About

Dr. Elbert Huang is a Professor of Medicine and the founding Director of the Center for Chronic Disease Research and Policy at the University of Chicago. He also serves as the Associate Director of the Chicago Center for Diabetes Translation Research. Between 2010 and 2011, Dr. Huang was a Senior Advisor in the Office of the Assistant Secretary for Planning and Evaluation at the Department of Health and Human Services. As a general internist, his research focuses on clinical and health care policy issues at the intersection of diabetes, aging, and health economics. His primary research area is medical decision making for elderly patients with type 2 diabetes, particularly addressing the uncertainty in individualizing diabetes treatments based on clinical parameters and patient preferences. His work has influenced care recommendations for older patients with diabetes.

Research topics

• Medicine
• Internal medicine
• Biochemistry
• Endocrinology
• Cardiology
• Oncology
• Emergency medicine
• Gynecology
• Psychiatry
• Gerontology
• Intensive care medicine

Selected publications

• Stakeholder engagement in genetics research development in diverse urban communities in the Midwestern United States: process and considerations

  Frontiers in Medicine · 2026-05-08

  articleOpen access

  Introduction The inclusion of individuals from diverse backgrounds is essential to enhancing the generalizability and interpretability of genetic testing results. It is imperative to foster stakeholder engagement at all steps in the research process in diverse communities, given past and present experiences of marginalization and discrimination in healthcare research. A stakeholder engagement workshop was convened to provide input on study design and community priorities for genetic research in diverse communities. Methods Seventeen stakeholders including primary care providers (PCP) and patient advocates from diverse communities provided anonymous quantitative (ranking exercises) and qualitative (group discussion) input during a 2-h web-based workshop. Stakeholders discussed the following topics: prioritization of conditions to include in community-based genetic screening research and considerations for genetic research development and design in diverse communities. Emergent themes were noted and summarized to inform future research development. Results Community stakeholder discussion themes included: rationale for conditions to include in community-based genetic screening, strategies for community trust-building, the importance of actionability and support following results, provision of informational support related to genetic testing privacy issues and protections, and inclusion of genetic testing education for both PCPs and community members. Discussion During this workshop, stakeholder input addressed considerations across the research continuum from study conceptualization to the application of findings in diverse community settings. Stakeholders’ comments provide valuable insights on the development of a genetic screening program that incorporates their input from the beginning to beyond the completion of the study period.

  PublisherDOI

• Effectiveness of Interventions to Improve Glycemic Control in US Asian and Pacific Islander Populations With Type 2 Diabetes: Systematic Review and Meta-Analysis

  Asian/Pacific Island Nursing Journal · 2026-04-30

  articleOpen access

  Background: Asian American and Pacific Islander populations are disproportionately affected by diabetes. Objective: The purpose of this study was to assess the efficacy of nonpharmacologic interventions in reducing hemoglobin A1c (HbA1c) levels among Asian American or Pacific Islander individuals with type 2 diabetes. Methods: A systematic review was conducted using the PubMed, Scopus, PsycInfo, and CINAHL databases, covering studies published from 1985 to 2019. Eligible studies were randomized controlled trials that evaluated nonpharmacologic interventions in outpatient settings for adults with type 2 diabetes in the United States, with at least 50% Asian American or Pacific Islander participants. Data extraction and risk of bias assessment were independently performed by 2 reviewers for each trial. The Cochrane Collaboration risk of bias tool and the Grading of Recommendations, Assessment, Development, and Evaluation approach were used to evaluate quality. Random-effects meta-analyses were conducted to estimate pooled effect sizes. Results: A total of 1835 articles were screened, with 9 randomized controlled trials meeting the inclusion criteria, comprising 1492 participants, with a median follow-up duration of 6 (IQR 3-12) months. Interventions included diabetes self-management education, bilingual counseling, glucose or weight monitoring, motivational interviewing, and financial support, often tailored to the cultural context of the participants. Pooled analysis of the 9 trials demonstrated a significant average HbA1c reduction of -0.39% (95% CI -0.64% to -0.14%; I²=65%). Seven studies were judged to have a low risk of bias, 1 study had some concerns, and 1 study was assessed as high risk. The overall strength of evidence was high. Conclusions: Nonpharmacologic interventions substantively reduced HbA1c levels in Asian American or Pacific Islander individuals with type 2 diabetes, particularly when culturally and linguistically tailored.

