Applying Patient Segmentation Using Primary Care Electronic Medical Records to Develop a Virtual Peer-to-Peer Intervention for Patients with Type 2 Diabetes

Abstract

The aim of this study was to design a virtual peer-to-peer intervention for patients with type 2 diabetes (T2D) by grouping patients from specific segments using data from primary care electronic medical records (EMRs). Two opposing segments were identified: patients living with diabetes who tend to take several medications (“medication” segment: ~32%) and patients who do not take any diabetes-specific medications (“lifestyle” segment: ~15%). The remaining patients were from two intermediate segments and exhibited medication-taking behavior that placed them midway between the medication and lifestyle segments. Patients were grouped into six workshops (two workshops in each group: medication, lifestyle, and mixed group), including individuals with good and bad control of their disease. Measures of attitudes, learning, and motivation were addressed during and after the workshops. Results showed that patients in the lifestyle segment were more interested in T2D lifestyle control strategies, more satisfied with their in-workshop learning experience, and more motivated to set a goal than those in the medication segment. These results suggest that the proposed intervention may be more viable for patients in the lifestyle segment and that EMR data may be used to tailor behavioral interventions to specific patient groups. Future research is needed to investigate different segmentation approaches (e.g., using data related to smoking, drinking, diet, and physical activity) that could help tailor the intervention more effectively.

The Electronic Medical Record—A New Look at the Challenges and Opportunities

“…The accepted papers published within this Special Issue explored numerous aspects previously unaddressed in the literature on this topic. They employed a variety of methodologies, including interviews (Campos-Castillo et al) [14], data science (Baja et al) [15], the co-design of a digital mental health intervention (DMHI) followed by workshops (Patrickson et al) [16], and an intervention in the form of workshop followed by a survey (Paplialonga et al) [17]. A number of different theories were explored, including neo-institutionalism [14], the diffusion of innovation [15], and positive deviance [17].…”

“…Paplialonga et al [17] use the central repository of EMR data to add knowledge and wisdom through research, demonstrating how data taken from a primary-care network allowed them to study an intervention that compared two distinct groups of patients with type 2 diabetes. They demonstrated how a data-driven strategy might bring valuable insights in this area of substantial challenge for health systems.…”

“…They show how the use of EMR data may be used to help support some of the most significant health issues of our time such as diabetes and mental health. The two articles in these areas [16,17] indicate the benefit of future work on how EMR can help promote more equitable health outcomes with a greater focus on prevention and wellness. Campos-Castillo et al [14] suggest further research into how EMR can promote patient-doctor face-to-face communication in a less hierarchical setting.…”