Establishing a Correlation between prescription analysis and medication adherence using the General Medication Adherence Scale (GMAS) in the Indian Population
Read the Magazine in PDF
Abstract
Medication non-adherence, a global concern, led to the development of the Medication Adherence Scale (GMA). This study assessed its correlation with prescription quality via GMAS in India. A pilot study validated internal consistency using a 27-element checklist for prescription quality and the DMS tool for adherence assessment. A moderately positive correlation (0.6) between prescription quality and medication adherence was observed among 150 patients. Enhancing prescription quality could enhance adherence, improve patient outcomes, and reduce financial burdens
Introduction
Medication non-adherence is a prevalent issue worldwide, with the World Health Organization (WHO) reporting that around 50% of chronically ill patients do not take medications as prescribed. This non-adherence has significant financial implications, with estimates suggesting that it costs around $280 billion per year. The issue is so severe that it prompted the development of an 11-element Medication Adherence Scale (GMA) in 2018, which was validated in 2019.
Data related to Medication non-adherence
A recent study aimed to assess the prevalence of medication non-adherence and its correlation with prescription quality. The study had three main objectives: to conduct a prescription analysis using a validated checklist; to study medication adherence and causes of non-adherence using the DMS tool; and to study the correlation between medication adherence and prescription analysis.
To achieve these objectives, a pilot study was conducted to establish internal validity. A validated checklist, formulated by the amalgamation of WHO good prescribing guidelines, literature research, and an average of new guidelines, was used to assess prescription quality. The prescriptions of 150 patients were audited and assessed for quality using this 27-element checklist. At the same time, medication adherence was assessed using the DMS tool, a patient-reported outcome measure.
The study found a moderately positive correlation between prescription quality and medication adherence, with a correlation coefficient of 0.6. This correlation was based on a sample size of 29 patients, and the study analyzed the prescriptions of 150 patients.
The prescription analysis revealed that none of the prescriptions fell into the low- or poor-quality category. However, some discrepancies were found, including unclear handwriting, a lack of allergy status mention, and no follow-up mention in 54% of the prescriptions. Polypharmacy was present in 20% of the prescriptions, while 12% of the prescriptions showed drug interactions. Medications were prescribed but not available in the hospital for 25% of the prescriptions.
The study also found that 53% of the patients were adherent, 43% were partially adherent, and only 4% were poorly adherent. Non-adherence was mostly related to patient behavior and pill burden. Demographic analysis revealed that women were more adherent than men, and age played a role in adherence, with non-adherence being more prevalent among patients below 30 or above 60 years of age.
In terms of income, the study found that patients in the high-income group were more adherent than those in the low-income group. The competitive analysis showed a moderately positive correlation between prescription quality and medication adherence, with an increase in prescription quality leading to an increase in medication adherence and vice versa.
Conclusion
The study highlights the need to address medication non-adherence and improve prescription quality. A moderately positive correlation was established between medication adherence and prescription quality, suggesting that improving prescription quality could increase medication adherence. The validated checklist used in the study could be used by other researchers in similar studies. Addressing the causes of medication non-adherence could lead to better patient care, satisfaction, and quality of life. The findings of this study could help healthcare providers improve patient outcomes and reduce the financial burden of medication non-adherence.
FAQs
Q. What was the sample size in the pilot study for ESP FM, and how did it affect the study results?
A. The sample size was relatively small during the pilot study for ESP FM. The presenter stated that the correlation coefficient obtained when the study was conducted was either zero or 0.1; the sample size for this was 784 and 583. As the correlation increased, the sample size decreased; for a correlation coefficient of 0.6, the sample size was only 29. Although this allowed the study to obtain results, the presenter acknowledged that a larger sample size would have been better for validity purposes. As a result, the researchers took a sample size of 150, which was five times larger than the suggested sample size, to obtain better results. The presenter suggested that there is room for further study to explore the correlation between these two aspects.
