Management of Type 2 Diabetes Mellitus With Noninsulin Pharmacotherapy.

Type 2 diabetes mellitus is a chronic disease that is increasing in global prevalence. An individualized approach to pharmacotherapy should consider costs, benefits beyond glucose control, and adverse events. Metformin is the first-line therapy due to its low cost and effectiveness. Sulfonylureas and thiazolidinediones are additional low-cost oral hypoglycemic classes available in the United States; however, evidence shows variability in weight gain and hypoglycemia. Thiazolidinediones increase fluid retention and are not recommended in patients with New York Heart Association class III or IV heart failure. Newer medications, including glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors, have demonstrated weight loss, reduced cardiovascular events, decreased renal disease, and improved all-cause morbidity and mortality. Sodium-glucose cotransporter-2 inhibitors are recommended for people with known cardiovascular disease, heart failure, and chronic kidney disease but carry an increased risk of urinary tract and mycotic infections. Glucagon-like peptide-1 receptor agonists are contraindicated in patients with active multiple endocrine neoplasia type 2 or a personal or family history of medullary thyroid carcinoma; adverse effects include gastrointestinal upset and pancreatitis. Dipeptidyl-peptidase-4 inhibitors have a low risk of hypoglycemia but may increase the risk of pancreatitis and require a renal dose adjustment. Public and private programs to increase access to newer hypoglycemic medications are increasing; however, there are limitations to access, particularly for uninsured and underinsured people.

A review of top cardiology and cardiovascular medicine journal guidelines regarding the use of generative artificial intelligence tools in scientific writing.

BACKGROUND: Generative Artificial Intelligence (AI) tools have experienced rapid development over the last decade and are gaining increasing popularity as assistive models in academic writing. However, the ability of AI to generate reliable and accurate research articles is a topic of debate. Major scientific journals have issued policies regarding the contribution of AI tools in scientific writing. METHODS: We conducted a review of the author and peer reviewer guidelines of the top 25 Cardiology and Cardiovascular Medicine journals as per the 2023 SCImago rankings. Data were obtained though reviewing journal websites and directly emailing the editorial office. Descriptive data regarding journal characteristics were coded on SPSS. Subgroup analyses of the journal guidelines were conducted based on the publishing company policies. RESULTS: Our analysis revealed that all scientific journals in our study permitted the documented use of AI in scientific writing with certain limitations as per ICMJE recommendations. We found that AI tools cannot be included in the authorship or be used for image generation, and that all authors are required to assume full responsibility of their submitted and published work. The use of generative AI tools in the peer review process is strictly prohibited. CONCLUSION: Guidelines regarding the use of generative AI in scientific writing are standardized, detailed, and unanimously followed by all journals in our study according to the recommendations set forth by international forums. It is imperative to ensure that these policies are carefully followed and updated to maintain scientific integrity.

Preparing Community Health Workers to Empower Latino(a)s With Diabetes: A Real-World Implementation Study.

PURPOSE: The purpose of the study was to evaluate the delivery of diabetes self-management education (DSME) to Latino(a) adults by community health workers (CHWs). METHODS: Investigators developed an evidence-based, bilingual (Spanish/English) diabetes education curriculum and trained 10 CHWs on its content. CHWs then implemented the curriculum in 6-month diabetes group visit programs for low-income Latino(a)s with type 2 diabetes in nonacademic 501(c)3 community clinics. Investigators evaluated efficacy of the training through successful implementation, measured by participant group visit acceptance and attendance. RESULTS: Participants (n = 70) reported high levels of program satisfaction (3.8/4.0), improvement in quality of life (9.7/10), meeting of individual needs (3.8/4.0), and acceptability (9.7/10.0). Content analyses revealed that 87.1% of participants would not change the program or wanted to extend it. Participant attendance was 81.6%. CONCLUSIONS: Investigators demonstrated the ability to develop a training that nonmedical personnel (CHWs) successfully implemented in a real-world study. This study provides a curricular framework for CHW-led education that may serve as a template to extend to other diseases and populations.

