Implicit or Unconscious Bias in Diabetes Care.

"Implicit bias," also called "unconscious bias," refers to associations outside of conscious awareness that adversely affect one's perception of a person or group. Awareness of implicit bias has been increasing in the realm of diabetes care. Here, the authors highlight several types of unconscious bias on the part of clinicians and patients, including biases based on race, ethnicity, and obesity. They discuss how these biases can negatively affect patient-centered clinical interactions and diabetes care delivery, and they recommend implementation of evidence-based interventions and other health system policy approaches to reduce the potential impact of such biases in health care settings.

Emotional Distress Predicts Reduced Type 2 Diabetes Treatment Adherence in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).

OBJECTIVE: We examined longitudinal associations between emotional distress (specifically, depressive symptoms and diabetes distress) and medication adherence in Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE), a large randomized controlled trial comparing four glucose-lowering medications added to metformin in adults with relatively recent-onset type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: The Emotional Distress Substudy assessed medication adherence, depressive symptoms, and diabetes distress in 1,739 GRADE participants via self-completed questionnaires administered biannually up to 3 years. We examined baseline depressive symptoms and diabetes distress as predictors of medication adherence over 36 months. Bidirectional visit-to-visit relationships were also examined. Treatment satisfaction, beliefs about medication, diabetes care self-efficacy, and perceived control over diabetes were evaluated as mediators of longitudinal associations. RESULTS: At baseline, mean ± SD age of participants (56% of whom were White, 17% Hispanic/Latino, 18% Black, and 66% male) was 58.0 ± 10.2 years, diabetes duration 4.2 ± 2.8 years, HbA1c 7.5% ± 0.5%, and medication adherence 89.9% ± 11.1%. Higher baseline depressive symptoms and diabetes distress were independently associated with lower adherence over 36 months (P < 0.001). Higher depressive symptoms and diabetes distress at one visit predicted lower adherence at the subsequent 6-month visit (P < 0.0001) but not vice versa. Treatment assignment did not moderate relationships. Patient-reported concerns about diabetes medications mediated the largest percentage (11.9%-15.5%) of the longitudinal link between emotional distress and adherence. CONCLUSIONS: Depressive symptoms and diabetes distress both predict lower adherence to glucose-lowering medications over time among adults with T2DM. Addressing emotional distress and concerns about anticipated negative effects of taking these treatments may be important to support diabetes treatment adherence.

Hospital Equity Rating Metrics-Promise, Pitfalls, and Perils.

This Viewpoint addresses several considerations regarding equity metrics across hospital regulatory and accrediting organizations and suggestions for improvement.

Endocrine Health and Health Care Disparities in the Pediatric and Sexual and Gender Minority Populations: An Endocrine Society Scientific Statement.

Endocrine care of pediatric and adult patients continues to be plagued by health and health care disparities that are perpetuated by the basic structures of our health systems and research modalities, as well as policies that impact access to care and social determinants of health. This scientific statement expands the Society's 2012 statement by focusing on endocrine disease disparities in the pediatric population and sexual and gender minority populations. These include pediatric and adult lesbian, gay, bisexual, transgender, queer, intersex, and asexual (LGBTQIA) persons. The writing group focused on highly prevalent conditions-growth disorders, puberty, metabolic bone disease, type 1 (T1D) and type 2 (T2D) diabetes mellitus, prediabetes, and obesity. Several important findings emerged. Compared with females and non-White children, non-Hispanic White males are more likely to come to medical attention for short stature. Racially and ethnically diverse populations and males are underrepresented in studies of pubertal development and attainment of peak bone mass, with current norms based on European populations. Like adults, racial and ethnic minority youth suffer a higher burden of disease from obesity, T1D and T2D, and have less access to diabetes treatment technologies and bariatric surgery. LGBTQIA youth and adults also face discrimination and multiple barriers to endocrine care due to pathologizing sexual orientation and gender identity, lack of culturally competent care providers, and policies. Multilevel interventions to address these disparities are required. Inclusion of racial, ethnic, and LGBTQIA populations in longitudinal life course studies is needed to assess growth, puberty, and attainment of peak bone mass. Growth and development charts may need to be adapted to non-European populations. In addition, extension of these studies will be required to understand the clinical and physiologic consequences of interventions to address abnormal development in these populations. Health policies should be recrafted to remove barriers in care for children with obesity and/or diabetes and for LGBTQIA children and adults to facilitate comprehensive access to care, therapeutics, and technological advances. Public health interventions encompassing collection of accurate demographic and social needs data, including the intersection of social determinants of health with health outcomes, and enactment of population health level interventions will be essential tools.

