Receipt of Diabetes Specialty Care and Management Services by Older Adults With Diabetes in the U.S., 2015-2019: An Analysis of Medicare Fee-for-Service Claims.

OBJECTIVE: We characterized the receipt of diabetes specialty care and management services among older adults with diabetes. RESEARCH DESIGN AND METHODS: Using a 20% random sample of fee-for-service Medicare beneficiaries aged ≥65 years, we analyzed cohorts of type 1 diabetes (T1D) or type 2 diabetes (T2D) with history of severe hypoglycemia (HoH), and all other T2D annually from 2015 to 2019. Outcomes were receipt of office-based endocrinology care, diabetes education, outpatient diabetes health services, excluding those provided in primary care, and any of the aforementioned services. RESULTS: In the T1D cohort, receipt of endocrinology care and any service increased from 25.9% and 29.2% in 2015 to 32.7% and 37.4% in 2019, respectively. In the T2D with HoH cohort, receipt of endocrinology care and any service was 13.9% and 16.4% in 2015, with minimal increases. Age, race/ethnicity, residential setting, and income were associated with receiving care. CONCLUSIONS: These findings suggest that many older adults may not receive specialty diabetes care and underscore health disparities.

Extending an Antiracism Lens to the Implementation of Precision Public Health Interventions.

Precision public health holds promise to improve disease prevention and health promotion strategies, allowing the right intervention to be delivered to the right population at the right time. Growing concerns underscore the potential for precision-based approaches to exacerbate health disparities by relying on biased data inputs and recapitulating existing access inequities. To achieve its full potential, precision public health must focus on addressing social and structural drivers of health and prominently incorporate equity-related concerns, particularly with respect to race and ethnicity. In this article, we discuss how an antiracism lens could be applied to reduce health disparities and health inequities through equity-informed research, implementation, and evaluation of precision public health interventions. (Am J Public Health. 2023;113(11):1210-1218. https://doi.org/10.2105/AJPH.2023.307386).

The Growing Role of Technology in the Care of Older Adults With Diabetes.

The integration of technologies such as continuous glucose monitors, insulin pumps, and smart pens into diabetes management has the potential to support the transformation of health care services that provide a higher quality of diabetes care, lower costs and administrative burdens, and greater empowerment for people with diabetes and their caregivers. Among people with diabetes, older adults are a distinct subpopulation in terms of their clinical heterogeneity, care priorities, and technology integration. The scientific evidence and clinical experience with these technologies among older adults are growing but are still modest. In this review, we describe the current knowledge regarding the impact of technology in older adults with diabetes, identify major barriers to the use of existing and emerging technologies, describe areas of care that could be optimized by technology, and identify areas for future research to fulfill the potential promise of evidence-based technology integrated into care for this important population.

Obesity, multiple chronic conditions, and the relationship with physical function: Data from the national health and aging trends survey.

BACKGROUND: The population of older adults living with multiple chronic conditions (MCC) continues to grow. MCC is independently associated with functional limitation and obesity. The aim of our study was to evaluate the association between obesity and MCC, and secondarily, the combined presence of obesity and functional limitations with MCC. METHODS: We analyzed cross-sectional survey data from the National Health and Aging Trends Survey (NHATS) 2011 baseline data, a nationally representative Medicare beneficiary cohort of adults in the United States. We evaluated the coexistent prevalence of obesity and MCC overall, and by standard body mass index (BMI) categories. We then evaluated the prevalence of functional limitations (mobility, self-care, and household activities) and Fried-defined frailty status in persons with a BMI ≥ 30 kg/m2. Logistic regression was used to measure the association between MCC and BMI, and functional limitations and MCC among those with obesity. RESULTS: In the 6,600 participants, the prevalence of concurrent obesity and MCC was 30.4%. Of those with obesity, the prevalence of MCC was 84.0%, and were more likely to have MCC (adjusted OR: 2.17, 95% CI 1.86, 2.54) compared to a normal BMI. Obesity and functional limitations or frailty were more likely have MCC than individuals with obesity alone. CONCLUSIONS: We found that individuals with obesity is strongly associated with MCC and that functional limitations and frailty status have a greater association with having MCC than individuals with obesity without MCC. Future longitudinal analyses are needed to ascertain this relationship.