Implementation and Evaluation of a mHealth-Based Community Health Worker Feedback Loop for Hispanics with and at Risk for Diabetes.

BACKGROUND: Gaps in accessibility and communication hinder diabetes care in poor communities. Combining mobile health (mHealth) and community health workers (CHWs) into models to bridge these gaps has great potential but needs evaluation. OBJECTIVE: To evaluate a mHealth-based, Participant-CHW-Clinician feedback loop in a real-world setting. DESIGN: Quasi-experimental feasibility study with intervention and usual care (UC) groups. PARTICIPANTS: A total of 134 participants (n = 67/group) who were all low-income, uninsured Hispanics with or at-risk for type 2 diabetes. INTERVENTION: A 15-month study with a weekly to semimonthly mHealth Participant-CHW-Clinician feedback loop to identify participant issues and provide participants monthly diabetes education via YouTube. MAIN MEASURES: We used pre-defined feasibility measures to evaluate our intervention: (a) implementation, the execution of feedback loops to identify and resolve participant issues, and (b) efficacy, intended effects of the program on clinical outcomes (baseline to 15-month HbA1c, systolic blood pressure (SBP), diastolic blood pressure (DBP), and weight changes) for each group and their subgroups (at-risk; with diabetes, including uncontrolled (HbA1c ≥ 7%)). KEY RESULTS: CHWs identified 433 participant issues (mean = 6.5 ± 5.3) and resolved 91.9% of these. Most issues were related to supplies, 26.3% (n = 114); physical health, 23.1% (n = 100); and medication access, 20.8% (n = 90). Intervention participants significantly improved HbA1c (- 0.51%, p = 0.03); UC did not (- 0.10%, p = 0.76). UC DBP worsened (1.91 mmHg, p < 0.01). Subgroup analyses revealed HbA1c improvements for uncontrolled diabetes (intervention: - 1.59%, p < 0.01; controlled: - 0.72, p = 0.03). Several variables for UC at-risk participants worsened: HbA1c (0.25%, p < 0.01), SBP (4.05 mmHg, p < 0.01), DBP (3.21 mmHg, p = 0.01). There were no other significant changes for either group. CONCLUSIONS: A novel mHealth-based, Participant-CHW-Clinician feedback loop was associated with improved HbA1c levels and identification and resolution of participant issues. UC individuals had several areas of clinical deterioration, particularly those at-risk for diabetes, which is concerning for progression to diabetes and disease-related complications. CLINICAL TRIAL: NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456.

Ascertainment of Minimal Clinically Important Differences in the Diabetes Distress Scale-17: A Secondary Analysis of a Randomized Clinical Trial.

