About

Steven Edelman is a faculty member in the Department of Medicine at UC San Diego, with a focus on clinical research related to diabetes and endocrinology. His research activities include studying the kinetics of in vivo glucose uptake in diabetes, the impact of continuous glucose monitoring on adherence and healthcare costs, and the development of digital health technologies for insulin initiation and optimization. Edelman has contributed to understanding therapeutic strategies such as inhaled insulin therapy, insulin pump technology, and the management of type 2 diabetes with digital therapeutics. His work emphasizes improving glycemic outcomes, patient experiences, and addressing challenges in diabetes management through innovative clinical approaches and technology integration.

Research topics

• Medicine
• Endocrinology
• Internal medicine
• Physical therapy
• Mathematics
• Urology
• Statistics

Selected publications

• Cortisol’s role in difficult-to-control type 2 diabetes: Insights from the CATALYST study—a plain language review

  Current Medical Research and Opinion · 2026-05-13

  article
  PublisherDOI

• Integrating the Glycemia Risk Index Into Clinical Practice and Research: A Consensus Report

  Journal of Diabetes Science and Technology · 2026-03-07

  articleOpen access

  A panel of experts in the use of continuous glucose monitoring (CGM) data in the treatment of diabetes met in Burlingame, California on October 27, 2025 to discuss the utility of the glycemia risk index (GRI) for clinical care research and population health management. The GRI composite metric is a single number (on a 0-100 percentile scale-lower is better) based on an expert-determined weighting of the seven individual components in the existing ambulatory glucose profile (AGP). The GRI describes the quality of glycemia based on glucose values collected in a 14-day CGM tracing, thus providing additional insights into CGM profiles beyond the AGP. During the meeting, the mathematical derivation of the GRI metric was presented along with its use for adult and pediatric individuals with diabetes and cancer who require medications that can adversely affect the glucose concentration. Examples where the GRI provided useful insights into the quality of CGM tracings were also discussed by the expert panel. In addition, a new smartphone application, the GRI Calculator, was presented. This app calculates the GRI of a CGM tracing and provides visualization of sequential CGM tracings for a specific individual. The GRI provides a reference measurement for the accuracy of artificial intelligence (AI) models assigning levels of glycemic quality to CGM tracings intended to match the assessments of clinicians. The GRI is now part of the data visualization panel for the Integration of Connected Diabetes Device Data into the Electronic Health Record (iCoDE-2) project, which standardizes both CGM and insulin dosing data. Further exploration of the potential value of the GRI for non-insulin users needs to be undertaken. The panel unanimously recommended that CGM manufacturers and developers of data visualization software for CGMs add the GRI to their data platforms for insulin users.

  PublisherDOI

• Improved glycemic outcomes in people with type 2 diabetes using smart blood glucose monitoring integrated with popular digital health therapeutics

  Scientific Reports · 2025-03-14 · 4 citations

  articleOpen accessSenior author

  The increasing prevalence of metabolic syndrome and type 2 diabetes places a burden on healthcare systems, necessitating cost-effective, engaging and accessible interventions to address the underlying behavioral and lifestyle drivers. Our study evaluated combining Bluetooth connected OneTouch blood glucose meters (BGM) and the OneTouch Reveal mobile app with one of four digital therapeutic apps. Each group was independent, with people with type 2 diabetes (PwT2D) themselves choosing their therapeutic intervention, to better reflect real-world use. Our 3-month decentralized study screened 912 subjects, with 612 returning mail-in A1cs, providing 191 subjects (Noom = 68, Fitbit = 31, Cecelia Health = 47, Welldoc = 45) who met all inclusion criteria, including entry A1c 7.5 to 12.0%. The primary endpoint of A1c change showed improvement in the overall group by - 0.77% (95% CI - 0.98 to - 0.56, n = 141) after 3-months, Noom - 1.03% (CI - 1.4 to - 0.61, n = 49), Fitbit - 0.56% (CI - 1.0 to - 0.11, n = 24), Cecelia Health - 0.76% (CI - 1.2 to - 0.36, n = 36), Welldoc - 0.55% (CI - 0.94 to - 0.17, n = 32). In terms of secondary endpoints, more than half (56%) of these PwT2D lowered A1c by ≥ 0.5% and more than a third (36%) lowered A1c by ≥ 1.0%, with similar improvements across each of the four independent groups. Our real-world approach shows the potential for connected BGMs and widely accessible digital therapeutics to contribute to improvements in glycemic outcomes.