Inequalities in Glycemic Control in Youth with Type 1 Diabetes Over Time: Intersectionality Between Socioeconomic Position and Race and Ethnicity.

BACKGROUND: Racial/ethnic health inequities have been well-documented among youth and young adults with type 1 diabetes (T1D), yet little is known about how socioeconomic position (SEP) intersects with the risk marker of race/ethnicity to predict inequities in longitudinal glycemic control. PURPOSE: To identify patterns of SEP, race/ethnicity, and clinical characteristics that differentiate hemoglobin A1c (HbA1c) trajectories among youth and young adults after T1D diagnosis. METHODS: The SEARCH for Diabetes in Youth cohort includes youth with diabetes diagnosed from 2002 to 2006 and 2008 who were followed through 2015. We analyzed data from 1,313 youth and young adults with T1D with ≥3 HbA1c measures. Classification tree analysis identified patterns of baseline demographic, SEP, and clinical characteristic that best predicted HbA1c trajectories over an average of 8.3 years using group-based trajectory modeling. RESULTS: Two HbA1c trajectories were identified: Trajectory 1 (77%) with lower baseline HbA1c and mild increases (from mean 7.4% to 8.4%) and Trajectory 2 (23%) with higher baseline HbA1c and major increases (from 8.5% to 11.2%). Race/ethnicity intersected with different SEP characteristics among non-Hispanic white (NHW) than in non-whites. Public health insurance predicted high-risk Trajectory 2 membership in non-whites, whereas parental education, household structure, diagnosis age and glucose checking frequency predicted membership for NHW youth and young adults. Two characteristics, race/ethnicity and parental education alone identified 80% of the Trajectory 2 members. CONCLUSIONS: Race/ethnicity intersects with multiple SEP and clinical characteristics among youth and young adults with T1D, which is associated with particularly high risk of poor long-term glycemic control.

Deintensification of Treatment With Sulfonylurea and Insulin After Severe Hypoglycemia Among Older Adults With Diabetes.

Importance: Practice guidelines recommend deintensification of hypoglycemic agents among older adults with diabetes who are at high risk of hypoglycemia, yet real-world treatment deintensification practices are not well characterized. Objective: To examine the incidence of sulfonylurea and insulin deintensification after a hypoglycemia-associated emergency department (ED) visit or hospitalization among older adults with diabetes and to identify factors associated with deintensification of treatment. Design, Setting, and Participants: This retrospective cohort study included a random sample of 20% of nationwide fee-for-service US Medicare beneficiaries aged 65 years and older with concurrent Medicare parts A, B, and D coverage between January 1, 2007, and December 31, 2017. Individuals with diabetes who had at least 1 hypoglycemia-associated ED visit or hospitalization were included. Data were analyzed from August 1, 2020, to August 1, 2021. Exposures: Baseline medication for the treatment of diabetes (sulfonylurea, insulin, or both). Main Outcomes and Measures: Incidence of treatment deintensification (yes or no) in the 100 days after a severe hypoglycemic episode requiring an ED visit or hospitalization, with treatment deintensification defined as (1) a decrease in sulfonylurea dose, (2) a change from long-acting to short-acting sulfonylurea (glipizide), (3) discontinuation of sulfonylurea, or (4) discontinuation of insulin based on pharmacy dispensing claims. Results: Among 76 278 distinct Medicare beneficiaries who had a hypoglycemia-associated ED visit or hospitalization, the mean (SD) age was 76.6 (7.6) years. Of 106 293 total hypoglycemic episodes requiring hospital attention, 69 084 (65.0%) occurred among women, 26 056 (24.5%) among Black individuals; 4761 (4.5%) among Hispanic individuals; 69 704 (65.6%) among White individuals; and 5772 (5.4%) among individuals of other races and ethnicities (comprising Asian, North American Native, unknown race or ethnicity, and unspecified race or ethnicity). A total of 32 074 episodes (30.2%) occurred among those receiving sulfonylurea only, 60 350 (56.8%) occurred among those receiving insulin only, and 13 869 (13.0%) occurred among those receiving both sulfonylurea and insulin. Treatment deintensification rates were highest among individuals receiving both sulfonylurea and insulin therapies at the time of their hypoglycemic episode (6677 episodes [48.1%]), followed by individuals receiving sulfonylurea only (14 192 episodes [44.2%]) and insulin only (14 495 episodes [24.0%]). Treatment deintensification rates increased between 2007 and 2017 (sulfonylurea only: from 41.4% to 49.7%; P < .001 for trend; insulin only: from 21.3% to 25.9%; P < .001 for trend; sulfonylurea and insulin: from 45.9% to 49.6%; P = .005 for trend). Lower socioeconomic status (as indicated by the receipt of low-income subsidies) was associated with lower odds of deintensification, regardless of baseline hypoglycemic regimen (sulfonylurea only: adjusted odds ratio [AOR], 0.74 [95% CI, 0.70-0.78]; insulin only: AOR, 0.71 [95% CI, 0.68-0.75]; sulfonylurea and insulin: AOR, 0.72 [95% CI, 0.66-0.78]). A number of patient factors were associated with higher odds of treatment deintensification: higher frailty (eg, ≥40% probability of needing assistance with activities of daily living among those receiving sulfonylurea and insulin: AOR, 1.50; 95% CI, 1.32-1.71), chronic kidney disease (eg, sulfonylurea and insulin: AOR, 1.29; 95% CI, 1.19-1.40), a history of falls (eg, sulfonylurea and insulin: AOR, 1.20; 95% CI, 1.09-1.33), and depression (eg, sulfonylurea and insulin: AOR, 1.11; 95% CI, 1.02-1.20). Conclusions and Relevance: In this cohort study, deintensification of sulfonylurea and/or insulin therapy within 100 days after a hypoglycemia-associated ED visit or hospitalization occurred in fewer than 50% of older adults with diabetes; however, these deintensification rates may be increasing over time, and deintensification of insulin was likely underestimated because of challenges in capturing changes to insulin dosing using administrative claims data. These results suggest that greater efforts are needed to identify individuals at high risk of hypoglycemia to encourage appropriate treatment deintensification in accordance with current evidence.