Importance: The Diabetes Distress Scale-17 (DDS-17) is a common measure of diabetes distress. Despite its popularity, there are no agreed-on minimal clinically important difference (MCID) values for the DDS-17. Objective: To establish a distribution-based metric for MCID in the DDS-17 and its 4 subscale scores (interpersonal distress, physician distress, regimen distress, and emotional distress). Design, Setting, and Participants: This secondary analysis of a randomized clinical trial used baseline and postintervention data from a hybrid (implementation-effectiveness) trial evaluating Empowering Patients in Chronic Care (EPICC) vs an enhanced form of usual care (EUC). Participants included adults with uncontrolled type 2 diabetes (glycated hemoglobin A1c [HbA1c] level >8.0%) who received primary care during the prior year in participating Department of Veterans Affairs clinics across Illinois, Indiana, and Texas. Data collection was completed in November 2018, and data analysis was completed in June 2023. Interventions: Participants in EPICC attended 6 group sessions led by health care professionals based on collaborative goal-setting theory. EUC included diabetes education. Main Outcomes and Measures: The main outcome was distribution-based MCID values for the total DDS-17 and 4 DDS-17 subscales, calculated using the standard error of measurement. Baseline to postintervention changes in DDS-17 and its 4 subscale scores were grouped into 3 categories: improved, no change, and worsened. Multilevel logistic and linear regression models examined associations between treatment group and MCID change categories and whether improvement in HbA1c varied in association with MCID category. Results: A total of 248 individuals with complete DDS-17 data were included (mean [SD] age, 67.4 [8.3] years; 235 [94.76%] men), with 123 participants in the EPICC group and 125 participants in the EUC group. The MCID value for DDS-17 was 0.25 and MCID values for the 4 distress subscales were 0.38 for emotional and interpersonal distress and 0.39 for physician and regimen distress. Compared with EUC, more EPICC participants were in the MCID improvement category on DDS-17 (63 participants [51.22%] vs 40 participants [32.00%]; P = .003) and fewer EPICC participants were in the worsened category (20 participants [16.26%] vs 39 participants [31.20%]; P = .008). There was no direct association of DDS-17 MCID improvement (ß = -0.25; 95% CI, -0.59 to 0.10; P = .17) or worsening (ß = 0.18; 95% CI, -0.22 to 0.59; P = .38) with HbA1c levels among all participants. Conclusions and Relevance: In this secondary analysis of data from a randomized clinical trial, an MCID improvement or worsening of more than 0.25 on the DDS-17 was quantitatively significant and patients in the EPICC group were more likely to experience improvement than those in the EUC group. Trial Registration: ClinicalTrials.gov Identifier: NCT01876485.

Global Cardiovascular Research: Gaps and Opportunities.

PURPOSE OF REVIEW: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. CVDs contribute to a large health and economic burden on a global scale. We aim to describe the current landscape of global cardiovascular research, highlight significant findings, and identify potential opportunities for further studies. RECENT FINDINGS: There has been remarkable research output regarding cardiovascular health in recent decades. Large-scale collaborative studies have made impactful strides in identifying modifiable risk factors and forming evidence-based guidelines to facilitate improved cardiovascular care and outcomes. However, there are significant CVD disparities between high- and low- income countries which require interventions to mitigate these inequalities. Encouraging collaborative partnerships, strengthening research capacity in low-resource settings, and promoting equity in research are fundamental strategic approaches to help improve global cardiovascular research.

Determining call-to-entry rate and recruitment barriers in clinical studies for community clinics serving low-income populations: a cohort study.

BACKGROUND: Recruitment for clinical studies is challenging. To overcome barriers, investigators have previously established call-to-entry rates to assist in planning. However, rates specific to low-income minority populations are needed to account for additional barriers to enrolment these individuals face. OBJECTIVE: To obtain a call-to-entry rate in a low-income uninsured Hispanic population with chronic disease. METHODS: We used data from four of our randomised clinical studies to determine the call-to-entry rate for individuals (n=1075) with or at risk for type 2 diabetes: participants needed/potential participants contacted=recruitment rate (yield). Research staff contacted potential participants to enrol in a study that evaluated 6 month diabetes programmes at community clinics from 2015 to 2020. We recorded call-to-entry rates, reasons for declining the study, show rates, and attrition. RESULTS: The call-to-entry rate was 14.5%. Forty per cent of potential participants could not be contacted, and 30.6%, 19.1%, and 5.4% responded yes, no, and maybe, respectively. No show percentages were 54% for yes and 91.4% for maybe responders. The majority (61.6%) declined due to inability to attend; reasons to decline included work (43%), eligibility (18%), transportation (10%), out of town (9%), did not think they needed the programme (7%) and other/unknown (14%). Being a physician predicted inability to reach participants (adjusted OR 2.91, 95% CI 1.73 to 4.90). Attrition was 6.8%. CONCLUSIONS: We described a call-to-entry rate and detailed recruitment data, including reasons to decline the study. This valuable information can assist investigators in study planning and overcoming enrolment barriers in low-income populations. Telehealth-based or strategies that limit transportation needs may increase participant involvement. TRIAL REGISTRATION NUMBER: NCT03394456.

