The Problem: Adherence to medication and recommended self-care activities for managing T2DM is suboptimal and can increase disease complexity, onset of retinopathy, end-stage renal disease and other complications. According to the CDC, only 23.8% of adults with diabetes met the recommended goals of physical activity per week and 56.8% of adults between the ages of 40 and 75 were on recommended statin therapy.
MEMOTEXT’s experience in T2DM and SUPD population engagement and support spans 10 years and has been refined, validated and improved with Vanderbilt University Medical Center, Boots Pharmacies (UK) and Humana.
What is Diabetes Behaviour Change?
The MEMOTEXT REACH adaptive SMS engagement program listens, learns, supports and motivates.
Clinically and commercially validated, the MEMOTEXT REACH framework and content package is aimed at helping individuals improve adherence, lower HbA1c and make healthy lifestyle changes. Educational messages are categorized as related to: medication, disease, lifestyle and diet. Support messages are categorized as related to: motivation, tailored tips, goals and feedback on progress. The intervention can include pre-segmentation into cohorts based on adherence categorizations based on claims data.
Customized Interventions used by: Vanderbilt University Medical Center, Boots Pharmacy UK, Green Shield Canada and Humana.
T2DM Adherence and the REACH Framework
The program is design to support adults with type 2 diabetes in their self-care and help them improve their HbA1c numbers, through self-monitoring and providing feedback on their progress. Messages are personalized and segmented based on each patient’s barriers. Different barriers include: having behavioural skills to take medication, having sufficient motivation and having the right information to know why taking medication is important.
Predictive Analytic & ChatBots
MEMOTEXT Data Science has validated a series of feature predictors to address clinical business needs such as: identifying high cost plan members, drug switching in early stage treatment, and likelihood of disease onset.
Machine learning allows digital health interventions and higher touch resources to be proactively targeted to the right people. Some of these features include demographics, medication utilization, drug-level specific information, suspected diagnoses and claiming patterns. Outcomes from a study conducted showed an 83% accuracy in prediction.
To increase program engagement an intake assessment chat bot based on a validated Pre-Diabetes risk assessment has been shown to increase recruitment/enrolment completion rates.
The ChatBot determines the level of risk for Pre-Diabetes and can determine and provide tools and resources available to help manage and/or reverse the risk. It will also collect information to help with segmentation for the educational and supportive messages.
The program helps to prevent disease and reduces associated costs, supports at risk adults with through healthy lifestyle promotion, increase engagement and collects real world data for future analytic initiatives. The program provides participants with accurate information and support to help self manage their condition and remain adherent.
Results from previous studies with type 2 diabetes have shown improved medication adherence and improved dietary decisions at 6 and 12 months and improved diabetes self-efficacy. Typical response rates to Diabetes engagement programs are very high (+90% over 12 months). The research study completed with the Vanderbilt University Medical Center showed enhanced awareness about non adherence, increased accountability and gave participants the feeling of being cared about. 92% of participants stated they would sign up for the study again. See the study here.
The research team from Vanderbilt University Medical center included Lyndsay Nelson, PhD and Lindsay Mayberry, M.S., PhD.
Lindsay Mayberry, M.S., PhD is an assistant professor of medicine in the Division of General Internal Medicine and Public Health at Vanderbilt University Medical Center. She has created and evaluated interventions to support and maintain behavioural health changes in adults.
Lyndsay Nelson, PhD is a research assistant professor of medicine in the Division of General Internal Medicine and Public Health at Vanderbilt University Medical Center. Her research is based in self-care promotion and technology-based health interventions for diabetes.