Socioeconomic position is associated with glycemic control in youth and young adults with type 1 diabetes.

OBJECTIVE: Health inequities persist in youth and young adults (YYA) with type 1diabetes in achieving optimal glycemic control. The purpose of this study was to assess the contribution of multiple indicators of social need to these inequities. RESEARCH DESIGN AND METHODS: Two hundred and twenty two YYA withtype 1 diabetes enrolled in the SEARCH Food Insecurity Study in South Carolina and Washington between the years 2013 and 2015 were included. Latent class analysis was used to identify socioeconomic profiles based on household income, parental education, health insurance, household food insecurity, and food assistance. Profiles were evaluated in relation to glycemic control using multivariable linear and logistic regression, with HbA1c > 9%(75 mmol/mol) defined as high-risk glycemic control. RESULTS: Two profiles were identified: a lower socioeconomic profile included YYA whose parents had lower income and/or education, and were more likely to be uninsured, receive food assistance, and be food insecure. A higher socioeconomic profile included YYA whose circumstances were opposite to those in the lower socioeconomic profile. Those with a lower socioeconomic profile were more likely to have high-risk glycemic control relative to those with a higher socioeconomic profile (OR = 2.24, 95%CI = 1.16-4.33). CONCLUSIONS: Lower socioeconomic profiles are associated with high-risk glycemic control among YYA with type 1 diabetes. This supports recommendations that care providers of YYA with type 1 diabetes assess individual social needs in tailoring diabetes management plans to the social context of the patient.

Assessment of third-year medical students' comfort and preparedness for navigating challenging clinical scenarios with patients, peers, and supervisors.