The Rationale and Logistics for Incorporating Community Health Workers Into the Multidisciplinary Team.

Community Health Workers (CHWs) have shown value in diabetes care. CHWs are often the individuals who provide behavioral lifestyle intervention to underserved communities and are often the first to assist patients in gaining appropriate access to care. As trusted members of their communities, they have the ability to significantly impact psychosocial and biomedical outcomes, making them important members of the behavioral medicine team. However, lack of recognition of CHWs within multidisciplinary teams (MDTs) gives rise to the issue of the underutilization of their services. Therefore, barriers to including CHWs in MDTs including standardized training and strategies to overcome these are discussed.

Addressing Training Gaps: A Competency-Based, Telehealth Training Initiative for Community Health Workers.

Background: To overcome vast variations in Community Health Worker (CHW) training, investigators for the CHW Core Consensus Project (CCCP) derived three types of CHW (Category 1, 2, 3) and established competencies for each category. However, studies are needed that implement these competencies in real-world settings. Objective: Using the six competency domains of the CCCP as a theoretical backbone, we developed and evaluated a training for Category 1 CHWs, individuals whose focus is on community outreach and advocacy. Methods: We developed five telehealth-based, bilingual (Spanish/English) training sessions and implemented them among Category 1 Latino(a) CHWs. We measured the number of CHWs who achieved ≥70% correct on a domain-based posttest, attendance, and qualitative feedback. Results: All (18/18) CHWs achieved at least 70% on the posttest (mean: 93.7%; range 73.3-100%). Training attendance was 98.9%. Using a six-point scale, CHWs reported high levels of satisfaction overall (5.72 ± 0.57/6.0), with telehealth (5.72 ± 0.58/6.0), effectiveness of teaching strategies/methods (5.89 ± 0.32/6.0), achieving training objectives (5.96 ± 0.15/6.0), knowledge improvement (5.72 ± 0.57/6.0), and interest (5.78 ± 0.43/6.0). Conclusion: We successfully developed and evaluated a bilingual training program for Category 1 CHWs to address core competency gaps. High CHW attendance reinforces the value of telehealth modalities and their potential to increase the reach for CHW training. To overcome gaps in chronic disease training, investigations are needed to address additional CHW trainings. Trial Registration: NCT04835493.

Demographic and Regional Trends of Cardiovascular Diseases and Diabetes Mellitus-Related Mortality in the United States From 1999 to 2019.

OBJECTIVE: The purpose of this research was to study the contemporary trends in cardiovascular disease (CVD) and diabetes mellitus (DM)-related mortality. METHODS: We used the Centers for Disease Control and Prevention Wide-Ranging OnLine Data for Epidemiologic Research (CDC WONDER) database to identify adults ≥25 years old where both CVD and DM were listed as an underlying or contributing cause of death between 1999 and 2019. Crude and age-adjusted mortality rates per 100,000 population were determined. RESULTS: The overall age-adjusted mortality rate was 99.18 in 1999 and 91.43 in 2019, with a recent increase from 2014-2019 (annual percent change 1.0; 95% confidence interval [CI], 0.3-1.6). Age-adjusted mortality rate was higher for males compared with females, with increasing mortality in males between 2014 and 2019 (annual percent change 1.5; 95% CI, 0.9-2.0). Age-adjusted mortality rate was highest for non-Hispanic Black adults and was ∼2-fold higher compared with non-Hispanic White adults. Young and middle-aged adults (25-69 years) had increasing age-adjusted mortality rates in recent years. There were significant urban-rural disparities, and age-adjusted mortality rates in rural counties increased from 2014 to 2019 (annual percent change 2.2; 95% CI, 1.5-2.9); states in the 90th percentile of mortality had age-adjusted mortality rates that were ∼2-fold higher than those in the bottom 10th percentile of mortality. CONCLUSION: After an initial decrease in DM + CVD-related mortality for a decade, this trend has reversed, with increasing mortality from 2014 to 2019. Significant geographic and demographic disparities persist, requiring targeted health policy interventions to prevent the loss of years of progress.