Disruptive Innovations to Achieve Health Equity Through Healthcare and Research Transformation.

In order to achieve health equity, we must implement innovative health system, public health, and policy-level interventions to address the historical root causes of structural and institutional racism embedded in our medical and social systems. A history of unconsented medical and research experimentation on vulnerable groups and residual healthcare provider biases toward minoritized patients has led to patient distrust of medical systems and poor quality of care. Historical discriminatory housing and lending policies resulted in racial residential segregation and neighborhoods with inadequate housing, healthy food access, and educational resources, resulting in present-day social determinants of health (SDOH). To reduce these disparities and achieve health equity, four disruptive healthcare innovations are recommended: (i) infuse health equity principles into clinical workflows by implementing National Culturally and Linguistically Appropriate Services Standards; (ii) address poverty-related SDOH; (iii) deliver care and recruit for research in nonclinical settings to reach marginalized communities; and (iv) leverage health system subject matter experts to advocate for health equity policies. During the COVID-19 pandemic we leveraged the diversity of our workforce to deliver bilingual and culturally tailored COVID-19 testing, education, and vaccines to the Hispanic and Black communities in nonclinical settings, the primary marginalized communities served by our health system that were also disproportionately impacted by COVID-19 infections, hospitalizations, and deaths. Now that we understand the importance of using innovative health equity strategies to reach marginalized communities, we must continue to re-engineer our healthcare systems to deliver care outside of our brick and mortar to overcome barriers in access to care and mistrust in the healthcare establishment stemming from past abuses and remaining experiences of bias.

Organizations in science and medicine must hold each other accountable for discriminatory practices.

Many organizations persist in working with others that engage in known, remediable structural discrimination. We name this practice interorganizational structural discrimination (ISD) and argue it is a pivotal contributor to inequities in science and medicine. We urge organizations to leverage their relationships and demand progress from collaborators.

Modernizing Diabetes Care Quality Measures.

The proliferation of diabetes quality measures in the US since the mid-1990s has increased the burden of measurement without commensurate improvements in the quality of care or health outcomes. Measures in use today do not represent or incentivize achievement of care goals in all domains of quality that are necessary to achieve optimal diabetes health. We recommend reimagining and improving diabetes quality measurement through the following propositions: widespread adoption of new measures and modernization of existing measures across six domains of quality; use of a subset of new and modernized metrics as top-line measures for reporting and reimbursement; and optional use of the remaining new and modernized measures for evaluative purposes at all levels of the care delivery system to identify and address gaps in care quality and outcomes. These propositions would support practices and policies at all levels of the health care system to improve the health of people with diabetes.

Determinants of Metabolic Syndrome and Type 2 Diabetes in the Absence of Obesity: The Jackson Heart Study.