  PublisherDOI

• Effect of an IT‐based social care intervention for dementia caregivers on unmet resource needs

  Alzheimer s & Dementia · 2025-12-01

  articleOpen access

  Interventions for dementia caregivers should be scalable and available at the point of care. CommunityRx-Dementia (CRxD) is an IT-based intervention to improve caregiver outcomes by providing information about local community resources and connection to a resource navigator and online resource finder. We compared self-reported unmet needs and resource knowledge among 343 caregivers enrolled in a randomized trial of CRxD vs usual care (UC). At baseline,1 and 3 months, caregivers' reported their knowledge of and need for any of 14 resource types (e.g., respite care, end-of-life planning, food) and, at 12 months, they reported their use of acute care. For the outcomes of knowledge and needs, mixed-effects regression models were fit with treatment arm, time, treatment arm by time interaction and baseline knowledge or needs as predictors. For acute care utilization outcomes, negative binomial regression models were fit with treatment group and baseline utilization as predictors. Incidence rate ratios (IRR) and corresponding 95% CIs were calculated. Participants (78% women, 81% non-Hispanic Black, 49% aged 50-64, 64% income ≥$50k/year) included both newer (22% 6 months-2 years) and more experienced caregivers (44% > 5 years). At baseline, caregivers in both study arms reported an average of 4 unmet needs (87% ≥1, 65% ≥3, most often [61%] for caregiver education), and knew of an average of 6 resources. At 3 months, the number of known resources was greater in the CRxD than UC group (6.5 vs 5.2; β: 1.0, 95% CI 0.3, 1.7) and the number of unmet needs was lower (2.8 vs 3.6; β: -0.5, 95% CI -1.1, 0.0). Over 12 months, caregivers in CRxD had lower ED visits rates than UC participants (0.3 vs 0.5; IRR: 0.6, 95% CI 0.3, 0.9) but similar hospitalization rates (0.1 vs 0.2; IRR: 0.7, 95% CI 0.3, 1.2). This low-intensity social care intervention for dementia caregivers may improve knowledge of available resources, decrease unmet needs, and reduce caregivers' use of emergency care.

  PublisherOA PDFDOI

• Caring for dementia caregivers: How well does social risk screening reflect unmet needs?

  Health Services Research · 2025-04-01

  articleOpen access
  PublisherOA PDFDOI

• Challenges and Opportunities for Improving Care for Type 1 Diabetes in Older Adulthood

  Diabetes Care · 2025-11-20

  articleOpen access

  As care for type 1 diabetes (T1D) advances, the number of adults with T1D living into older adulthood (ages ≥65 years) continues to grow. The population of older adults with T1D is highly heterogeneous, and over the life span, various factors may change over time while others may not, necessitating an individualized approach to management. A key care consideration for people with T1D is the ongoing need for exogenous insulin replacement intensive self-monitoring for effective management. At the same time, growing older may bring changes such as increased risk of misdiagnosis of T1D as type 2 diabetes, greater vulnerability to hypoglycemia, accumulating comorbidities and complications, declining independence due to geriatric syndromes, and a growing need for support in using diabetes technologies and navigating complex care transitions. Given the unique clinical and management needs of this population, we sought to present key care challenges in this population and suggest strategies to optimize quality of care in older adults with T1D, including 1) integrating geriatric screenings, age-friendly care frameworks, and regular reassessments into routine T1D management; 2) developing tailored care approaches for cognitive impairment; 3) establishing support systems for diabetes technology use in primary and long-term care settings; and 4) ensuring insurance coverage and access to diabetes technologies and therapies. Forward-thinking strategies to optimize care include individualized glycemic goal setting, the development and adoption of care models that support continuity of diabetes technology use, and individualized management strategies that consider of the goals and capabilities of the person living with T1D and care partners.