BACKGROUND: Medical training focuses heavily on clinical skills but lacks in training for navigating challenging clinical scenarios especially with regard to diversity issues. Our objective was to assess third-year medical students' preparedness to navigate such scenarios. METHODS: A 24-item survey was administered electronically to third-year medical students describing a range of specific interactions with patients, peers, and "upper-levels" or superiors including residents and attendings, spanning subjects including gender, race/ethnicity, politics, age, sexual orientation/identity, disability, and religion. Students rated their level of comfort via a 5-point Likert scale ranging from 1 ("Very Uncomfortable") to 5 ("Very Comfortable"). Basic demographics were collected and data were summarized for trends. RESULTS: Data were analyzed from 120 students (67% response rate, 54.2% female, 60.8% non-Hispanic white). Students reported lower comfort with peer and superiors compared to patient interactions (p < 0.0001). Students reported the highest comfort with sexual orientation/identity- and religion-related interactions (median (IQR): 3.3 (1.3) and 3.4 (10.0), respectively) and the lowest comfort with gender-, race/ethnicity-, and disability- related interactions (median (IQR): 2.3 (1.3), 2.0 (1.0), 2.5 (1.5), respectively). Males reported significantly higher median comfort levels for scenarios with upper-level, gender, and religion related interactions. Males were more likely to be completely comfortable versus females across the 24 scenarios, although multiple male response patterns showed evidence of a bimodal distribution. CONCLUSIONS: Third-year medical students report generally inadequate comfort with navigating complex clinical scenarios, particularly with peers and supervisors and relating to gender-, race/ethnicity-, and disability-specific conflicts. There are differences across gender with regards to median comfort and distribution of scores suggesting that there is a subgroup of males report high/very high comfort with challenging clinical scenarios. Students may benefit from enhanced training modules and personalized toolkits for navigating these scenarios.

Assessment of a Precision Medicine Analysis of a Behavioral Counseling Strategy to Improve Adherence to Diabetes Self-management Among Youth: A Post Hoc Analysis of the FLEX Trial.

Importance: The Flexible Lifestyles Empowering Change (FLEX) trial, an 18-month randomized clinical trial testing an adaptive behavioral intervention in adolescents with type 1 diabetes, showed no overall treatment effect for its primary outcome, change in hemoglobin A1c (HbA1c) percentage of total hemoglobin, but demonstrated benefit for quality of life (QoL) as a prespecified secondary outcome. Objective: To apply a novel statistical method for post hoc analysis that derives an individualized treatment rule (ITR) to identify FLEX participants who may benefit from intervention based on changes in HbA1c percentage (primary outcome), QoL, and body mass index z score (BMIz) (secondary outcomes) during 18 months. Design, Setting, and Participants: This multisite clinical trial enrolled 258 adolescents aged 13 to 16 years with type 1 diabetes for 1 or more years, who had literacy in English, HbA1c percentage of total hemoglobin from 8.0% to 13.0%, a participating caregiver, and no other serious medical conditions. From January 5, 2014, to April 4, 2016, 258 adolescents were recruited. The post hoc analysis excluded adolescents missing outcome measures at 18 months (2 participants [0.8%]) or continuous glucose monitoring data at baseline (40 participants [15.5%]). Data were analyzed from April to December 2018. Interventions: The FLEX intervention included a behavioral counseling strategy that integrated motivational interviewing and problem-solving skills training to increase adherence to diabetes self-management. The control condition entailed usual diabetes care. Main Outcomes and Measures: Subgroups of FLEX participants were derived from an ITR estimating which participants would benefit from intervention, which would benefit from control conditions, and which would be indifferent. Multiple imputation by chained equations and reinforcement learning trees were used to estimate the ITR. Subgroups based on ITR pertaining to changes during 18 months in 3 univariate outcomes (ie, HbA1c percentage, QoL, and BMIz) and a composite outcome were compared by baseline demographic, clinical, and psychosocial characteristics. Results: Data from 216 adolescents in the FLEX trial were reanalyzed (166 [76.9%] non-Hispanic white; 108 teenaged girls [50.0%]; mean [SD] age, 14.9 [1.1] years; mean [SD] diabetes duration, 6.3 [3.7] years). For the univariate outcomes, a large proportion of FLEX participants had equivalent predicted outcomes under intervention vs usual care settings, regardless of randomization, and were assigned to the muted group (HbA1c: 105 participants [48.6%]; QoL: 63 participants [29.2%]; BMIz: 136 participants [63.0%]). Regarding the BMIz univariate outcome, mean baseline BMIz of participants assigned to the muted group was lower than that of those assigned to the intervention and control groups (muted vs intervention: mean difference, 0.48; 95% CI, 0.21 to 0.75; P = .002; muted vs control: mean difference, 0.86; 95% CI, 0.61 to 1.11; P < .001); this group also had a higher proportion of individuals with underweight or normal weight using weight status cutoffs (95 [69.9%] in muted group vs 24 [54.6%] in intervention group and 11 [30.6%] in control group; χ24 = 24.67; P < .001). The approach identified subgroups estimated to benefit based on HbA1c percentage (54 participants [25.0%]), QoL (89 participants [41.2%]), and BMIz (44 participants [20.4%]). Regarding the HbA1c percentage outcome, participants expected to benefit from the intervention did not have significantly higher baseline HbA1c percentages than those expected to benefit from usual care (9.4% vs 9.2%; difference, 0.2%; 95% CI, -0.16% to 0.56%; P = .44). However, participants in the muted group had higher mean HbA1c percentages at baseline than those assigned to the intervention or control groups (muted vs intervention: 9.9% vs 9.4%; difference, 0.5%; 95% CI, 0.13% to 0.89%; P = .02; muted vs control; 9.9% vs 9.2%; difference, 0.7%; 95% CI, 0.34% to 1.08%; P = .001). No significant differences were found between subgroups estimated to benefit in terms of the composite outcome from the FLEX intervention (91 participants [42.1%]) vs usual care (125 participants [57.9%]). Conclusions and Relevance: The precision medicine approach represents a conceptually and analytically novel approach to post hoc subgroup identification. More work is needed to understand markers of positive response to the FLEX intervention. Trial Registration: ClinicalTrial.gov identifier: NCT01286350.