Context: Multiple studies suggest that adults who were normal weight at diabetes diagnosis are at higher risk for all-cause mortality than those who had overweight or obesity at diagnosis. Objective: While obesity is a known risk factor for cardiometabolic disease, differences in body fat distribution in those without obesity are understudied, especially in African Americans. Methods: In 1005 participants of the Jackson Heart Study, without cardiovascular disease at baseline, we used logistic regression to investigate the longitudinal association of body fat distribution by CT scan with metabolic syndrome (MetS) or type 2 diabetes (T2D). We used the harmonized International Diabetes Federation criteria to define MetS. We included only normal weight or overweight participants (BMI: 18.5 to < 30.0 kg/m2). We created separate models for MetS and T2D adjusted for a standard set of covariates. We excluded participants with prevalent MetS or T2D, respectively in sensitivity. Results: Higher visceral fat, subcutaneous fat, BMI, and insulin resistance (HOMA-IR) were significantly associated with MetS and T2D after adjustment. Visceral fat was strongly associated with both outcomes (MetS OR = 2.07 [1.66-2.68]; T2D OR = 1.51 [1.21-1.88]), and the association for MetS persisted in the normal weight only group. Estimates were robust to sensitivity analysis and were only modestly mediated by insulin resistance. Physical activity was not associated with MetS or T2D. Conclusion: Visceral fat is strongly associated with developing MetS, even in normal weight individuals, suggesting that excess visceral fat plays a role in cardiometabolic risk beyond that of overall adiposity and obesity in African Americans.

Association of Area-Level Socioeconomic Deprivation With Hypoglycemic and Hyperglycemic Crises in US Adults With Diabetes.

Importance: Social determinants of health play a role in diabetes management and outcomes, including potentially life-threatening complications of severe hypoglycemia and diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar state (HHS). Although several person-level socioeconomic factors have been associated with these complications, the implications of area-level socioeconomic deprivation are unknown. Objective: To examine the association between area-level deprivation and the risks of experiencing emergency department visits or hospitalizations for hypoglycemic and hyperglycemic crises (ie, DKA or HHS). Design, Setting, and Participants: This cohort study used deidentified administrative claims data for privately insured individuals and Medicare Advantage beneficiaries across the US. The analysis included adults with diabetes who met the claims criteria for diabetes between January 1, 2016, and December 31, 2017. Data analyses were performed from November 17, 2020, to November 11, 2021. Exposures: Area deprivation index (ADI) was derived for each county for 2016 and 2017 using 17 county-level indicators from the American Community Survey. ADI values were applied to patients who were living in each county based on their index dates and were categorized according to county-level ADI quintile (with quintile 1 having the least deprivation and quintile 5 having the most deprivation). Main Outcomes and Measures: The numbers of emergency department visits or hospitalizations related to the primary diagnoses of hypoglycemia and DKA or HHS (ascertained using validated diagnosis codes in the first or primary position of emergency department or hospital claims) between 2016 and 2019 were calculated for each ADI quintile using negative binomial regression models and adjusted for patient age, sex, health plan type, comorbidities, glucose-lowering medication type, and percentage of White residents in the county. Results: The study population included 1 116 361 individuals (563 943 women [50.5%]), with a mean (SD) age of 64.9 (13.2) years. Of these patients, 343 726 (30.8%) resided in counties with the least deprivation (quintile 1) and 121 810 (10.9%) lived in counties with the most deprivation (quintile 5). Adjusted rates of severe hypoglycemia increased from 13.54 (95% CI, 12.91-14.17) per 1000 person-years in quintile 1 counties to 19.13 (95% CI, 17.62-20.63) per 1000 person-years in quintile 5 counties, corresponding to an incidence rate ratio of 1.41 (95% CI, 1.29-1.54; P < .001). Adjusted rates of DKA or HHS increased from 7.49 (95% CI, 6.96-8.02) per 1000 person-years in quintile 1 counties to 8.37 (95% CI, 7.50-9.23) per 1000 person-years in quintile 5 counties, corresponding to an incidence rate ratio of 1.12 (95% CI, 1.00-1.25; P = .049). Conclusions and Relevance: This study found that living in counties with a high area-level deprivation was associated with an increased risk of severe hypoglycemia and DKA or HHS. The concentration of these preventable events in areas of high deprivation signals the need for interventions that target the structural barriers to optimal diabetes management and health.

The Financial Impact of an Inpatient Diabetes Management Service.

