Examining a Diabetes Self-Management Education and Support Telemedicine Model With High-Risk Patients in a Rural Community.

BACKGROUND: Ongoing support is critical to diabetes self-management education and support (DSMES) effectiveness, but difficult to realize, particularly in areas with limited resources. The objective of this feasibility study was to assess the impact of a virtual support model on diabetes outcomes and acceptability with high-risk patients with type 2 diabetes in a rural community. METHODS: In a 12-month nonrandomized trial in federally qualified health centers (FQHCs), patients with hemoglobin A1c (HbA1c) >9% were referred to the Telemedicine for Reach, Education, Access, Treatment, and Ongoing Support (TREAT-ON) program where a Diabetes Care and Education Specialist provided DSMES through videoconferencing. HbA1c change was compared in 30 patients in the intervention group (IG) to a propensity score-matched retrospective control group (CG) of patients who received in-person DSMES delivered by a DCES. Changes in HbA1c, diabetes distress, empowerment, self-care and acceptability were assessed within the intervention group (IG) between those who did and did not meet self-management goals. RESULTS: The IG experienced similar significant reductions in HbA1c as the CG. Most (64%) IG participants achieved their self-management goal. Goal attainers had a significant HbA1c decrease of 0.21% every 3 months as well as significant reduction in diabetes distress and improvement in general dietary intake. Regardless of goal attainment, IG participants reported high levels of acceptability with TREAT-ON. CONCLUSIONS: This feasibility study suggests that TREAT-ON was well-received and as effective as traditional in-person DSMES. While findings augment ample evidence regarding DSMES benefits, the TREAT-ON model offers additional advantages and provides validation for telehealth to inform future practice in reaching and supporting self-management for high-risk patients in underserved areas. TRIAL REGISTRATION: Clinicaltrials.gov, # NCT04107935.

Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation.

BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face using the EHR. This study sought to assess the utility of a visual analytics dashboard in addition to EHR in managing hypertension in a primary care setting. METHODS: Primary care physicians within an urban, academic internal medicine clinic were tasked with performing 2 simulated patient encounters for hypertension management: the first using standard EHR, and the second using EHR paired with a visual dashboard. The dashboard included graphical blood pressure trends with guideline-directed targets, calculated atherosclerotic cardiovascular disease risk score, and relevant medications. Guideline-appropriate antihypertensive prescribing, correct target blood pressure goal, and total encounter time were assessed. RESULTS: We evaluated 70 case simulations. Use of the dashboard with the EHR compared with use of the EHR alone was associated with greater adherence to prescribing guidelines (95% vs. 62%, P < 0.001) and more correct identification of blood pressure target (95% vs. 57%, P < 0.01). Total encounter time fell an average of 121 seconds (95% confidence interval 69-157 seconds, P < 0.001) in encounters that used the dashboard combined with the EHR. CONCLUSIONS: The integration of a hypertension-specific visual analytics dashboard with EHR demonstrates the potential to reduce time and improve hypertension guideline implementation. Further widespread testing in clinical practice is warranted.