Analyzing the effects of barriers to and facilitators of medication adherence among patients with cardiometabolic diseases: a structural equation modeling approach

Reimagining Medication Adherence: A Novel Holistic Model for Hypertension Therapy

Purpose

Patients' adherence to the prescribed therapy is influenced by several personal and social factors. However, existing studies have mostly focused on individual aspects. We took a holistic approach to develop a higher-level impact factor model.

Patients and Methods

In this independent, non-interventional, cross-sectional and anonymous study design the pharmacist recruited patients who entered the pharmacy and handed in a prescription for a blood pressure medication. The patients received a paper questionnaire with a stamped return envelope to volunteer participation. A total of 476 patients in Germany who reported having at least high normal blood pressure according to the Global Hypertension Practice Guidelines were surveyed. In this study, each patient received an average of 2.49 antihypertensive prescriptions and 7.9% of all patients received a fixed-dose combination. Partial least squares structural equation modeling was performed for model analytics since it enables robust analysis of complex relationships.

Results

Emotional attitude, behavioral control, and therapy satisfaction directly explained 65% of therapy adherence. The predictive power of the out-of-sample model for the Q2-statistic was significant. The patient's overall therapy satisfaction determined medication adherence. The medication scheme's complexity also influenced the adherence levels. Therapy satisfaction was significantly shaped by the complexity of the medication scheme, behavioral control, and emotional attitude. The results demonstrated the superior performance of fixed-dose combinations against combinations of mono-agents according to the adherence level. Additionally, patient-physician and patient-pharmacist relationships influenced behavioral control of medication therapy execution. According to the A14-scale to measure the level of adherence, 49.6% of patients were classified as adherent and the remainder as non-adherent.

Conclusion

The results enable healthcare stakeholders to target attractive variables for intervention to achieve maximum effectiveness. Moreover, the proven predictive power of the model framework enables clinicians to make predictions about the adherence levels of their hypertensive patients.

Strategies for rate and rhythm control of atrial fibrillation in the ED

ABSTRACT

Atrial fibrillation (AF) is one of the most common dysrhythmias managed in the ED and accounts for more than half a million visits a year in the United States. More than 6 out of 10 of these visits result in admissions. As the prevalence of AF has continued to increase in recent years, so has the presentation of patients with AF to the ED. For these reasons, clinicians in emergency settings must be knowledgeable of evidence-based rate and rhythm control strategies for stabilizing patients and preventing complications. This article discusses options, indications, contraindications, and safe implementation of rate and rhythm control strategies for ED clinicians. Recent studies have suggested that early rhythm control may benefit newly diagnosed patients, reducing stroke risk, cardiovascular deaths, and disease progression.

A Participatory Sensing Study to Understand the Problems Older Adults Faced in Developing Medication-Taking Habits

Past research has demonstrated that older adults tend to use daily activities as cues to remember to take medications. However, they may still experience medication non-adherence because they did not select adequate contextual cues or face situations that interfere with their medication routines. This work addresses two research questions: (1) How does the association that older adults establish between their daily routines and their medication taking enable them to perform it consistently? (2) What problems do they face in associating daily routines with medication taking? For 30 days, using a mixed-methods approach, we collected quantitative and qualitative data from four participants aged 70–73 years old about their medication taking. We confirm that older adults who matched their medication regimens to their habitual routines obtained better results on time-based consistency measures. The main constraints for using daily routines as contextual cues were the insertion of medication taking into broad daily routines, the association of multiple daily routines with medication taking, the lack of strict daily routines, and the disruption of daily routines. We argue that the strategies proposed by the literature for forming medication-taking habits should support their formulation by measuring patients’ dosage patterns and generating logs of their daily activities.