CONTEXT: Diabetes is a leading metabolic disorder with a substantial cost burden, especially in inpatient settings. The complexity of inpatient glycemic management has led to the emergence of inpatient diabetes management service (IDMS), a multidisciplinary team approach to glycemic management. OBJECTIVE: To review recent literature on the financial and clinical impact of IDMS in hospital settings. METHODS: We searched PubMed using a combination of controlled vocabulary and keyword terms to describe the concept of IDMS and combined the search terms with a comparative effectiveness filter for costs and cost analysis developed by the National Library of Medicine. FINDINGS: In addition to several improved clinical endpoints such as glycemic management outcomes, IDMS implementation is associated with hospital cost savings through decreased length of stay, preventing hospital readmissions, hypoglycemia reduction, and optimizing resource allocation. There are other downstream potential cost savings in long-term patient health outcomes and avoidance of litigation related to suboptimal glycemic management. CONCLUSION: IDMS may play an important role in helping both academic and community hospitals to improve the quality of diabetes care and reduce costs. Clinicians and policymakers can utilize existing literature to build a compelling business case for IDMS to hospital administrations and state legislatures in the era of value-based healthcare.

Development and Validation of a Machine Learning Model to Predict Near-Term Risk of Iatrogenic Hypoglycemia in Hospitalized Patients.

Importance: Accurate clinical decision support tools are needed to identify patients at risk for iatrogenic hypoglycemia, a potentially serious adverse event, throughout hospitalization. Objective: To predict the risk of iatrogenic hypoglycemia within 24 hours after each blood glucose (BG) measurement during hospitalization using a machine learning model. Design, Setting, and Participants: This retrospective cohort study, conducted at 5 hospitals within the Johns Hopkins Health System, included 54 978 admissions of 35 147 inpatients who had at least 4 BG measurements and received at least 1 U of insulin during hospitalization between December 1, 2014, and July 31, 2018. Data from the largest hospital were split into a 70% training set and 30% test set. A stochastic gradient boosting machine learning model was developed using the training set and validated on internal and external validation. Exposures: A total of 43 clinical predictors of iatrogenic hypoglycemia were extracted from the electronic medical record, including demographic characteristics, diagnoses, procedures, laboratory data, medications, orders, anthropomorphometric data, and vital signs. Main Outcomes and Measures: Iatrogenic hypoglycemia was defined as a BG measurement less than or equal to 70 mg/dL occurring within the pharmacologic duration of action of administered insulin, sulfonylurea, or meglitinide. Results: This cohort study included 54 978 admissions (35 147 inpatients; median [interquartile range] age, 66.0 [56.0-75.0] years; 27 781 [50.5%] male; 30 429 [55.3%] White) from 5 hospitals. Of 1 612 425 index BG measurements, 50 354 (3.1%) were followed by iatrogenic hypoglycemia in the subsequent 24 hours. On internal validation, the model achieved a C statistic of 0.90 (95% CI, 0.89-0.90), a positive predictive value of 0.09 (95% CI, 0.08-0.09), a positive likelihood ratio of 4.67 (95% CI, 4.59-4.74), a negative predictive value of 1.00 (95% CI, 1.00-1.00), and a negative likelihood ratio of 0.22 (95% CI, 0.21-0.23). On external validation, the model achieved C statistics ranging from 0.86 to 0.88, positive predictive values ranging from 0.12 to 0.13, negative predictive values of 0.99, positive likelihood ratios ranging from 3.09 to 3.89, and negative likelihood ratios ranging from 0.23 to 0.25. Basal insulin dose, coefficient of variation of BG, and previous hypoglycemic episodes were the strongest predictors. Conclusions and Relevance: These findings suggest that iatrogenic hypoglycemia can be predicted in a short-term prediction horizon after each BG measurement during hospitalization. Further studies are needed to translate this model into a real-time informatics alert and evaluate its effectiveness in reducing the incidence of inpatient iatrogenic hypoglycemia.