Association of Race and Ethnicity With Glycemic Control and Hemoglobin A1c Levels in Youth With Type 1 Diabetes.

IMPORTANCE: Health disparities in the clinical presentation and outcomes among youth with type 1 diabetes exist. Long-term glycemic control patterns in racially/ethnically diverse youth are not well described. OBJECTIVES: To model common trajectories of hemoglobin A1c (HbA1c) among youth with type 1 diabetes and test how trajectory group membership varies by race/ethnicity. DESIGN SETTING AND PARTICIPANTS: Longitudinal cohort study conducted in 5 US locations. The analysis included data from 1313 youths (aged <20 years) newly diagnosed in 2002 through 2005 with type 1 diabetes in the SEARCH for Diabetes in Youth study (mean [SD] age at diabetes onset, 8.9 [4.2] years) who had 3 or more HbA1c study measures during 6.1 to 13.3 years of follow-up. Data were analyzed in 2017. EXPOSURES: Self-reported race/ethnicity. MAIN OUTCOMES AND MEASURES: Hemoglobin A1c trajectories identified through group-based trajectory modeling over a mean (SD) of 9.0 (1.4) years of diabetes duration. Multinomial models studied the association of race/ethnicity with HbA1c trajectory group membership, adjusting for demographic characteristics, clinical factors, and socioeconomic position. RESULTS: The final study sample of 1313 patients was 49.3% female (647 patients) with mean (SD) age 9.7 (4.3) years and mean (SD) disease duration of 9.2 (6.3) months at baseline. The racial/ethnic composition was 77.0% non-Hispanic white (1011 patients), 10.7% Hispanic (140 patients), 9.8% non-Hispanic black (128 patients), and 2.6% other race/ethnicity (34 patients). Three HbA1c trajectories were identified: group 1, low baseline and mild increases (50.7% [666 patients]); group 2, moderate baseline and moderate increases (41.7% [548 patients]); and group 3, moderate baseline and major increases (7.5% [99 patients]). Group 3 was composed of 47.5% nonwhite youths (47 patients). Non-Hispanic black youth had 7.98 higher unadjusted odds (95% CI, 4.42-14.38) than non-Hispanic white youth of being in the highest HbA1c trajectory group relative to the lowest HbA1c trajectory group; the association remained significant after full adjustment (adjusted odds ratio of non-Hispanic black race in group 3 vs group 1, 4.54; 95% CI, 2.08-9.89). Hispanic youth had 3.29 higher unadjusted odds (95% CI, 1.78-6.08) than non-Hispanic white youth of being in the highest HbA1c trajectory group relative to the lowest HbA1c trajectory group; the association remained significant after adjustment (adjusted odds ratio of Hispanic ethnicity in group 3 vs group 1, 2.24; 95% CI, 1.02-4.92). In stratified analyses, the adjusted odds of nonwhite membership in the highest HbA1c trajectory remained significant among male patients and youth diagnosed at age 9 years or younger, but not female patients and youth who were older than 9 years when they were diagnosed (P for interaction = .04 [sex] and .02 [age at diagnosis]). CONCLUSIONS AND RELEVANCE: There are racial/ethnic differences in long-term glycemic control among youth with type 1 diabetes, particularly among nonwhite male patients and nonwhite youth diagnosed earlier in life.

