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KMID : 0869620180350040418
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Journal of Korean Society of Hospital Pharmacists
2018 Volume.35 No. 4 p.418 ~ p.429
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Predictive Factors for Medication Adherence in a Geriatric Assessment Program in Korea
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Kim Min-So
Choi Na-Ye
Suh Ye-Won
Park Jin-Young
Lee Jeong-Hwa
Lee Eun-Sook
Lee Euni
Kim Sun-Wook
Kim Kwang-Il
Kim Cheol-Ho
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Abstract
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Background: To improve medication adherence in elderly patients, the role of pharmacists in teambased services has been highlighted in the literature. However, not much is known about the role and the service elements involved in comprehensive geriatric programs in South Korea. This study was designed to describe the current status of medication adherence in geriatric patients based on the comprehensive geriatric assessment program and analyze the predictive factors for medication adherence in a tertiary teaching hospital.
Methods: A retrospective cohort study was performed using electronic medical records of 247 patients from March 1st, 2015 to August 31st, 2015. Medication adherence and the types of non-adherence were also collected. Predictive factors for adherence were evaluated by including factors related to demographics, medications, illness, and patterns of medical usage.
Results: The mean age of the study population was 81.2 years (range 65~98 years) and they were taking 9.7 drugs on an average (SD 5.0 drugs). The overall rate of non-adherence was 34%. About 48% of the patients had any forms of assistance in the medication administration. The most common type of non-adherence was“ self-adjustment”. The multivariate analyses revealed that age (adjusted odds ratio, 0.87 [95% CI, 0.80-0.96]; p 0.05) and the number of inappropriate medications (adjusted odds ratio, 0.59 [95% CI, 0.40-0.89]; p 0.05) were strong predictors for non-adherence.
Conclusions: These results indicate that strategic considerations of the predictors of non-adherence should be improved in medication counseling services targeting elderly patients.
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KEYWORD
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Elderly patient, Medication adherence, Comprehensive geriatric assessment, Predictive factor
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