Insights into the Feasibility and Acceptability of a Mobile Insulin Titration Application in Clinical Practice and Its Effects on Diabetes Outcomes.

Introduction: Insulin therapy is most effective if patients learn how to properly adjust insulin to achieve glycaemic targets. There is a need for methods and tools that can assist these processes in clinical practice. The purpose of this feasibility study was to evaluate an approach to support insulin dose adjustment in individual patients using a mobile titration application (app). Methods: A cohort of adults (N=36) with type 2 diabetes with suboptimal glycaemia who were starting basal insulin self-titration were trained by a diabetes care and education specialist to use a mobile titration app to guide adjusting insulin doses. Glycaemia, diabetes distress and patient and provider satisfaction were assessed during the first 3 months after initiating basal insulin titration using the mobile app. Results: Mean haemoglobin type A1c (HbA1c) was significantly reduced by an average of 2.1 ± 2.2% from baseline to 3 months (p<0.001). Diabetes distress significantly decreased from baseline to follow-up with scores going down (or improving) across all scales. Both patients and providers reported high levels of satisfaction and positive experiences. Conclusion: The model offers a promising solution to streamline insulin dosage adjustments to achieve specific clinical and self-management goals with high expectations for long-term benefits and warrants further investigation.

Access to Specialty Care for Commercially Insured Youths With Type 1 and Type 2 Diabetes.

Importance: Youths with type 2 diabetes are at higher risk for complications compared with peers with type 1 diabetes, though few studies have evaluated differences in access to specialty care. Objective: To compare claims with diabetes specialists for youths with type 1 vs type 2 diabetes and the association between specialist claims with multidisciplinary and acute care utilization. Design, Setting, and Participants: This cross-sectional study used Optum Clinformatics Data Mart commercial claims. Individuals included in the study were youths younger than 19 years with type 1 or 2 diabetes as determined by a validated algorithm and prescription claims. Data were collected for youths with at least 80% enrollment in a commercial health plan from December 1, 2018, to December 31, 2019. Statistical analysis was performed from September 2022 to January 2024. Main Outcomes and Measures: The primary outcome was the number of ambulatory claims from an endocrine and/or diabetes physician or advanced practice clinician associated with a diabetes diagnosis code; secondary outcomes included multidisciplinary and acute care claims. Results: Claims were analyzed for 4772 youths (mean [SD] age, 13.6 [3.7] years; 4300 [90.1%] type 1 diabetes; 472 [9.9%] type 2 diabetes; 2465 [51.7%] male; 128 [2.7%] Asian, 303 [6.4] Black or African American, 429 [9.0%] Hispanic or Latino, 3366 [70.5%] non-Hispanic White, and 546 [11.4%] unknown race and ethnicity). Specialist claims were lower in type 2 compared with type 1 diabetes (incidence rate ratio [IRR], 0.61 [95% CI, 0.52-0.72]; P < .001) in propensity score-weighted analyses. The presence of a comorbidity was associated with increased specialist claims for type 1 diabetes (IRR, 1.07 [95% CI, 1.03-1.10]) and decreased claims for type 2 diabetes (IRR, 0.77 [95% CI, 0.67-0.87]). Pooling diagnosis groups and adjusted for covariates, each additional specialist claim was associated with increased odds of a claim with a diabetes care and education specialist (odds ratio [OR], 1.31 [95% CI, 1.25-1.36]), dietitian (OR, 1.14 [95% CI, 1.09-1.19]), and behavioral health clinician (OR, 1.16 [95% CI, 1.12-1.20]). For acute care claims, each additional specialist claim was associated with increased odds of admission (OR, 1.17 [95% CI, 1.11-1.24]) but not for emergency claims (OR, 1.03 [95% CI, 0.98-1.82]). Conclusions and Relevance: This cross-sectional study found that youths with type 2 diabetes were significantly less likely to have specialist claims despite insurance coverage, indicating other barriers to care, which may include medical complexity. Access to diabetes specialists influences engagement with multidisciplinary services. The association between increasing ambulatory clinician services and admissions suggests high utilization by a subgroup of patients at greater risk for poor outcomes.

School-based diabetes care: A national survey of U.S. pediatric diabetes providers.

