Non-Adherent Behaviour and Glycaemic Control in Patients with Type 2 Diabetes Treated with Insulin

A676

VA L U E I N H E A LT H 1 9 ( 2 0 1 6 ) A 3 4 7 – A 7 6 6

Lausanne, Lausanne, Switzerland, 2School of pharmaceutical sciences, University of Geneva, Lausanne, Switzerland, 3Institute of Health Economics and Management ESSEC, Cergy-Pontoise, France, 4CHU Dijon, Dijon, France, 5MSD, Courbevoie, France, 6Observia, Paris, France, 7Medical evaluation Chair ESC Dijon, Dijon, France

Objectives: Despite significant improvements in the follow up of type 2 diabetes patients, last results of Entred 2007-2010 are showing an insufficient level of control with too many patients with HbA1C> 7%. Despite of regular controls, the physician encounter difficulties to well inform his patients due to a lack of time and means. Thanks to their expertise, number and accessibility pharmacists could play a beneficial role on patient adherence. IPhODia study aims to assess the impact on adherence of specific information provided by community pharmacists.  Methods: The intervention consists in three different 30 min interviews during 6 months, covering thematic information on diabetes. Two groups of pharmacists have been randomized, one providing interviews in addition to the usual drug delivery, one delivering drug in usual settings. The criteria for evaluation is the Medication Possession Ratio (MPR). In total 182 pharmacists (91+91) recruited 553 patients (296+257).  Results: 45% of pharmacists work in rural area, 85% have a confidentiality space and 65% have already been trained to therapeutic education (no difference between 2 groups). Patients’ main characteristics are similar in the 2 groups: gender, age, diabetes duration, percentage of overweight people, number of antidiabetic treatment. Mean HbA1c level has significantly decreased after 6 months in the group of patients who were followed with pharmacist interviews (Baseline 7,9% – 6 months 7,4%) versus the usual drug delivery group (Baseline 7,7% – 6 months 7,5%). (-0.5% – -0.2 %, (p =  0.0035 )). MPR at baseline was very high and does not change at 6 months.  Conclusions: Six months results show that information provided by community pharmacists to type 2 diabetes patients has significantly decreased HbA1c level. The MPR was very high in both group at baseline, due to this, it does not change, after 6 months. 12 months results will be presented. PDB62 Association Between Stages of Change and Medication Adherence Among Diabetic Patients in a Primary Health Care Setting in Qatar: A Preliminary Study MI1, Arafat Y1, Awaisu A1, Owusu Y1, Colagiuri

S2, AlHafiz

M3

Mohamed Ibrahim 1Qatar University, Doha, Qatar, 2The University of Sydney, Sydney, Australia, 3Primary Health Care Corporation, Doha, Qatar

Objectives: The objective of this study was to determine the association between the TTM’s Stages of Change (SOC) and medication adherence, and the relationship between SOC and glycated hemoglobin (HbA1c) among patients with T2DM in a primary healthcare setting in Qatar.  Methods: A cross‐sectional observational study was carried out among T2DM patients attending a noncommunicable diseases clinic at Mesaimeer Healthcare Center. Medication adherence was assessed using Morisky Medication Adherence Scale (MMAS‐8), and a 2‐item SOC questionnaire identified the SOC. HbA1c values were obtained from the electronic database at the clinic. Spearman rank correlation statistic was conducted at α  <  0.05.  Results: A total of 184 patients were included in the analysis; 70.7% males. The rate of low, medium, and high adherence to antidiabetic medications was 26.4%, 23.3%, and 50.3% respectively. There was a significant positive correlation between SOC and adherence score (r=  0.743, P <  0.001), but there was no significant correlation between SOC and HbA1c.  Conclusions: There was a strong positive association between SOC and medication adherence suggesting that SOC could potentially be used to identify patients at risk of low adherence. The findings are based on preliminary data and more in‐depth analyses are needed to confirm this.

PDB63 Non-Adherent Behaviour and Glycaemic Control in Patients with Type 2 Diabetes Treated with Insulin Buchs S1, Weatherall J2, DiBonaventura M3, Wisniewski T2 1Novo Nordisk A/S, Søborg, Denmark, 2Novo Nordisk Inc., Plainsboro, NJ, USA, 3Kantar Health, New York, NY, USA

Objectives: Approximately 64% of US type 2 diabetes (T2DM) patients are in poor glycaemic control. Previous studies show that a high proportion of patients in poor glycaemic control also have poor treatment adherence. The aim of this analysis was to investigate the characteristics and proportion of patients with T2DM treated with insulin that engage in non-adherent behaviour, and to assess if there is an association between non-adherent behaviour and HbA1c.  Methods: Data from the National Health and Wellness Survey (NHWS) from 2012-2013 was applied. The NHWS is an annual health questionnaire administered to a nationwide sample of adults in the US. All T2DM insulin users with non-missing HbA1c data were included (N= 2,288). The eight-item Morisky Medication Adherence Scale (MMAS-8) was used to assess the level of non-adherent behavior. Bi-and multivariate analyses were conducted to determine the association of a) the MMAS-8 score and individual items with demographic and health history factors and b) HbA1c when controlling for these factors.  Results: Among T2DM insulin users, 39.29% and 19.97% reported medium and low adherence to insulin treatment. Commonly reported non-adherent behaviours included: having difficulties remembering (33.87%), feeling hassled (30.33%) and forgetting medication (21.59%). Patients with poorer adherence were younger, had diagnosed and initiated insulin more recently, were more likely to be female, of low socioeconomic standing and to have diabetic complications (p<  0.05). In terms of HbA1c, levels were at 7.12% among those with high adherence and significantly higher at 7.31% and 7.81% among those with medium and low adherence respectively (p< 0.05). Adherent behaviour which was strongly associated with HbA1c included skipping medication, forgetting medication when traveling, forgetting medication and feeling hassled about the medication regimen (p<  0.05).  Conclusions: Non-adherent behaviour seems associated with poorer HbA1c possibly due to skipping and forgetting doses. Less stringent treatment regimens may increase adherence and therefore improve glucose control.