  PublisherOA PDFDOI

• Risk of new‐onset type 1 diabetes in individuals with celiac disease and thyroid disease—An observational study

  Diabetes Obesity and Metabolism · 2025-05-28 · 7 citations

  articleOpen access1st authorCorresponding

  AIMS: The objective of this study was to compare the risk of developing type 1 diabetes in individuals with celiac disease, hyperthyroidism and hypothyroidism to that of individuals without those conditions. MATERIALS AND METHODS: In this retrospective, observational, matched-cohort study based on real-world claims data, individuals with at least one diagnosis of celiac disease, hyperthyroidism (e.g. Graves' disease) or hypothyroidism (e.g. Hashimoto's disease) and a control cohort of individuals without any of these three conditions were included. Individuals from the disease and control cohorts were propensity score matched 1:1 based on baseline demographics and clinical characteristics. A Cox proportional hazards model was used to compare the risk of type 1 diabetes between cohorts. RESULTS: Type 1 diabetes developed in 0.14% (68/47 099) of individuals with celiac disease compared to 0.06% (27/47 099) of controls. Of those with hyperthyroidism, type 1 diabetes developed in 0.17% (281/164 830) compared to 0.06% (99/164 830) of controls. Of those with hypothyroidism, type 1 diabetes developed in 0.18% (1756/980 477) compared to 0.08% (764/980 477) of controls. The risk of developing type 1 diabetes was increased for each of the disease cohorts compared to their respective controls (celiac disease: HR = 2.54 [p < 0.0001]; hyperthyroidism: adjusted HR = 2.98 [p < 0.0001]; hypothyroidism: HR = 2.41 [p < 0.0001]); risk was highest among individuals aged <18 years. CONCLUSIONS: The risk of developing type 1 diabetes was significantly higher for individuals with celiac disease or thyroid disease compared to those without any of these conditions. These findings support the screening of individuals with these conditions for stage 2 type 1 diabetes.

  PublisherOA PDFDOI

• Author response for "Risk of new‐onset type 1 diabetes in individuals with celiac disease and thyroid disease—An observational study"

  2025-04-18

  peer-review1st authorCorresponding
  PublisherDOI

• Impact of Continuous Glucose Monitoring Sourcing on Real-World Adherence and Health Care Costs: A Comparative Analysis by Insurance Type

  Clinical Diabetes · 2025-03-24

  articleOpen access

  This real-world analysis compared adherence rates, total health care costs, and health care resource utilization of individuals receiving continuous glucose monitoring (CGM) supplies through durable medical equipment (DME) providers versus through pharmacies, according to insurance type. Patients in the DME cohort had higher adherence rates than those in the pharmacy cohort. Total costs were lower for Medicare/Medicare Advantage patients getting supplies from a DME than for patients getting supplies from a pharmacy. Among those with commercial insurance, health care utilization was lower in the DME cohort than in the pharmacy cohort. Sourcing CGM supplies from DME providers versus pharmacies may yield benefits on adherence, health care costs, and resource utilization.

