Lowering Cost Share May Improve Rates of Home Glucose Monitoring Among Patients with Diabetes Using Insulin

The Barriers to Insulin Therapy Initiation in Type 2 Diabetes Patients: A Study of General Practitioner Perceptions in Huinan Community in South Shanghai

Background

Despite the demonstrated benefits of insulin therapy, many general practitioners (GPs) are hesitant to administer it due to challenges such as a lack of knowledge, time constraints, and patient reluctance. The barriers that prevent a GP from initiating insulin therapy may vary in comparison to those encountered by a diabetic patient; this aspect of clinical research in the South Shanghai metropolitan area has received limited attention so far.

Objective

This is a 6-months of interventional analytic cohort study. The prime aim is to investigate the barriers general practitioners (GPs) face when initiating insulin therapy for patients with type 2 diabetes (T2D).

Materials and Methods

As part of a training program, all 189 registered GPs in Nanhui Health Service Center in Shanghai were given a structured online-multi-choice questionnaire before and after a six-month interval, during which the GPs received sessions of training on insulin therapy either on theoretic classes or clinical practices.

Results

Before and after training, via the methods of multiple-response analyses, the results showed that social, GP's, and patient barriers to initiating insulin therapy were comparable. However, through the crosstabs chi-square test, we found significant changes in the basal insulin initiation following the prescription of the senior endocrinologists, the titration of insulin, and the need for training (p<0.05). The Spearman analyses discovered significant changes associated with the cause of initial insulin refusal and the factors influencing insulin administration. Finally, the binary logistic regression analysis revealed that distinct causes such as social factors, insurance, GP experience, insulin dosage calculation, follow-up, and patients' feelings are related to insulin treatment application before and after training.

Conclusion

According to this study, training increased general practitioners' confidence in initiating insulin administration, especially basal insulin. General practitioners require additional education on insulin therapy, with a potential need for increased face-to-face training for insulin initiation.

The COVID-19 Pandemic and Access to Selected Ambulatory Care Services Among Populations With Severely Uncontrolled Diabetes and Hypertension in Massachusetts

OBJECTIVES

The outbreak of COVID-19 in Massachusetts may have reduced ambulatory care access. Our study aimed to quantify this impact among populations with severely uncontrolled diabetes and hypertension; these populations are at greatest risk for adverse outcomes caused by disruptions in care.

METHODS

We analyzed multidisciplinary ambulatory electronic health record data from MDPHnet. We established 3 cohorts of patients with severely uncontrolled diabetes and 3 cohorts of patients with severely uncontrolled hypertension using 2017, 2018, and 2019 data, then followed each cohort through the subsequent 15 months. For the diabetes cohorts, we generated quarterly counts of glycated hemoglobin A1c (HbA1c) tests. For the hypertension cohorts, we generated monthly counts of blood pressure measurements. Finally, we assessed telehealth use among the 2019 diabetes and hypertension cohorts from January 2020 through March 2021.

RESULTS

HbA1c testing and blood pressure monitoring dropped considerably during the pandemic compared with previous years. In the 2019 diabetes cohort, HbA1c measurements declined from 44.0% in January-March 2020 (baseline) to 15.9% in April-June 2020 and was 11.8 percentage points below baseline in January-March 2021. In the 2019 hypertension cohort, blood pressure measurements declined from 40.0% in January 2020 to 4.5% in April 2020 and was 23.5 percentage points below baseline in March 2021. Telehealth use increased precipitously during the pandemic but was not uniform across subpopulations.

CONCLUSIONS

Access to selected diabetes and hypertension services declined sharply during the pandemic among populations with severely uncontrolled disease. Although telehealth is an important strategy, ensuring equity in access is essential. Telehealth hybrid models can also minimize disruptions in care.

Stressful life events, parental psychosocial factors, and glycemic management in school-aged children during the 1 year follow-up of new-onset type 1 diabetes

OBJECTIVE

To monitor occurrence of stressful life events, assess correlations with family functioning and parental psychosocial measures, and examine the impact of stressful life events on diabetes management in the first year after diagnosis of type 1 diabetes (T1D) in children using a mixed methods design.

METHODS

In a prospective study of 5- to 9-year-olds with recent-onset T1D (mean age 7.4 ± 1.3 years, T1D duration 4.7 ± 3.3 months), we monitored glycated hemoglobin A1c (HbA1c), income, job status, family health, and marital status at baseline and every 3 months up to 1 year. We measured coping, parental depression, and diabetes family conflict at baseline.

RESULTS

Of 128 families, 53.9% (n = 69) reported 1+ stressful event, with 25.8% reporting income change (n = 33) during this period, 23.4% additional family health changes (n = 30), 22.7% job changes (n = 29), 21.9% changes in child's school (n = 28), and 3.9% changes in marital status (n = 5). Baseline active avoidance coping, parental depression, and diabetes family conflict correlated with a higher number of stressful life events (r = 0.239, P < .01; r = 0.197, P < .05; r = 0.225, P < .01, respectively). There were also cross-sectional associations between HbA1c and income decrease, school change, and job change at various time points in the study.

CONCLUSIONS

Families can experience concurrent life stressors during the first year of T1D, which relate to coping, depression, and conflict. Consistent with existing literature, stressful life events relate to glycemic management. Future research should explore the individual's or parent's perception of stress and ways that diabetes centers can effectively assist families of youth with T1D and concurrent life stressors.

A Review of Research Progress on Glycemic Variability and Gestational Diabetes

Gestational diabetes mellitus (GDM) is associated with many adverse obstetric outcomes and neonatal outcomes, including preeclampsia, Cesarean section, and macrosomia. Active screening and early diabetes control can reduce the occurrence of adverse outcomes. Glycosylated hemoglobin (HbA1c) only reflects average blood glucose levels, but not glycemic variability (GV). Studies have shown that GV can cause a series of adverse reactions, and good control of GV can reduce the incidence of adverse pregnancy outcomes in patients with GDM. In order to provide clinicians with a better basis for diagnosis and treatment, this study reviewed the measurement, evaluation, and control of GV, the importance of GV for patients with GDM, and correlations between GV and maternal and neonatal outcomes.

Glycemic Variability: How to Measure and Its Clinical Implication for Type 2 Diabetes

Glycated hemoglobin A1c (A1C) levels have traditionally been the gold standard for assessing glycemic control and treatment efficacy in patients with type 2 diabetes. However, A1C does not take into account fluctuations in blood glucose levels known as glycemic variability (GV). In recent years, GV has become increasingly clinically relevant, because of a better understanding of the need to reach target A1C while avoiding hypoglycemia. GV relates to both hyperglycemia and hypoglycemia, and has been associated with poorer quality of life. Diabetes treatments targeting multiple pathophysiological mechanisms are most beneficial in controlling A1C and reducing GV. In clinical trials, a number of metrics are used to measure GV, many of which are not well understood in the clinical practice. Until a gold standard metric for GV is established, the variety of measurements available may confound the choice of an optimal treatment for an individual patient.