsMost patients (n = 428) were married or living with their partners (57%) and were men (85%) who were diagnosed with hypertension and hyperlipidemia (64%). The most commonly reported barriers were having too much medication to take (31%) and forgetting whether medication was taken at a particular time (24%). In adjusted analysis, those who were not employed (1.32, 95% CI = 0.50-2.14) or did not have someone to help with tasks, if needed (1.66, 95% CI = 0.42-2.89), reported higher medication barrier scores. Compared with those diagnosed with hypertension and hyperlipidemia, those with only hypertension (0.91, 95% CI = 0.04-1.79) reported higher medication barrier scores.ConclusionsBarriers to medication adherence are common. Evaluating and addressing barriers may increase medication adherence. | |
| dc.identifier | 2015(21)6: 479-485 | |
| dc.identifier.issn | 2376-0540 | |
| dc.identifier.issn | 2376-1032 | |
| dc.identifier.uri | ||
| dc.language | eng | |
| dc.publisher | Academy of Managed Care Pharmacy | |
| dc.relation.ispartof | Journal of managed care & specialty pharmacy | |
| dc.relation.isversionof | 10.18553/jmcp.2015.21.6.479 | |
| dc.rights.uri | ||
| dc.subject | Humans | |
| dc.subject | Cardiovascular Diseases | |
| dc.subject | Hypertension | |
| dc.subject | Linear Models | |
| dc.subject | Risk Factors | |
| dc.subject | Telephone | |
| dc.subject | Aged | |
| dc.subject | Middle Aged | |
| dc.subject | Pharmacists | |
| dc.subject | Pharmacy Service, Hospital | |
| dc.subject | Hospitals, Veterans | |
| dc.subject | Primary Health Care | |
| dc.subject | Female | |
| dc.subject | Male | |
| dc.subject | Hyperlipidemias | |
| dc.subject | Medication Adherence | |
| dc.title | Patient-reported medication adherence barriers among patients with cardiovascular risk factors. | |
| dc.type | Journal article | |
| duke.contributor.orcid | Zullig, Leah L|0000-0002-6638-409X | |
| duke.contributor.orcid | Goldstein, Karen M|0000-0003-4419-5869 | |
| duke.contributor.orcid | Olsen, Maren K|0000-0002-9540-2103 | |
| duke.contributor.orcid | Crowley, Matthew J|0000-0002-6205-4536 | |
| duke.contributor.orcid | Bosworth, Hayden B|0000-0001-6188-9825 | |
| pubs.begin-page | 479 | |
| pubs.end-page | 485 | |
| pubs.issue | 6 | |
| pubs.organisational-group | Duke | |
| pubs.organisational-group | School of Medicine | |
| pubs.organisational-group | Basic Science Departments | |
| pubs.organisational-group | Clinical Science Departments | |
| pubs.organisational-group | Institutes and Centers | |
| pubs.organisational-group | Biostatistics & Bioinformatics | |
| pubs.organisational-group | Medicine | |
| pubs.organisational-group | Psychiatry & Behavioral Sciences | |
| pubs.organisational-group | Medicine, Endocrinology, Metabolism, and Nutrition | |
| pubs.organisational-group | Medicine, General Internal Medicine | |
| pubs.organisational-group | Duke Cancer Institute | |
| pubs.organisational-group | Duke Clinical Research Institute | |
| pubs.organisational-group | Institutes and Provost's Academic Units | |
| pubs.organisational-group | Center for the Study of Aging and Human Development | |
| pubs.organisational-group | Initiatives | |
| pubs.organisational-group | Duke Science & Society | |
| pubs.organisational-group | Population Health Sciences | |
| pubs.organisational-group | Duke Innovation & Entrepreneurship | |
| pubs.organisational-group | Psychiatry & Behavioral Sciences, Behavioral Medicine & Neurosciences | |
| pubs.organisational-group | Duke - Margolis Center For Health Policy | |
| pubs.organisational-group | Biostatistics & Bioinformatics, Division of Biostatistics | |
| pubs.publication-status | Published | |
| pubs.volume | 21 |
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