Objectives: To understand the practices, attitudes, and beliefs of type 1 diabetes (T1D) providers towards school-based diabetes care (SBDC), including counseling families and communicating with schools, and explore the barriers and facilitators which affect their support of SBDC. Research Design and Methods: We conducted a national survey of pediatric T1D providers about their perceived support of SBDC, including family counseling and school communication. We used descriptive statistics to analyze results and explored differences by practice size (<500, 500-999, and ≥1000 patients) and environment (academic vs non-academic). Results: A total of 149 providers completed the survey. Nearly all (95%) indicated SBDC was very important. Though most (63%) reported counseling families about SBDC multiple times per year, few (19%) spoke with school staff routinely, reporting that was a shared responsibility among different providers. Close to 90% agreed school feedback on T1D management plans would be helpful, yet only 31% routinely requested this input. Moderate to extremely significant barriers to SBDC communication included internal factors, such as staff resources (67%) and time (82%), and external factors, such as school nurse education needs (62%) and differing school district policies (70%). Individuals from large or academic practices reported more barriers in their knowledge of SBDC, including federal/state laws. Desired facilitators for SBDC included a designated school liaison (84%), electronic transmission for school forms (90%), and accessible school staff education (95%). Conclusions: Though providers universally agree that SBDC is important, there are multilevel internal (practice) and external (policy) barriers to facilitating a bidirectional relationship between schools and health teams.

School Nurse Confidence with Diabetes Devices in Relation to Diabetes Knowledge and Prior Training: A Study of Convergent Validity.

Objective: The Diabetes Device Confidence Scale (DDCS) is a new scale designed to evaluate school nurse confidence with diabetes devices. We hypothesized that DDCS score would be associated with related constructs of school nurse diabetes knowledge, experience, and training. Research Design and Methods: In a cross-sectional study, we co-administered the DDCS and Diabetes Knowledge Test 2 (DKT2) questionnaires to school nurses in Pennsylvania. We summarized DDCS scores (range 1-5) descriptively. We evaluated the relationship between DKT2 percent score and DDCS mean score with the Spearman correlation coefficient. Simple linear regression examined school nurse characteristics as predictors of DDCS score. Results: A total of 271 completed surveys were received. Mean DDCS score was 3.16±0.94, indicating moderate confidence with devices overall. School nurses frequently reported low confidence in items representing specific skills, including suspending insulin delivery (40%), giving a manual bolus (42%), knowing when to calibrate a continuous glucose monitor (48%), changing an insulin pump site (54%), and setting a temporary basal rate (58%). Mean DKT2 score was 89.5±0.1%, which was weakly but not significantly correlated with DDCS score (r=0.12, p=0.06). Formal device training (p<0.001), assisting ≥5 students with diabetes devices in the past 5 years (p<0.01), and a student caseload between 1000-1500 students (p<0.001) were associated with higher mean DDCS score. Conclusions: DDCS score is related to prior training and experience, providing evidence for the scale's convergent validity. The DDCS may be a useful tool for assessing school nurse readiness to use devices and identify areas to enhance knowledge and practical skills.

Comparisons of school-day glycemia in different settings for children with type 1 diabetes using continuous glucose monitoring.

Objective: Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and non-school time. Methods: We conducted a retrospective analysis of CGM metrics in children 7-12 years (n=217, diabetes duration 3.5±2.5 years, hemoglobin A1c 7.5±0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school. Results: Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) lower, for weekends and virtual school (p<0.001). Hour and setting exhibited a significant interaction for several metrics (p<0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p=0.006), lower hemoglobin A1c (p<0.001), and insulin pump use (p=0.02) were associated with higher TIR in-school. Conclusion: Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines.

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.

Development and psychometric analysis of the Diabetes Device Confidence Scale for school nurses.

BACKGROUND: School nurses need to be equipped to help students with diabetes devices. No existing tools assess school nurse self-efficacy in using devices. OBJECTIVE: To develop and evaluate the psychometric properties of a novel scale to measure school nurse confidence with diabetes devices. RESEARCH DESIGN AND METHODS: We generated a list of items with community partners and examined logical validity. We then revised and distributed the item set to school nurses in Pennsylvania to examine aspects of structural validity, convergent validity, and internal consistency reliability. We used item response theory to refine the scale. RESULTS: Facilitated discussion with collaborators generated an initial list of 50 potential items. Based upon the item-content validity index, we revised/eliminated 13 items. School nurses (n = 310) in Pennsylvania completed an updated 38-item scale; the majority had experience with insulin pumps or continuous glucose monitors. Exploratory factor analysis identified a one-factor solution, suggesting a unidimensional scale. We eliminated 13 additional items based upon significant inter-item correlation or skewed response patterns. Item response theory did not identify additional candidate items for removal. Despite a high degree of redundancy (Cronbach's alpha > 0.90), we retained all remaining items to maximize the future utility of the scale. CONCLUSION: The 25-item, unidimensional Diabetes Device Confidence Scale is a new tool to measure school nurse confidence with diabetes devices. This scale has future clinical, programmatic, and research applications. Combined with knowledge assessments, this scale can serve to evaluate school nurse device use readiness, assess training gaps, and tailor interventions.