The Use of Reframing: Increasing the Importance of Lifestyle Medicine.

Lifestyle behavior modification is an essential component to prevention and treatment of non-communicable diseases worldwide. For the last 40 years, studies have recognized that there is suboptimal training of physicians in lifestyle medicine and its implementation in clinical settings. The lack of nutrition and exercise counseling occurring in the medical office does not reflect the high level of evidence supporting its use. Lifestyle behavior counseling is complex; as are the individualized needs of patients. Therefore, we suspect that the lack of knowledge in nutrition and exercise prescriptions are not the only barriers to providing optimal care. Reframing lifestyle medicine interventions like nutrition and exercise from adjunctive to central to treatment and reframing the role of the physician therein may be necessary to address important barriers to overall lifestyle behavioral counseling.

A Mistake Not to Be Repeated: What Can We Learn from the Underutilization of Statin Therapy for Efficient Dissemination of Cardioprotective Glucose Lowering Agents?

PURPOSE OF REVIEW: To review the factors contributing to underutilization of guideline-directed therapies, identify strategies to alleviate these factors, and apply these strategies for effective and timely dissemination of novel cardioprotective glucose-lowering agents. RECENT FINDINGS: Recent analyses demonstrate underutilization of cardioprotective glucose lowering agents despite guideline recommendations for their use. Major contributors to underutilization of guideline-directed therapies include therapeutic inertia, perceptions about side effects, and factors found at the level of the clinicians, patients, and the healthcare system. The recent emergence of several novel therapies, such as sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists, for use in cardiovascular disease provides a unique avenue to improve patient outcomes. To effectively utilize novel cardioprotective glucose lowering agents to improve cardiovascular outcomes, clinicians must recognize and learn from prior barriers to application of guideline-directed therapies. Further endeavors are prudent to ensure uptake of novel agents.

Correlates of Glucagon-Like Peptide-1 Receptor Agonist Use Among Patients With Atherosclerotic Cardiovascular Disease and Type 2 Diabetes Mellitus (from the Department of Veterans Affairs).

This study used data from the Veterans Affairs administrative and clinical dataset to evaluate determinants of glucagon-like peptide-1 receptor agonist (GLP-1 RA) use among patients with concomitant atherosclerotic cardiovascular disease and diabetes mellitus and an antecedent primary care provider visit. The prevalence of GLP-1 RA use was 8.0%. In multivariable-adjusted models, White race, hypertension, obesity, higher hemoglobin A1c, ischemic heart disease, chronic kidney disease, a higher number of primary care provider visits, and previous cardiology or endocrinology visits were directly associated with GLP-1 RA use. Older age, having a physician primary care provider, and receiving care at a teaching facility were inversely associated with GLP-1 RA use. Our data can help inform targeted interventions to promote equitable access to GLP-1 RA and incentivize the adoption of these disease-modifying agents in high-risk patient populations.

Racial/ethnic and socioeconomic disparities in the use of newer diabetes medications in the Look AHEAD study.

Background: Among patients with type 2 diabetes, minority racial/ethnic groups have a higher burden of cardiovascular disease, chronic kidney disease, and hypoglycaemia. These groups may especially benefit from newer diabetes medication classes, but high cost may limit access. We examined the association of race/ethnicity with the initiation of newer diabetes medications (GLP-1 receptor agonists, DPP-4 inhibitors, SGLT-2 inhibitors). Methods: We conducted a secondary analysis of the Look AHEAD (Action for Health in Diabetes) trial including participants with at least one study visit after April 28, 2005. Cox proportional hazards models were used to estimate the association between race/ethnicity and socioeconomic factors with time to initiation of any newer diabetes medication from April 2005 to February 2020. Models were adjusted for demographic and clinical characteristics. Findings: Among 4,892 participants, 63.6%, 15.7%, 12.6%, 5.2%, and 2.9% were White, Black, Hispanic, American Indian or Alaskan Native (AI/AN), or other race/ethnicity, respectively. During a median follow-up of 8.3 years, 2,180 (45.2%) participants were initiated on newer diabetes medications. Race/ethnicity was associated with newer diabetes medication initiation (p=.019). Specifically, initiation was lower among Black (HR 0.81, 95% CI 0.70 -0.94) and AI/AN participants (HR 0.51, 95% CI 0.26-0.99). Yearly family income was inversely associated with initiation of newer diabetes medications (HR 0.78, 95% CI 0.62-0.98) comparing the lowest and highest income groups. Findings were mostly driven by GLP-1 receptor agonists. Interpretation: These findings provide evidence of racial/ethnic disparities in the initiation of newer diabetes medications, independent of socioeconomic factors, which may contribute to worse health outcomes.