Casting a Health Equity Lens on Endocrinology and Diabetes.

As endocrinologists we have focused on biological contributors to disparities in diabetes, obesity and other endocrine disorders. Given that diabetes is an exemplar health disparity condition, we, as a specialty, are also positioned to view the contributing factors and solutions more broadly. This will give us agency in contributing to health system, public health, and policy-level interventions to address the structural and institutional racism embedded in our medical and social systems. A history of unconsented medical and research experimentation on vulnerable groups and perpetuation of eugenics theory in the early 20th century have resulted in residual health care provider biases toward minority patients and patient distrust of medical systems, leading to poor quality of care. Historical discriminatory housing and lending policies resulted in racial residential segregation and neighborhoods with inadequate housing, healthy food access, and educational resources, setting the foundation for the social determinants of health (SDOH) contributing to present-day disparities. To reduce these disparities we need to ensure our health systems are implementing the National Standards for Culturally and Linguistically Appropriate Services in Health and Health Care to promote health equity. Because of racial biases inherent in our medical systems due to historical unethical practices in minority communities, health care provider training should incorporate awareness of unconscious bias, antiracism, and the value of diversity. Finally, we must also address poverty-related SDOH (eg, food and housing insecurity) by integrating social needs into medical care and using our voices to advocate for social policies that redress SDOH and restore environmental justice.

Second Victims: Aftermath of Gun Violence and Faith-Based Responses.

In the aftermath of gun violence, those impacted and left to mourn are regarded as second victims. These individuals experience and are often burdened by mental and physical sequelae while attempting to cope with the trauma. The objective of this report is to highlight the support and resources of congregational and faith-based leaders available in an urban city with a high prevalence of gun violence. We describe information and insights presented during a symposium uniting medical-religious partners to discuss actions and programs to address trauma from gun violence. Faith-based persons from various Abrahamic religions, ranging from imams to reverends to hospital-based chaplains, discussed key strategies to allocate resources to second victims. These strategies included religious rituals meant to cope with trauma, memorials, and providing insight into resiliency for difficult times. Resources were identified for both within the hospital and community. Such medical-religious resources should be considered for future interventions which aim to attenuate the consequences of gun violence for second victims.

Determinants of mental health outcomes among people with and without diabetes during the COVID-19 outbreak in the Arab Gulf Region.

AIMS: To determine the prevalence and factors associated with depression and anxiety among people with and without diabetes during the coronavirus disease 2019 (COVID-19) outbreak. METHODS: A cross-sectional questionnaire-based study collecting demographic and mental health data from 2166 participants living in the Arab Gulf region (568 with diabetes, 1598 without diabetes). Depression and anxiety were assessed using the 9-item Patient Health Questionnaire and the 7-item Generalized Anxiety Disorder scale, respectively. RESULTS: The prevalence of depression and anxiety symptoms were 61% and 45%, in people with diabetes (PWD) and 62% and 44%, respectively, in people without diabetes. PWD who have had their diabetes visit canceled by the clinic were more likely to report depression and anxiety symptoms than those without diabetes (odds ratio [95% confidence interval]: 1.37 [1.02, 1.84] and 1.37 [1.04, 1.80], for depression and anxiety; respectively). PWD who had no method of telecommunication with their health care providers (HCP) during the pandemic, PWD with A1C of ≥ 10%, women, employees (particularly HCPs), students, unmarried individuals, and those with lower income were more likely to report depression and/or anxiety symptoms (all P < 0.01). Fear of acquiring the coronavirus infection; running out of diabetes medications; or requiring hospitalization for hypoglycemia, hyperglycemia, or diabetic ketoacidosis; and lack of telecommunication with HCPs were all associated with significantly higher odds of having depression and anxiety symptoms among PWD. CONCLUSIONS: The remarkably high prevalence of depression and anxiety symptoms during the COVID-19 pandemic, particularly among subgroups of PWD, calls for urgent public health policies to address mental health during the pandemic and reestablish health care access for PWD.