PDB64 Adherence to Oral Antidiabetic Medication in Type 2 Diabetes Mellitus Clients in the Volta Region of Ghana Sefah IA1, Okotah A2 1GHANA HEALTH SERVICE, KETA, Ghana, 2JOHN SNOW INC, ACCRA, Ghana

Objectives: This study sought to assess adherence to oral anti-diabetes mellitus medications and associated factors among clients reporting to four randomly selected Hospitals in the Volta region of Ghana.  Methods: A cross-sectional study was conducted among type 2 diabetes mellitus clients who attended the Diabetes Clinic of four randomly selected Hospitals in the Volta region of Ghana between the months of January 2015 to March 2015. Adherence prevalence was assessed using the eight (8)-item Morisky Medication Adherence scale. Study participants were interviewed using a structure questionnaire to, among other things, determine the commonest self-reported reason (s) of non adherence. Data generated were analyzed using SPSS version 21. Cross-tabulation analysis was performed between the adherence levels and the indicators generated from the questionnaire. Multiple logistic regression was further performed between adherence level and the statistically significant variables.  Results: Adherence prevalence rate to oral anti-diabetes in Type 2 Diabetes Mellitus was found to be 47.75%. In a multiple logistic regression analysis, the odds of adherence in respondents with fasting blood glucose of 1 – 6mmol/L was about 2-fold (OR =  1.9, 95% CI 1.128 – 3.232, p-value 002) the odds of having fasting blood glucose of above 10mmol/L while the odds of adherence among respondents with tertiary education was about 3-fold (OR= 2.888, 95% CI 1.394 – 5.982, p-value 0.004) of those with no formal education. The commonest self-reported reason for non-adherence was forgetfulness.  Conclusions: Adherence to oral anti-diabetes in type 2 diabetes mellitus was found to be suboptimal. Management of type 2 diabetes mellitus with oral anti-diabetes must include strategies to identify non-adherent clients for adherence counseling before modification of therapy in ensuring good glycaemic control and prevention of the more costly management of its complications. PDB65 Can We Predict Adherence in Diabetes Patients Based on Medication Characteristics? Meng J1, Casciano R2, Stern L2, Perrin A2, Lew E3 1LASER Analytica, Loerrach, Germany, 2LASER Analytica, New York, NY, USA, 3Sanofi, ChillyMazarin, France

Objectives: Medication adherence is an important concern for both physicians and payers. Non-adherence can lead to treatment failure and death, as well as an increase in the use of costly resources. Available literature regarding adherence tends to focus on the effect of patient attributes on therapy usage. However, it is likely that attributes specific to the therapy itself (such as adverse events) also have an effect on whether patients are adherent. The ability to predict the adherence rates for a therapy based on its characteristics, particularly in comparison to those of comparator treatments, could add significant value to a product’s profile. The study herein was performed as a feasibility analysis to determine if it is possible to predict patient adherence based on a treatment’s profile. The analysis focuses on type 2 diabetes treatments.  Methods: Relationships between individual product characteristics and product discontinuation rates were determined. Product characteristics (i.e., adverse event and success rates) were obtained from clinical trials and realworld discontinuation data were obtained from a physician survey. The products included were DPP4s, GLP-1s, basal insulins, and OADs and the attributes examined were nausea/vomiting, other GI effects, hypoglycemia, weight gain, and lack of success/efficacy. From these relationships, a predictive model was derived that would allow the user to estimate a therapy’s adherence based on its profile.  Results: The analysis found a clear correlation between weight change and discontinuation. The piecewise prediction model is as follows: Discontinuation =  0.2453*HbA1c reduction + 0.0144*weight change + 0.5090*proportion of patients with hypoglycemia + 0.0935*proportion of patients with GI side effects + 0.2368*proportion of patients with nausea/vomiting + 0.3943.  Conclusions: Despite analysis limitations, study trends suggest that it would be feasible to construct a model predicting adherence based on a treatment’s profile. Due to the link between adherence and outcomes, this topic warrants further research.

PDB66 A Proposed Holistic Conceptual Framework for Barriers to Medication Adherence in Diabetes Jaam M, Mohamed Ibrahim MI, Kheir N, Awaisu A Qatar University, Doha, Qatar

Objectives: Non-adherence to medications in patients with diabetes which results in poor clinical outcomes and increased healthcare cost is commonly reported globally. Factors associated with poor medication adherence have also been widely studied. However, interventions aimed at enhancing medication adherence have shown conflicting results with modest efficacy. These interventions usually target limited barriers, neglecting many other important factors. A clear and comprehensive conceptual framework that captures all possible factors has not been established. We aimed to develop a conceptual framework that addresses the complex network of barriers to medication adherence in patients with diabetes.  Methods: Fourteen databases and grey literature sources were systematically searched through April 2016. Systematic reviews reporting barriers to medication adherence in patients with diabetes were identified. A thematic approach was used to categorize all identified barriers from the reviews and to create a matrix representing the complex network and relations of the different barriers.  Results: Seventeen systematic reviews were used for the development of the conceptual framework. Overall, six different themes emerged: patient–, medication–, disease–, provider–, system–, and society–related factors. Each of these themes was further classified into different categories. It was noted that most interactions were identified to be within the