Long-Term Effectiveness of the TIME Intervention to Improve Diabetes Outcomes in Low-Income Settings: a 2-Year Follow-Up.

BACKGROUND: We previously found that a 6-month multidimensional diabetes program, TIME (Telehealth-Supported, Integrated Community Health Workers, Medication-Access) resulted in improved clinical outcomes. OBJECTIVE: To follow TIME participant clinical outcomes for 24 months PARTICIPANTS: Low-income Latino(a)s with type 2 diabetes DESIGN AND INTERVENTION: We collected post-intervention clinical data for five cohorts (n = 101, mean n = 20/cohort) who participated in TIME programs from 2018 to 2020 in Houston, Texas. MAIN MEASURES: We gathered HbA1c (primary outcome), weight, body mass index (BMI), and blood pressure data at baseline, 6 months (intervention end), and semiannually thereafter until 24 months after baseline to assess sustainability. We also evaluated participant loss to follow-up until 24 months. KEY RESULTS: Participants decreased HbA1c levels during the intervention (p < 0.0001) and maintained these improvements at each timepoint from baseline to 24 months (p range: < 0.0001 to 0.015). Participants reduced blood pressure levels during TIME and maintained these changes at each timepoint from baseline until 18 months (systolic p range < 0.0001 to 0.0005, diastolic p range: < 0.0001 to 0.008) but not at 24 months (systolic: p = 0.065; diastolic: p = 0.85). There were no significant weight changes during TIME or post-intervention: weight (p range = 0.07 to 0.77), BMI (p range = 0.11 to 0.71). Attrition rates (loss to follow-up during the post-intervention period) were 5.9% (6 months), 24.8% (12 months), 35.6% (18 months), and 41.8% (24 months). CONCLUSIONS: It is possible for vulnerable populations to maintain long-term glycemic and blood pressure improvements using a multiple dimensional intervention. Attrition rates rose over time but show promise given the majority of post-intervention timepoints occurred during the COVID-19 pandemic when low-income populations were most susceptible to suboptimal healthcare access. Future studies are needed to evaluate longitudinal outcomes of diabetes interventions conducted by local clinics rather than research teams.

Utilization Rates of SGLT2 Inhibitors and GLP-1 Receptor Agonists and Their Facility-Level Variation Among Patients With Atherosclerotic Cardiovascular Disease and Type 2 Diabetes: Insights From the Department of Veterans Affairs.