  PublisherOA PDFDOI

• Biases in the performance of FRAX without BMD in predicting fracture risk in a multiethnic population with diabetes: the Diabetes and Aging Study

  Journal of Bone and Mineral Research · 2025-01-29 · 7 citations

  articleOpen access

  Fracture risk calculators, such as the Fracture Risk Assessment Tool (FRAX), calculate the risk of major osteoporotic fracture (MOF) and hip fracture but do not account for the excess risk of fracture in people with diabetes. We examined the predictive performance of FRAX without BMD in ethnically diverse, older patients with diabetes. Patients included were between ages 65 and 89 from the Kaiser Permanente Northern California Diabetes Registry and not already taking osteoporosis medications. Race and ethnicity were self-identified. We calculated FRAX without BMD based on baseline characteristics and assessed how well FRAX predicted MOF and hip fracture over follow-up. Predictive performance was based on measures of discrimination (area under the receiver operator curve, AUC) and calibration (observed-to-predicted ratio, O/P). We identified 96 914 patients (47.0% female), of whom 5383 (5.6%) and 1767 (1.8%) had MOF and hip fracture, respectively, over a mean follow-up of 4.3 yr. The AUC for MOF and hip fracture were 0.72 and 0.77, respectively. FRAX mildly underestimated MOF and hip fracture rates (O/P 1.2 for both) overall. Discrimination was similar by race and ethnicity and diabetes duration but was worse in those over age 75 (AUC < 0.7). In some groups, there were substantial calibration errors, such as Hispanic women (O/P: 1.8 and 1.5), Black men (O/P: 1.5 and 1.8), those with duration of diabetes ≥20 yr (O/P: 1.6 and 1.5), and those over the age of 80 (O/P: 1.4 and 1.2) for MOF and hip fracture, respectively. While the discriminatory performance of FRAX without BMD was good overall in patients with diabetes, it underestimated risk in Hispanic women, Black men, those with long duration of diabetes, and in the oldest patients with diabetes. These algorithmic biases suggest that diabetes-specific tools may be needed to stratify fracture risk in patients with diabetes.

  PublisherOA PDFDOI

• Preparing to Meet the Needs of a Growing Older Adult Population with Type 1 Diabetes: A Narrative Review

  Journal of General Internal Medicine · 2025-12-08 · 1 citations

  articleOpen access
  PublisherOA PDFDOI

• Development and Internal Validation of the Multiethnic Type 2 Diabetes Outcomes Model for the U.S. (DOMUS)

  2025-09-25

  articleOpen access

  &lt;p dir="ltr"&gt;OBJECTIVE: The objective of this study was to develop and internally validate a mathematical model of the relationships between patient clinical and social risk factors and outcomes using data from a multiethnic population with type 2 diabetes.&lt;/p&gt;&lt;p dir="ltr"&gt;RESEARCH DESIGN AND METHODS: We constructed an incidence cohort of all adults (18 years or older) with newly diagnosed type 2 diabetes in the Kaiser Permanente Northern California (KPNC) healthcare system between 2005 and 2016 (N=129,000), following patients for at least 1 year, but up to 12 years. Using this cohort, we modeled 17 distinct diabetes-related outcomes related to micro and macrovascular disease, as well as atrial fibrillation, depression, and dementia, relevant biomarkers, and mortality. &lt;/p&gt;&lt;p dir="ltr"&gt;RESULTS: Data were randomly split into 50%, 25%, and 25% samples to perform model estimation, calibration, and validation, respectively. Empirical and simulated data were similar for the events and biomarkers, but some factors required calibration, but after calibration, they closely aligned empirical estimates. &lt;/p&gt;&lt;p dir="ltr"&gt;CONCLUSIONS: DOMUS is a major step forward in understanding diabetes progression and the role of social determinants of health. This model can be used by scientists, policymakers, and health system managers to better understand how choices can impact population health and health disparities, including the broad diversity of U.S. races and ethnicities. Moreover, this model can be used to realize longer-term comparative effectiveness in cost-effectiveness analyses for diabetes management in the future.&lt;/p&gt;

  PublisherDOI

• AI analysis of medical images at scale as a health disparities probe: a feasibility demonstration using chest radiographs.