Sex differences in glycemic measures, complications, discharge disposition, and postdischarge emergency room visits and readmission among non-critically ill, hospitalized patients with diabetes.

INTRODUCTION: The purpose of this prospective observational cohort study was to examine sex differences in glycemic measures, diabetes-related complications, and rates of postdischarge emergency room (ER) visits and hospital readmissions in non-critically ill, hospitalized patients with diabetes. RESEARCH DESIGN AND METHODS: Demographic data including age, body mass index, race, blood pressure, reason for admission, diabetes medications at admission and discharge, diabetes-related complications, laboratory data (hematocrit, creatinine, hemoglobin A1c, point-of-care blood glucose measures), length of stay (LOS), and discharge disposition were collected. Patients were followed for 90 days following hospital discharge to obtain information regarding ER visits and readmissions. RESULTS: 120 men and 100 women consented to participate in this study. There were no sex differences in patient demographics, diabetes duration or complications, or LOS. No differences were observed in the percentage of men and women with an ER visit or hospital readmission within 30 (39% vs 33%, p=0.40) or 90 (60% vs 49%, p=0.12) days of hospital discharge. More men than women experienced hypoglycemia prior to discharge (18% vs 8%, p=0.026). More women were discharged to skilled nursing facilities (p=0.007). CONCLUSIONS: This study demonstrates that men and women hospitalized with an underlying diagnosis of diabetes have similar preadmission glycemic measures, diabetes duration, and prevalence of diabetes complications. More men experienced hypoglycemia prior to discharge. Women were less likely to be discharged to home. Approximately 50% of men and women had ER visits or readmissions within 90 days of hospital discharge. TRIAL REGISTRATION NUMBER: NCT03279627.

Effects of an integrated mindfulness intervention for veterans with diabetes distress: a randomized controlled trial.

INTRODUCTION: US military veterans have disproportionately high rates of diabetes and diabetes-related morbidity in addition to being at risk of comorbid stress-related conditions. This study aimed to examine the effects of a technology-supported mindfulness intervention integrated into usual diabetes care and education on psychological and biobehavioral outcomes. RESEARCH DESIGN AND METHODS: Veterans (N=132) with type 1 or 2 diabetes participated in this two-arm randomized controlled efficacy trial. The intervention arm received a one-session mindfulness intervention integrated into a pre-existing program of diabetes self-management education and support (DSMES) plus one booster session and 24 weeks of home practice supported by a mobile application. The control arm received one 3-hour comprehensive DSMES group session. The primary outcome was change in diabetes distress (DD). The secondary outcomes were diabetes self-care behaviors, diabetes self-efficacy, post-traumatic stress disorder (PTSD), depression, mindfulness, hemoglobin A1C (HbA1C), body weight, and blood pressure. Assessments were conducted at baseline, 12 weeks, and 24 weeks. Participant satisfaction and engagement in home practice were assessed in the intervention group at 12 and 24 weeks. RESULTS: Intention-to-treat group by time analyses showed a statistically significant improvement in DD in both arms without significant intervention effect from baseline to 24 weeks. Examination of distal effects on DD between weeks 12 and 24 showed significantly greater improvement in the intervention arm. Improvement in DD was greater when baseline HbA1C was <8.5%. A significant intervention effect was also shown for general dietary behaviors. The secondary outcomes diabetes self-efficacy, PTSD, depression, and HbA1C significantly improved in both arms without significant intervention effects. Mindfulness and body weight were unchanged in either group. CONCLUSIONS: A technology-supported mindfulness intervention integrated with DSMES showed stronger distal effects on DD compared with DSMES control. Examination of longer-term outcomes, underlying mechanisms, and the feasibility of virtual delivery is warranted. TRIAL REGISTRATION NUMBER: NCT02928952.

A Risk Stratification Approach to Allocating Diabetes Education and Support Services.

The objective of this study was to describe a predictive modeling approach to risk stratify people with type 2 diabetes for diabetes self-management education and support (DSMES) services. With data from a large health system, a predictive model including age, glycated hemoglobin (HbA1c), and insulin use among other factors, was developed to assess risk of future high HbA1c. The model was retrospectively applied to a cohort of people who received DSMES over a 2-year period to assess the impact of DSMES on glycemia by risk strata. Of 6934 eligible people, 4014 (58%) were in the composite low-risk group and 2604 (38%) were in the composite high-risk group. Mean HbA1c change after DSMES was -0.38% in the low-risk group and -0.84% in the high-risk group. This analysis demonstrates the potential application of predictive modeling as one approach to target DSMES resources to people who will benefit most.

