Medication Adherence Among Hypertensive Patients Taking Metoprolol Using Prescriptions Data from Estonian Medical Prescription Center

Name
Ulvi Kuusik
Abstract
Poor adherence to prescribed medications is a major cause of treatment failure, particularly in chronic diseases such as hypertension. The Master’s thesis analyzes the medical adherence of patients with a diagnosis of hypertension based on prescription data from the Estonian Medical Prescription Center by analyzing the prescription refill rates for the metoprolol. There were 7631 patients in the sample who were prescribed metoprolol with an I10 diagnosis, 66% of whom were women and 34% of men. The study results showed that the proportion of patients with good adherence was 63.6%.
The WHO framework was used to examine the factors influencing treatment adherence. It divides the factors into five areas: social and economic, health care system, health condition, therapy, and patient. The results showed that age had a positive effect on adherence to treatment, while the association changes with older age: adherence is lower in patients over 80 years of age than in those aged 61-80 years. Women were found to be significantly more adherent than men. The duration of treatment has a positive effect on adherence: a statistically significant relationship was found with the length of treatment (duration in months) and also the number of prescriptions. The effect of the number of diagnoses on treatment adherence was not found in this study. The adherence to metoprolol treatment was statistically significantly different with some diagnoses. There was a statistically significant difference in the treatment adherence between the two groups of patients: where only uncomplicated hypertension (I10) was diagnosed, a lower adherence rate based on metoprolol purchase rates was detected than in those where an I10 diagnosis at some point became an I11 diagnosis. Patients who buy out better all other prescriptions also have a higher refill rate for the active substance metoprolol.
Graduation Thesis language
Estonian
Graduation Thesis type
Master - Conversion Master in IT
Supervisor(s)
Marek Oja, PhD
Defence year
2022
 
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