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Associations between patient factors and medication adherence: A Jordanian experience.

ABSTRACT: OBJECTIVE:To explore the effect of patient characteristics and health beliefs on their medication adherence. METHODS:Patients (n=167) with chronic conditions (mean age 58.9; SD=13.54, 53% males) were recruited from March 2009- to March 2010 using a cross sectional study design. Data collected included patients' demographics, medical conditions, medications therapeutic regimen, frequency of physician visits and health beliefs. Patient self-reported adherence to medications was assessed by the researcher using a validated and published scale. Treatment related problems (TRPs) were evaluated for each patient by competent clinical pharmacists. Associations between patient characteristics/health beliefs with adherence were explored. RESULTS:About half of the patients (46.1%) were non-adherent. A significant association was found between lower adherence and higher number of disease states (p<0.001), higher number of medications (p=0.001), and higher number of identified TRPs (p = 0.003). Patient adherence was positively affected by older age, higher educational level, and higher number of physician visits per month, while it was negatively affected by reporting difficulties with getting prescription refills on time. CONCLUSION:This study identified different factors that may negatively affect adherence, including higher number of medications and disease states, higher number of identified TRPs and inability to getting prescription refills on time. Hence, more care needs to be provided to patients with complex therapeutic regimens in order to enhance adherence.

SUBMITTER: Basheti IA

PROVIDER: S-EPMC4800011 | biostudies-literature | 2016 Jan-Mar

REPOSITORIES: biostudies-literature

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Associations between patient factors and medication adherence: A Jordanian experience.

Basheti Iman A IA Hait Sami Saqf El SS Qunaibi Eyad A EA Aburuz Salah S Bulatova Nailya N

Pharmacy practice 20160101 1

<h4>Objective</h4>To explore the effect of patient characteristics and health beliefs on their medication adherence.<h4>Methods</h4>Patients (n=167) with chronic conditions (mean age 58.9; SD=13.54, 53% males) were recruited from March 2009- to March 2010 using a cross sectional study design. Data collected included patients' demographics, medical conditions, medications therapeutic regimen, frequency of physician visits and health beliefs. Patient self-reported adherence to medications was asse ...[more]

PMID: 27011772

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Project description:PurposeTo understand patients' qualitative experiences with the Support, Educate, Empower (SEE) personalized glaucoma coaching program, provide a richer understanding of the components of the intervention that were useful in eliciting behavior change, and understand how to improve the SEE Program.DesignA concurrent mixed-methods process analysis.ParticipantsThirty-nine patients with a diagnosis of any kind of glaucoma or ocular hypertension who were aged ≥40 years, were taking ≥1 glaucoma medication, spoke English, self-administered their eye drops, and had poor glaucoma medication adherence (defined as taking ≤80% of prescribed medication doses assessed via electronic medication adherence monitors) who completed the 7-month SEE Program.MethodsAll participants who completed the study were interviewed in-person using a semistructured interview guide after the intervention. Coders conducted qualitative analysis of transcribed interviews using Grounded Theory. Participants were then stratified into groups based on change in adherence, and thematic differences between groups were examined.Main outcome measuresThemes that emerged from interviews categorized by the number of participants who expressed a theme and the number of representative citations.ResultsParticipants expressed positive views toward the program overall (95%, n = 37/39). They perceived program components as working together to improve their medication adherence. Interactions with the glaucoma coach (38 participants, 184 citations), motivation to aid personal change (38 participants, 157 citations), personalized glaucoma education (38 participants, 149 citations), electronic reminders, and hearing their adherence score (37 participants, 90 citations) were most commonly cited by participants as helpful program elements contributing to improved adherence. Patients expressed a desire for personalized education to be a standard part of glaucoma care. Participants who demonstrated more improvement in adherence had a more trusting attitude toward the adherence score and a greater magnitude of perceived personal need to improve adherence.ConclusionsParticipants reported a highly positive response to the in-person glaucoma education and motivational interviewing intervention used in conjunction with automated adherence reminders.