Implications of the School Day on Health Behaviors for Children With Type 1 Diabetes: A Survey of Parent Perspectives During the COVID-19 Pandemic.

PURPOSE: The purpose of this study is to survey parents of youth with type 1 diabetes during the COVID-19 pandemic with school closures to better understand the implications of the school day on health care behaviors. METHODS: A cross-sectional, online survey was distributed to parents of youth with type 1 diabetes ≤19 years of age in a large, academic diabetes center. Questions encompassed perceived changes in management behaviors and plans for return to school. Subgroup analysis compared parent responses by child's age, reported stressors, and socioeconomic markers. RESULTS: Parents reported a worsening in their child's diabetes health behaviors during school closures compared to what they perceived during a regular school day before the pandemic. More than half of parents reported feeling that their child was unable to maintain a normal routine, with particular implications for snacking between meals, daily physical activity, and sleep habits. Families with adolescents or those experiencing multiple pandemic-related stressors reported greater challenges. In open-ended responses, families highlighted difficulty in balancing school, work, and diabetes care and expressed concerns about the mental health repercussions of school closures for their children. Nearly half of parents reported being at least moderately worried about return to school, whereas only a minority reported seeking guidance from their diabetes provider. CONCLUSIONS: Parent-reported disruptions of school-day routines frequently had adverse consequences for diabetes management in this population. These findings highlight the importance of a school-day routine for children with type 1 diabetes; during closures, families may benefit from mitigating strategies to maintain effective habits.

Effect of a Primary Care-Based Diabetes Education Model on Provider Referrals and Patient Participation.

PURPOSE: The purpose of this study was to evaluate the impact of a primary care (PC)-based delivery model on diabetes self-management education and support (DSMES) referrals and participation. Despite evidence that DSMES is a critical component of diabetes care, referrals and participation remain low. METHODS: PC practices were assigned to the intervention (n = 6) or usual care (n = 6). Intervention practices had direct access to a diabetes educator (DE) and applied patient-centered medical home elements to DSMES delivery. Usual care practices referred patients to traditional hospital-based outpatient DSMES programs. DSMES referrals and participation were examined for patients with diabetes, 18 to 75 years old, presenting to PC over 18 months (n = 4,894) and compared between groups. RESULTS: Compared to the usual care group, a higher percentage of patients in the intervention practices were referred to DSMES (18.4% vs 13.4%; P < .0001), and of those referred, a higher percentage of patients in the intervention practices participated in DSMES (34.9% vs 26.1%; P = .02). Patient-level factors predicting referrals were obesity (odds ratio [OR] = 1.6), higher A1C (OR = 1.4), female (OR = 1.3), and younger age (OR = 0.98). The only patient-level factor that predicted DSMES participation was lower A1C (OR = 0.9). CONCLUSIONS: This study demonstrates the positive influence of a PC-based intervention on DSMES referral and participation. However, modest improvements in DSMES rates, even with targeted efforts to address reported barriers, raise questions as to what is truly needed to drive meaningful change.

2017 National Standards for Diabetes Self-Management Education and Support.

PURPOSE: The purpose of this study is to review the literature for Diabetes Self-Management Education and Support (DSMES) to ensure the National Standards for DSMES (Standards) align with current evidence-based practices and utilization trends. METHODS: The 10 Standards were divided among 20 interdisciplinary workgroup members. Members searched the current research for diabetes education and support, behavioral health, clinical, health care environment, technical, reimbursement, and business practice for the strongest evidence that guided the Standards revision. RESULTS: Diabetes Self-Management Education and Support facilitates the knowledge, skills, and ability necessary for diabetes self-care as well as activities that assist a person in implementing and sustaining the behaviors needed to manage their condition on an ongoing basis. The evidence indicates that health care providers and people affected by diabetes are embracing technology, and this is having a positive impact of DSMES access, utilization, and outcomes. CONCLUSION: Quality DSMES continues to be a critical element of care for all people with diabetes. The DSMES services must be individualized and guided by the concerns, preferences, and needs of the person affected by diabetes. Even with the abundance of evidence supporting the benefits of DSMES, it continues to be underutilized, but as with other health care services, technology is changing the way DSMES is delivered and utilized with positive outcomes.

Patient Understanding of Discharge Instructions for Home Diabetes Self-Management and Risk for Hospital Readmission and Emergency Department Visits.