  PubMed · 2025-04-08

  preprintOpen access

  Objectives: Health disparities (differences in non-genetic conditions that influence health) can be associated with differences in burden of disease by groups within a population. Social determinants of health (SDOH) are domains such as health care access, dietary access, and economics frequently studied for potential association with health disparities. Evaluating SDOH-related phenotypes using routine medical images as data sources may enhance health disparities research. We developed a pipeline for using quantitative measures automatically extracted from medical images as inputs into health disparities index calculations. Methods: Our study focused on the use case of two SDOH demographic correlates (sex and race) and data extracted from chest radiographs of 1,571 unique patients. The likelihood of severe disease within the lung parenchyma from each image type, measured using an established deep learning model, was merged into a single numerical image-based phenotype for each patient. Patients were then separated into phenogroups by unsupervised clustering of the image-based phenotypes. The 'health rate' for each phenogroup was defined as the median image-based phenotype for each SDOH used as inputs to four imaging-derived health disparities indices (iHDIs): one absolute measure (between-group variance) and three relative measures (index of disparity, Theil index, and mean log deviation). Results: The iHDI measures demonstrated feasible values for each SDOH demographic correlate, showing potential for medical images to serve as a novel probe for health disparities. Conclusions: Large-scale AI analysis of medical images can serve as a probe for a novel data source for health disparities research. Advances in knowledge: We have demonstrated the feasibility of using data extracted from medical images as inputs to health disparities indices, making possible their future use in data dashboards.

  PublisherOA PDF

• A social care assistance intervention for dementia caregivers reduces emergency care utilization

  Health Services Research · 2025-04-01

  articleOpen accessSenior author

  of 58Waiver implementation and understanding how Medicaid benefits may better meet member needs.Methods: Using a mixed methods approach, program data (collected during referral, enrollment, ongoing check-ins, and through invoices), participant surveys and interviews, and healthcare claims were leveraged to understand utilization, experiences, and impact, and qualitative interviews were conducted with staff from participating community-based organizations to understand program implementation and lessons learned.Results: Over 700 members were referred, and the majority of enrollees (n = 516) entered from a substance use residential programs, corrections, or foster care.The most frequent services received were housing navigation, monthly rent support, move-in support, and utility assistance.Average rent support totaled $10,245.The population with the highest total benefit utilization was individuals transitioning out of corrections.Staff interviews highlighted the importance of shared visions and expectations among stakeholders, program infrastructure, and staff training and support for successful implementation.Participant surveys and interviews revealed challenges and successes with program experiences and impacts on housing stability.Conclusion: Across the nation, Medicaid is stepping into the housing space to improve adverse health outcomes associated with housing insecurity.This pilot informs ongoing efforts to implement housing supports and build stronger cross-sector collaboration as part of Medicaid-covered benefits.

  PublisherOA PDFDOI

Recent grants

• Research and Mentorship in Medical Decision Making for Chronic Diseases of Older Adults

  NIH · $466k · 2020–2025

• NIH Grant R01HS018542

  NIH · $1.3M · 2017

• NIH Grant K24DK105340

  NIH · $884k · 2020

• Research and Mentorship in Medical Decision Making for Chronic Diseases of Older Adults

  NIH · $117k · 2020–2025

• Optimizing Medical Decision Making for Older Patients with Type 2 Diabetes

  NIH · $3.2M · 2019–2024

Frequent coauthors

• Marshall H. Chin

  University of Chicago

  191 shared

• Cynthia T. Schaefer

  Ivy Tech Community College of Indiana

  106 shared

• Loretta Heuer

  Icahn School of Medicine at Mount Sinai

  93 shared

• Sydney E. S. Brown

  University of Michigan–Ann Arbor

  88 shared

• Melinda L. Drum

  University of Tennessee at Knoxville

  84 shared

• Michael T. Quinn

  University of Chicago

  81 shared

• Jessica Graber

  79 shared

• Amy E. Schlotthauer

  Medical College of Wisconsin

  68 shared

Labs

• UChicago Center for Chronic Disease Research and PolicyPI

Education

• MD

  Harvard Medical School

  1996

Awards & honors

• Awards at the 2026 Society of General Internal Medicine Annu…