OBJECTIVE: There is mounting evidence regarding the cardiovascular benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP-1 RA) among patients with atherosclerotic cardiovascular disease (ASCVD) and type 2 diabetes mellitus (T2DM). There is paucity of data assessing real-world practice patterns for these drug classes. We aimed to assess utilization rates of these drug classes and facility-level variation in their use. RESEARCH DESIGN AND METHODS: We used the nationwide Veterans Affairs (VA) health care system data set from 1 January 2020 to 31 December 2020 and included patients with established ASCVD and T2DM. Among these patients, we assessed the use of SGLT2i and GLP-1 RA and the facility-level variation in their use. Facility-level variation was computed using median rate ratios (MRR), a measure of likelihood that two random facilities differ in use of SGLT2i and GLP-1 RA in patients with ASCVD and T2DM. RESULTS: Among 537,980 patients with ASCVD and T2DM across 130 VA facilities, 11.2% of patients received an SGLT2i while 8.0% of patients received a GLP-1 RA. Patients receiving these cardioprotective glucose-lowering drug classes were on average younger and had a higher proportion of non-Hispanic Whites. Overall, median (10th-90th percentile) facility-level rates were 14.92% (9.31-22.50) for SGLT2i and 10.88% (4.44-17.07) for GLP-1 RA. There was significant facility-level variation among SGLT2i use-MRRunadjusted: 1.41 (95% CI 1.35-1.47) and MRRadjusted: 1.55 (95% CI 1.46 -1.63). Similar facility-level variation was observed for use of GLP-1 RA-MRRunadjusted: 1.34 (95% CI 1.29-1.38) and MRRadjusted: 1.78 (95% CI 1.65-1.90). CONCLUSIONS: Overall utilization rates of SGLT2i and GLP-1 RA among eligible patients are low, with significantly higher residual facility-level variation in the use of these drug classes. Our results suggest opportunities to optimize their use to prevent future adverse cardiovascular events among these patients.

Testing the Impact of a Collaborative, Goal-Setting, and Behavioral Telehealth Intervention on Diabetes Distress: A Randomized Clinical Trial.

Background:Diabetes distress is underrecognized and associated with poor outcomes. This study tested whether a 12-month collaborative, goal-setting, and behavioral telehealth intervention reduced diabetes distress levels.Methods:This is a secondary analysis of the Healthy Outcomes through Patient Empowerment (HOPE) study that included individuals (N = 225) with uncontrolled diabetes and depression living at least 20 miles from a Veteran's Affairs medical center. Participants were randomized to HOPE (intervention) or Enhanced Usual Care (EUC) with education. We evaluated diabetes distress levels as measured by the Problem Areas in Diabetes (PAID) Questionnaire and its four subscales (emotional, diabetes management, social, and treatment distress) at baseline, 6, and 12 months.Results:Between-group analysis revealed greater improvements in HOPE versus EUC for: 6-month PAID total score (p = 0.04), emotional (p = 0.03), and social (p = 0.04) subscales; 12-month PAID total score (p = 0.07) and emotional subscale (p = 0.07). Within-group comparisons showed larger effect sizes for HOPE compared with EUC: 12-month PAID total scores (0.82 vs. 0.54), 6-month emotional burden (0.54 vs. 0.31), and 6-month (0.32 vs. 0.08) and 12-month (0.41 vs. 0.12) social burdens. Repeated-measures analysis evaluating treatment group and time trended toward improvement in PAID overall for HOPE compared with EUC participants, but was not statistically significant (ß = 6.96; SE = 4.35; p = 0.13).Discussion:Clinically meaningful reductions in PAID overall and the emotional and social subscales were observed in HOPE compared with EUC participants.Conclusion:Further evaluation of diabetes telehealth interventions that include other facets related to diabetes distress, including treatment, diabetes management, social, and emotional burdens, is warranted. Clinical Trial Number. NCT01572389; Clinical Trial Registry. https://clinicaltrials.gov/ct2/show/NCT01572389.

Mentored implementation to initiate a diabetes program in an underserved community: a pilot study.