OBJECTIVE: The primary objective of this study was to examine the patient comprehension of diabetes self-management instructions provided at hospital discharge as an associated risk of readmission. METHODS: Noncritically ill patients with diabetes completed patient comprehension questionnaires (PCQ) within 48 hours of discharge. PCQ scores were compared among patients with and without readmission or emergency department (ED) visits at 30 and 90 days. Glycemic measures 48 hours preceding discharge were investigated. Diabetes Early Readmission Risk Indicators (DERRIs) were calculated for each patient. RESULTS: Of 128 patients who completed the PCQ, scores were similar among those with 30-day (n = 31) and 90-day (n = 54) readmission compared with no readmission (n = 72) (79.9 ± 14.4 vs 80.4 ± 15.6 vs 82.3 ± 16.4, respectively) or ED visits. Clarification of discharge information was provided for 47 patients. PCQ scores of 100% were achieved in 14% of those with and 86% without readmission at 30 days (P = .108). Of predischarge glycemic measures, glycemic variability was negatively associated with PCQ scores (P = .035). DERRIs were significantly higher among patients readmitted at 90 days but not 30 days. CONCLUSION: These results demonstrate similar PCQ scores between patients with and those without readmission or ED visits despite the need for corrective information in many patients. Measures of glycemic variability were associated with PCQ scores but not readmission risk. This study validates DERRI as a predictor for readmission at 90 days.

Sleep in Parental Caregivers and Children With Type 1 Diabetes.

The purpose of this cross-sectional, descriptive, pilot study was to examine the correlations in sleep between caregivers (≥18 years) and young (6-12 years) children with type 1 diabetes. Sleep was measured in both parent and child over 7 days using actigraphy and a sleep diary. Parents completed questionnaires on sleep, stress, depressive symptoms, and demographics. Children completed pediatric anxiety and fatigue questionnaires, and A1C (Hemoglobin A1c) was documented at clinic. Descriptive statistics and Pearson correlations were used to analyze data. Parents (N = 18, mean age: 39.3 ± 5.4 years, 100% Caucasian, 83% mothers) and children (N = 18, mean age: 9.6 ± 2.4 years, diagnosed for mean 3.0 ± 2.4 years, 66% female, mean A1C: 7.5 ± 0.8%) were recruited. Strong to moderate correlations were found for several measures including sleep measures based on actigraphy: mean sleep duration (hours; 7.6 ± 0.7 for parents and 8.8 ± 0.8 for children; r = .638, p = .004), mean sleep efficiency (r = .823, p < .001), and mean daily wake after sleep onset (minutes; r = .530, p = .024).

Cyber School Is a Marker of Youth with High-Risk Diabetes.

OBJECTIVE: To explore the health characteristics of youth with diabetes in cyber school compared with peers with diabetes in traditional brick-and-mortar schools. STUDY DESIGN: This was a single-center cross-sectional study of youth with type 1 or type 2 diabetes in K-12 education during academic year 2017-2018. Youth enrolled in cyber school were matched with traditional school peers by age, sex, race, diagnosis, and diabetes duration. Comparisons included insurance status, hemoglobin A1c, treatment, coexisting conditions, screening, and healthcare use. RESULTS: Of 1694 participants, 5% (n = 87) were enrolled in cyber school. Youth enrolled in cyber school were predominantly white (89%), female (60%), adolescents (median 15.2 years) with type 1 diabetes (91%). Youth with type 2 diabetes were excluded from analyses owing to the small sample (n = 7). Public insurance was more common among youth enrolled in cyber school (P = .005). Youth in cyber school had higher mean hemoglobin A1c, 9.1 ± 1.8% (76 ± 20 mmol/mol) vs 8.3 ± 1.2% (67 ± 13 mmol/mol) (P = .003), lower insulin pump use (OR, 0.36; 95% CI, 0.18-0.73), and more mental health conditions (OR, 4.48; 95% CI, 1.94-10.35) compared with peers in traditional schools. Youth in cyber school were less likely to have recommended vision (OR, 0.34; 95% CI, 0.15-0.75) and dental (OR, 0.33; 95% CI, 0.15-0.75) evaluations. The relationship between hemoglobin A1c and cyber school persisted after adjusting for insurance status, pump use, and mental health conditions (P = .02). Similar trends were observed for participants with type 2 diabetes. CONCLUSIONS: Youth with diabetes in cyber school may be a high-risk population. Understanding the potential impact of cyber school-related factors on health may encourage additional provider/system/school supports for these patients.