Adherence to oral hypoglycaemic medications and the impact on diabetic biomarkers and clinical outcomes

Abstract

Introduction Improving adherence to appropriately prescribed medications enhances clinical outcomes. To our knowledge, there is scarce literature on the implementation and outcomes of an adherence support service when provided as “routine” or real-world care. Determination of the adherence level within the large population is challenging and increasing access to administrative data can be useful to face this challenge. The aim of this thesis was to determine medication adherence, to study factors influencing adherence, and to determine the influence of a medication use review (MUR) service on adherence. Methods This thesis used centrally-held dispensing data (Pharmhouse) to determine the medication adherence by estimating the proportion of days covered (PDC) in patients taking oral hypoglycaemics (OHG). The influence of patient demographics, type of therapy, and co-dispensing (polypharmacy) on adherence was evaluated. In a separate study MUR records were analyzed to determine the medication adherence which was then correlated to the clinical biomarkers from pathological report. Results Within the study region, 54.5% of patients receiving OHG were non-adherent (PDC < 80%). Non-adherence was significantly higher in men, NZ Māori ethnic group, young and middle ages (21 to 60 years) and low income group. Based on the type of therapy i.e. monotherapy, a combination of two and a combination of three OHG, the non-adherence was found to be 42.2%, 77.4%, and 93.3% respectively. Polypharmacy was significant in elder patients (age 61 years and above). Based on the polypharmacy status i.e. Non-poly, Poly with 5, Poly with 6, Poly with 7, Poly with 8, Poly with 9 and Excess polypharmacy (10 or 10+), the non-adherence (PDC < 80%) was found to be 60.9%, 49.5%, 46.8%, 47.7%, 41.8%, 43.1% and 37.5% respectively. People with high adherence (MUR score 3/4) had decreasing HbA1c or lipid levels and conversely, the people with poor adherence (MUR score 1/2) continued to show an increase in HbA1c or lipid levels with time. Discussion Non-adherence is a preventable public health burden if identified, and corrected early. Therefore, identification of medication non-adherence (prevalence, nature and cause) is the most important step for developing the strategies for adherence improvement. The observation from this thesis reporting non-adherence (PDC <80%) in 54.5% patients taking OHG was consistent with other published studies. Gender, ethnicity, and socioeconomic status had a significant influence on the rate of non-adherence. Many published studies from the literature have reported non-adherence in patients with polypharmacy. Contrary to these studies, this thesis observed that there was higher adherence in patients with polypharmacy. This thesis has investigated the impact of a structured adherence service when offered in a “real life” setting and indicated that for those patients who had follow-up visits, adherence was improved. Importantly there was a positive impact of this adherence on clinical biomarkers such as HbA1c and lipid profile. Compiling data on dispensing records and hospitalization information may allow longer-term tracking of the clinical outcomes of medication review services. Conclusion The pharmacy dispensing records can be used to identify the patients with medication non-adherence so that the adherence improvement strategies can be implemented. Pharmacists performing an adherence support service can positively influence medication adherence and clinical outcomes.