A New Look at Barriers to Clinical Care Among Appalachian Residents Living With Diabetes.

In the United States, diabetes is the seventh leading cause of death and continues to rise in prevalence, with type 2 diabetes accounting for 90-95% of all cases. Rates of diabetes in Kentucky, and, in particular, the Appalachian region, are among the highest in the nation and are increasing faster than the national average. Despite this disproportionate burden, barriers to clinical appointment attendance have not been fully explored in this population. This article examines the association among perceived barriers to clinical attendance, glycemic control, and diabetes self-care as part of an ongoing study. We used a 25-item checklist developed using the Chronic Care Model to assess participants' barriers to clinic attendance. Glycemic control was assessed via A1C measurement. Diabetes self-care was assessed using the Summary of Diabetes Self-Care Activities measure. At the time of analysis, 123 of the 356 participants (34.6%) did not report any barriers to clinic attendance. For the remainder, the major reported barriers included forgetting appointments, inability to afford medicines or other treatment, and placing faith above medical care. The average A1C was 7.7%, and the average diabetes self-care summary score was 17.1 out of 35 points (with higher values indicating better self-care). Missing clinic appointments is associated with lower health outcomes, especially in vulnerable populations. This study can help educate clinic staff on perceived barriers to type 2 diabetes management among people with diabetes in Appalachia.

Linking Postpartum and Parenting Women With a National Diabetes Prevention Program: Recruitment Efforts, Challenges, and Recommendations.

IN BRIEF Women with a history of gestational diabetes mellitus (GDM) are at higher risk for type 2 diabetes. This project piloted the National Diabetes Prevention Program lifestyle change program in cohorts of women with a history of GDM. The article describes recruitment efforts, challenges, and study participation and provides recommendations for future program implementation.

SENSING THE BIG PICTURE WITH CONTINUOUS GLUCOSE MONITORING.

When you have diabetes, monitoring your blood glucose is a crucial part of your treatment plan. Knowing your blood glucose values can help you avoid short-term problems such as hyperglycemia (high blood glucose) and hypoglycemia (low blood glucose). Ongoing optimal blood glucose control can help you prevent or delay long-term diabetes complications such as diabetes-related eye disease, kidney disease and nerve damage.

COVID-19 Impact Predicts Diabetes Distress Among Individuals With Type 2 Diabetes.

PURPOSE: The purpose of this study was to determine whether COVID-19 impact and Diabetes Self-Management Education and Support (DSMES) service attendance predicted diabetes distress among individuals with type 2 diabetes during the pandemic. METHODS: Eighty-six adults with type 2 diabetes who either attended (n = 29) or did not previously attend (n = 57) DSMES services completed a cross-sectional survey. Participants' mean age was 57 ± 12.3 years, 50% were female, and 71.3% were diagnosed with diabetes >5 years. The Coronavirus Impact Scale was used to measure impact of the pandemic on daily life. The Diabetes Distress Scale was used to measure distress overall and within 4 subscales (emotional burden, interpersonal distress, physician-related distress, regimen distress). Separate multiple linear regressions were conducted for each outcome, controlling for age, sex, marital status, financial status, and time since diabetes diagnosis. RESULTS: Higher COVID-19 impact predicted higher diabetes-related distress for all subscales and overall. Only the subscale for interpersonal distress was predicted by DSMES attendance, which decreased with DSMES attendance. CONCLUSION: This study identifies a link between the effects of the COVID-19 pandemic and diabetes distress. The findings highlight the negative impact of the pandemic on diabetes distress and the importance of DSMES services for diabetes-related distress. Interventions are needed to reduce psychological distress among this population during public health crises.

Primary Care Cluster RCT to Increase Diabetes Prevention Program Referrals.

INTRODUCTION: The Diabetes Prevention Program, an intensive lifestyle change program, effectively reduces the risk of progression from prediabetes to type 2 diabetes but is underutilized. An implementation study using formative research was undertaken to increase Diabetes Prevention Program referrals at a primary care clinic. STUDY DESIGN: A pragmatic, cluster randomized, mixed-methods study. SETTING/PARTICPANTS: Clusters were teams of primary care clinicians from 2 primary care clinics. The 3 intervention clusters had 8-11 clinicians, and the 3 control clusters had 7-20 clinicians. INTERVENTION: Implementation activities occurred from December 2017 to February 2019. The activities included targeted clinician education, a prediabetes clinician champion, and a custom electronic health record report identifying patients with prediabetes. MAIN OUTCOME MEASURES: The primary outcome was referral of patients with prediabetes to the institutional Diabetes Prevention Program. Study data, including patient demographic and clinical variables, came from electronic health record. Interviews with clinicians evaluated the implementation strategies. Generalized estimating equation analyses that accounted for multiple levels of correlation and interview content analysis occurred in 2019. RESULTS: Study clinicians cared for 2,992 patients with a prediabetes diagnosis or HbA1c indicative of prediabetes (5.7%-6.4%). Clinicians in the intervention clusters referred 6.9% (87 of 1,262) of patients with prediabetes to the Diabetes Prevention Program and those in the control clusters referred 1.5% (26 of 1,730). When adjusted for patient age, sex, race, HbA1c value, HbA1c test location, and insurance type, intervention clinicians had 3.85 (95% CI=0.40, 36.78) greater odds of referring a patient with prediabetes to the Diabetes Prevention Program. The 11 interviewed intervention clinicians had mixed opinions about the utility of the interventions, reporting the prediabetes clinic champion (n=7, 64%) and educational presentations (n=6, 55%) as most helpful. CONCLUSIONS: Intervention clinicians were more likely to make Diabetes Prevention Program referrals; however, the study lacked power to achieve statistical significance. Clinician interviews suggested that intervention components that triggered Diabetes Prevention Program referrals varied among clinicians.