Understanding antagonism and synergism: A qualitative assessment of weight management in youth with Type 1 diabetes mellitus.

AIMS: No current clinical guidelines focus on weight management in youth with type 1 diabetes mellitus (T1DM). Our aim was to characterize the patient-perceived experience and barriers to weight management in youth with T1DM. METHODS: Participants were recruited from the University of North Carolina (n = 16, 56% female, 60% White, 50% insulin pump users, mean age 14.8 years, mean HbA1c 8.5% (69 mmol/mol)) and the University of Colorado (n = 18, 50% female, 80% white, 53% pump users, mean age 15.3 years, mean HbA1c 9.3% (78 mmol/mol)). Focus groups were stratified by sex and weight status (BMI cutoff = 25). Discussions were guided by a standardized set of questions, audio-taped, transcribed, and analyzed thematically using inductive qualitative methods. RESULTS: Youth with T1DM expressed four interrelated themes of antagonism between type 1 diabetes and weight management: dysregulated appetite, disruption of blood glucose levels associated with changing diet/exercise, hypoglycemia as a barrier to weight loss, and the overwhelming nature of dual management of weight and glycemic control, and two interrelated themes of synergism: improvement in shared, underlying heath behaviors and exercise as a tool for weight and glycemic control. Variation in emphasis of specific thematic elements was greatest across sex. Youth identified five major components of a weight management program for T1DM: intensified glucose management, healthy diet with known carbohydrate content, exercise, individualization and flexibility, and psychosocial and peer support. CONCLUSIONS: There is critical need for personalized, T1DM-specific weight recommendations to overcome disease-specific barriers to weight management in the context of T1DM.

Implementation and Evaluation of Shared Medical Appointments for Type 2 Diabetes at a Free, Student-Run Clinic in Alamance County, North Carolina.

INTRODUCTION: Type 2 diabetes is a significant problem among uninsured patients. Shared medical appointments (SMA) have been shown to improve outcomes in type 2 diabetes. We hypothesized that the SMA model could be adapted for a non-profit clinic in North Carolina that serves uninsured patients with diabetes that have incomes at/below 150% of the federal poverty line. RESEARCH DESIGN AND METHODS: We implemented and sustained a patient-driven, student-led SMA model that incorporated the monthly rotations of students, physician assistant, and undergraduate students as well as pharmacy residents and an endocrinologist who collectively provide diabetes care at the free clinic. SMA groups are 'open' cohorts and include 4-12 patients scheduled for the monthly clinic. Teams of transdisciplinary trainees work together to perform triage, medication reconciliation, brief history, and physical exam, after which patients participate in the SMA. The endocrinologist evaluates SMA patients individually during and after the visit. RESULTS: Between November 2015 and January 2017, we enrolled 29 patients in SMA. There was high variability in HbA1c at baseline. Among eight type 2 diabetes patients seen in endocrine clinic and with complete data one year before and after SMA implementation, the mean (SD) HbA1c before SMA was 9.7% ± 1.7% (83±7 mmol/ mol); mean HbA1c after SMA was 9.2% ± 1.8% (77 ± 8mmol/mol). The median HbA1c before SMA was 9.5% (80 mmol/mol); median HbA1c after SMA was 8.9% (74 mmol/mol). Overall, 6/8 patients showed decreased HbA1c after SMA although there was variability between individuals in response of glycemic control to SMA. SMA increased clinic efficiency and offered an opportunity to integrate transdisciplinary trainees. Trainees gain experience with novel models of care and the complexities of the patient experience of diabetes. CONCLUSIONS: We hope this observation encourages others to implement such programs to enhance the evidence-base for SMA to address health disparities and increase the quality of free diabetes care.