Project description:Background: Few studies have investigated the association between medication literacy and medication adherence as well as the influence of medication literacy on medication adherence in hypertensive patients. Thus, the goal of the present study was to determine the association between medication literacy and medication adherence in hypertensive patients. Methods: A cross-sectional survey was conducted between August 2016 and December 2016. Self-administered questionnaires were completed, including a self-developed and structured socio-demographic questionnaire; a self-developed, validated, and self-reported Medication Literacy Scale for Hypertensive Patients (C-MLSHP) used for medication literacy measurement; and the Chinese Version of the Morisky Medication Adherence Scale-8 (C-MMAS-8), an eight-item validated, self-report scale for adherence measurement with a total score range of 0-8. A cut-off of 6 was applied to differentiate adherence levels, including patients with an MMAS score <6 (low adherence), MMAS score = 8 (high adherence), and MMAS score ?6 and <8 (moderate adherence). In this study, hypertensive patients' medication literacy levels and adherence to antihypertensive agents were identified. Pearson correlation analysis was carried out to identify the correlation between medication literacy and adherence. Binary logistic regression analysis was performed with medication adherence as the outcome variable in order to confirm factors associated with medication adherence. Results: A total of 420 hypertensive patients, including 198 women and 222 men with a mean age of 60.6 years (SD = 12.4), were recruited. The mean score of hypertensive patients on the medication literacy scale was 24.03 (SD = 5.13). The mean scores of the four dimensions of knowledge, attitude, skill, and behavior on the medication literacy scale of this study were 6.22 ± 2.22, 5.04 ± 1.16, 4.50 ± 2.21, and 8.27 ± 1.90, respectively. Regarding medication adherence, the mean score of the C-MMAS-8 in this study was 4.82 (SD = 2.11). A total of 63.6% of patients presented with low adherence, 29.5% presented with moderate adherence, and 7.6% presented with high adherence. The Pearson correlation results showed that medication literacy (r = 0.342, P < 0.01) as a whole variable and the three dimensions of knowledge (r = 0.284, P < 0.01), attitude (r = 0.405, P < 0.01), and behavior (r = 0.237, P < 0.01) were significantly associated with medication adherence. Binary logistic regression analysis indicated that annual income [OR 1.199 (95% CI: 1.011-1.421); P = 0.037] and two dimensions of attitude [OR 2.174 (95% CI: 1.748-2.706); P = 0.000] and behavior [OR 1.139 (95% CI: 1.002-1.294); P = 0.046] in medication literacy were found to be independent predictors of medication adherence. Individuals with better attitudes and behavior literacy in medication literacy were more likely to adhere to the use of antihypertensive agents. Those who had higher annual incomes were more likely to adhere to the use of antihypertensive agents. Conclusion: The levels of medication literacy and medication adherence of hypertensive patients are suboptimal and need to be improved in China. The level of medication literacy in patients with hypertension could affect their adherence to antihypertensive drugs. It was suggested that hypertensive patients' medication adherence could be improved and driven by increasing the medication literacy level, especially in the attitude and behavior domains. Pertinent strategies that are specific to several dimensions of medication literacy should be developed and implemented in order to promote full medication literacy among hypertensive patients, thus facilitating optimal adherence and blood pressure control.

Project description:BackgroundThis study assesses the feasibility of using machine learning methods such as Random Forests (RF), Artificial Neural Networks (ANN), Support Vector Regression (SVR) and Self-Organizing Feature Maps (SOM) to identify and determine factors associated with hypertensive patients' adherence levels. Hypertension is the medical term for systolic and diastolic blood pressure higher than 140/90 mmHg. A conventional medication adherence scale was used to identify patients' adherence to their prescribed medication. Using machine learning applications to predict precise numeric adherence scores in hypertensive patients has not yet been reported in the literature.MethodsData from 160 hypertensive patients from a tertiary hospital in Kuala Lumpur, Malaysia, were used in this study. Variables were ranked based on their significance to adherence levels using the RF variable importance method. The backward elimination method was then performed using RF to obtain the variables significantly associated with the patients' adherence levels. RF, SVR and ANN models were developed to predict adherence using the identified significant variables. Visualizations of the relationships between hypertensive patients' adherence levels and variables were generated using SOM.ResultMachine learning models constructed using the selected variables reported RMSE values of 1.42 for ANN, 1.53 for RF, and 1.55 for SVR. The accuracy of the dichotomised scores, calculated based on a percentage of correctly identified adherence values, was used as an additional model performance measure, resulting in accuracies of 65% (ANN), 78% (RF) and 79% (SVR), respectively. The Wilcoxon signed ranked test reported that there was no significant difference between the predictions of the machine learning models and the actual scores. The significant variables identified from the RF variable importance method were educational level, marital status, General Overuse, monthly income, and Specific Concern.ConclusionThis study suggests an effective alternative to conventional methods in identifying the key variables to understand hypertensive patients' adherence levels. This can be used as a tool to educate patients on the importance of medication in managing hypertension.

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Associations between patient factors and medication adherence: A Jordanian experience.

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Associations between patient factors and medication adherence: A Jordanian experience.

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