  PublisherOA PDFDOI

• Expert Clinical Interpretation of Continuous Glucose Monitor Reports From Individuals Without Diabetes

  Journal of Diabetes Science and Technology · 2025-02-12 · 5 citations

  articleOpen access

  BACKGROUND: Clinical interpretation of continuous glucose monitoring (CGM) data for people without diabetes has not been well established. This study aimed to investigate concordance among CGM experts in recommending clinical follow-up for individuals without diabetes, based upon their independent review of CGM data. METHODS: = 18) and asked them to evaluate 20 potentially challenging Dexcom G6 Pro CGM reports (and hemoglobin A1c [HbA1c] and fasting venous blood glucose levels) from individuals without diabetes. Clinicians reported whether they would recommend follow-up and the reasoning for their decision. We performed Fleiss Kappa interrater reliability to determine agreement among clinicians. RESULTS: More than half of expert clinicians (56-100%, but no clear consensus) recommended follow-up to individuals who spent >2% time above range (>180 mg/dL), even if HbA1c <5.7% and fasting glucose <100 mg/dL. There were no observed trends for recommending follow-up based on mean glucose or glucose management indicator. Overall, we observed poor agreement in recommendations for who should receive follow-up based on their CGM report (Fleiss Kappa = 0.36). CONCLUSIONS: High discordance among expert clinicians when interpreting potentially challenging CGM reports for people without diabetes highlights the need for more research in developing normative data for people without diabetes. Future work is required to develop CGM criteria for identifying potentially high-risk individuals who may progress to prediabetes or type 2 diabetes.

  PublisherOA PDFDOI

• &lt;b&gt;Impact of Continuous Glucose Monitoring Sourcing on Real-World Adherence and Health Care Costs: A Comparative Analysis by Insurance Type&lt;/b&gt;

  2025-03-24

  preprintOpen access

  &lt;p dir="ltr"&gt;This real-world analysis compared adherence rates, total health care costs, and health care resource utilization of individuals receiving continuous glucose monitoring (CGM) supplies through durable medical equipment (DME) providers versus through pharmacies, according to insurance type. Patients in the DME cohort had higher adherence rates than those in the pharmacy cohort. Total costs were lower for Medicare/Medicare Advantage patients getting supplies from a DME than for patients getting supplies from a pharmacy. Among those with commercial insurance, health care utilization was&lt;b&gt; &lt;/b&gt;lower in the DME cohort than in the pharmacy cohort. Sourcing CGM supplies from DME providers versus pharmacies may yield benefits on adherence, health care costs, and resource utilization.&lt;/p&gt;

  PublisherOA PDFDOI

• &lt;b&gt;Impact of Continuous Glucose Monitoring Sourcing on Real-World Adherence and Health Care Costs: A Comparative Analysis by Insurance Type&lt;/b&gt;

  2025-03-24

  preprintOpen access

  &lt;p dir="ltr"&gt;This real-world analysis compared adherence rates, total health care costs, and health care resource utilization of individuals receiving continuous glucose monitoring (CGM) supplies through durable medical equipment (DME) providers versus through pharmacies, according to insurance type. Patients in the DME cohort had higher adherence rates than those in the pharmacy cohort. Total costs were lower for Medicare/Medicare Advantage patients getting supplies from a DME than for patients getting supplies from a pharmacy. Among those with commercial insurance, health care utilization was&lt;b&gt; &lt;/b&gt;lower in the DME cohort than in the pharmacy cohort. Sourcing CGM supplies from DME providers versus pharmacies may yield benefits on adherence, health care costs, and resource utilization.&lt;/p&gt;

  PublisherDOI

• Risiko der Entwicklung von Typ-1-Diabetes bei Personen mit anderen Autoimmunerkrankungen

  Diabetologie und Stoffwechsel · 2025-05-01

  article1st authorCorresponding
  PublisherDOI

Recent grants

• NIH Grant F32DK008271

  NIH · $24k

Frequent coauthors

• Ginger Brechtel

  Indiana University – Purdue University Indianapolis

  64 shared

• Markku Laakso

  Kuopio University Hospital

  59 shared

• Alain Baron

  47 shared

• William H. Polonsky

  University of California, San Diego

  44 shared

• Robert R. Henry

  Medical University of South Carolina

  36 shared

• Elizabeth M. Venditti

  University of Pittsburgh

  30 shared

• Andrea M. Kriska

  29 shared

• William C. Knowler

  28 shared

Education

• M.D.

  University of California, San Diego

• B.S.

  University of California, San Diego