INTRODUCTION: Community clinics often face pragmatic barriers, hindering program initiation and replication of controlled research trial results. Mentoring is a potential strategy to overcome these barriers. We piloted an in-person and telehealth mentoring strategy to implement the Telehealth-supported, Integrated Community Health Workers (CHWs), Medication-access, group visit Education (TIME) program in a community clinic. RESEARCH DESIGN AND METHODS: Participants (n=55) were low-income Latino(a)s with type 2 diabetes. The study occurred in two, 6-month phases. Phase I provided proof-of-concept and an observational experience for the clinic team; participants (n=37) were randomized to the intervention (TIME) or control (usual care), and the research team conducted TIME while the clinic team observed. Phase II provided mentorship to implement TIME, and the research team mentored the clinic team as they conducted TIME for a new single-arm cohort of participants (n=18) with no previous exposure to the program. Analyses included baseline to 6-month comparisons of diabetes outcomes (primary outcome: hemoglobin A1c (HbA1c)): phase I intervention versus control, phase II (within group), and research-run (phase I intervention) versus clinic-run (phase II) arms. We also evaluated baseline to 6-month CHW knowledge changes. RESULTS: Phase I: compared with the control, intervention participants had superior baseline to 6-month improvements for HbA1c (mean change: intervention: -0.73% vs control: 0.08%, p=0.016), weight (p=0.044), target HbA1c (p=0.035), hypoglycemia (p=0.021), medication non-adherence (p=0.0003), and five of six American Diabetes Association (ADA) measures (p<0.001-0.002). Phase II: participants had significant reductions in HbA1c (mean change: -0.78%, p=0.006), diastolic blood pressure (p=0.004), body mass index (0.012), weight (p=0.010), medication non-adherence (p<0.001), and six ADA measures (p=0.007-0.005). Phase I intervention versus phase II outcomes were comparable. CHWs improved knowledge from pre-test to post-tests (p<0.001). CONCLUSIONS: A novel, mentored approach to implement TIME into a community clinic resulted in improved diabetes outcomes. Larger studies of longer duration are needed to fully evaluate the potential of mentoring community clinics.

A Telehealth-supported, Integrated care with CHWs, and MEdication-access (TIME) Program for Diabetes Improves HbA1c: a Randomized Clinical Trial.

BACKGROUND: Many individuals with diabetes live in low- or middle-income settings. Glycemic control is challenging, particularly in resource-limited areas that face numerous healthcare barriers. OBJECTIVE: To compare HbA1c outcomes for individuals randomized to TIME, a Telehealth-supported, Integrated care with CHWs (Community Health Workers), and MEdication-access program (intervention) versus usual care (wait-list control). DESIGN: Randomized clinical trial. PARTICIPANTS: Low-income Latino(a) adults with type 2 diabetes. INTERVENTIONS: TIME consisted of (1) CHW-participant telehealth communication via mobile health (mHealth) for 12 months, (2) CHW-led monthly group visits for 6 months, and (3) weekly CHW-physician diabetes training and support via telehealth (video conferencing). MAIN MEASURES: Investigators compared TIME versus control participant baseline to month 6 changes of HbA1c (primary outcome), blood pressure, body mass index (BMI), weight, and adherence to seven American Diabetes Association (ADA) standards of care. CHW assistance in identifying barriers to healthcare in the intervention group were measured at the end of mHealth communication (12 months). KEY RESULTS: A total of 89 individuals participated. TIME individuals compared to control participants had significant HbA1c decreases (9.02 to 7.59% (- 1.43%) vs. 8.71 to 8.26% (- 0.45%), respectively, p = 0.002), blood pressure changes (systolic: - 6.89 mmHg vs. 0.03 mmHg, p = 0.023; diastolic: - 3.36 mmHg vs. 0.2 mmHg, respectively, p = 0.046), and ADA guideline adherence (p < 0.001) from baseline to month 6. At month 6, more TIME than control participants achieved > 0.50% HbA1c reductions (88.57% vs. 43.75%, p < 0.001). BMI and weight changes were not significant between groups. Many (54.6%) TIME participants experienced > 1 barrier to care, of whom 91.7% had medication issues. CHWs identified the majority (87.5%) of barriers. CONCLUSIONS: TIME participants resulted in improved outcomes including HbA1c. CHWs are uniquely positioned to identify barriers to care particularly related to medications that may have gone unrecognized otherwise. Larger trials are needed to determine the scalability and sustainability of the intervention. CLINICAL TRIAL: NCT03394456, accessed at https://clinicaltrials.gov/ct2/show/NCT03394456.