About

David Maahs is the Lucile Salter Packard Professor of Pediatrics and also holds a courtesy appointment as a Professor of Epidemiology and Population Health at Stanford University. He is affiliated with the Center for Artificial Intelligence in Medicine & Imaging (AIMI) at Stanford. His research focuses on the application of artificial intelligence and imaging techniques in medicine, particularly within pediatric healthcare. As a leading figure in his field, he contributes to advancing medical research and education through his role at Stanford and his involvement in initiatives aimed at integrating AI into healthcare practices.

Research topics

• Medicine
• Internal medicine
• Endocrinology
• Intensive care medicine
• Demography
• Pediatrics
• Risk analysis (engineering)
• Gerontology
• Virology
• Urology
• Gastroenterology
• Family medicine
• Environmental health

Selected publications

• 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

• Research Code Sharing in Support of Gold Standard Science.

  UNC Libraries · 2026-03-17

  articleOpen access

  Sharing research code in an open access version-controlled repository offers significant benefits for both science as a whole and for individual researchers. In this article, we focus on this practice, which is fully aligned with the NIH's Gold Standard Science (GSS) program as well as FAIR (findable, accessible, interoperable, reusable) and TRUST (transparency, responsibility, user focus, sustainability, technology) principles. Gold Standard Science supports open science by emphasizing transparency, reproducibility, and the use of best practices that enable others to verify and extend research. Pairing a research article's cited data snapshot with a versioned, environment-specific code release, deposited in a companion code repository, ensures that, upon submission to a medical journal, readers and reviewers can directly verify results. An executable and updatable companion code repository complements, rather than replaces, established research data repositories. When code underlying medical research results is made openly available, then other scientists can inspect, run, and validate analyses. These activities enhance reproducibility, which is a core aim of GSS. Shared code also facilitates collaborative innovation by allowing researchers to extend the utility of the code to new datasets and applications. For researchers, code sharing can increase visibility, credibility, and citation impact. Demonstrating transparency through shared executable and updatable code builds trust with journal readers, peer reviewers, funders, and peers. Shared code in an open access repository signals adherence to high standards of scientific integrity and attracts opportunities for collaboration. A researcher who shares code receives recognition as a leader in reproducible, trustworthy research consistent with NIH's GSS principles.

  PublisherDOI

• Building the evidence to address disparities in type 1 diabetes (BEAD-T1D): methods and design of a study examining barriers and promoters to diabetes device use in families with public insurance

  Frontiers in Endocrinology · 2026-04-27

  articleOpen access

  Continuous glucose monitoring (CGM) and automated insulin delivery (AID) systems have led to improved outcomes in type 1 diabetes (T1D). Diabetes technology use in minoritized populations is 50% lower than more privileged groups. Tailored, multi-factorial interventions are needed to address disparities and improve technology uptake in minoritized youth with T1D. The Building the Evidence to Address Disparities in Type 1 Diabetes (BEAD-T1D) Study assesses drivers of disparities in CGM and AID use in youth with T1D and public insurance to develop an intervention to increase uptake of diabetes technology. This manuscript describes the rationale, design, and protocols of the study. BEAD-T1D is a prospective, mixed-methods study grounded in the social-ecological model informed by sequential triangulation. Study Aim 1 constructs an evidence base of barriers and promoters to CGM and AID use in youth with T1D and public insurance to formulate and test a pilot intervention to increase device uptake in minoritized populations. Study Aim 2 constructs an evidence base of barriers and promoters to recommending devices to youth with T1D and public insurance to formulate and test a pilot intervention for healthcare providers to increase recommendations of devices. The primary outcome is diabetes technology acceptance analyzed via descriptive statistics and univariate analyses to inform the systematic building of a multivariable model. BEAD-T1D lays the groundwork for future efforts to reduce disparities in the uptake and continued use of diabetes technology in marginalized populations. Interventions effective in increasing the uptake and continued use of diabetes technology in youth with T1D and public insurance are necessary to mitigate disparities.

  PublisherOA PDFDOI

• Cost-effectiveness of continuous glucose monitoring with remote patient monitoring in pediatric patients with newly diagnosed type 1 diabetes in the United States

  2026-03-25

  article

  <p dir="ltr"><b>Objective: </b>The use of continuous glucose monitoring (CGM) with remote patient monitoring (RPM) continues to grow. We evaluated the cost-effectiveness of CGM with RPM compared to self-monitoring of blood glucose (SMBG) and CGM alone.</p><p dir="ltr"><b>Research design and methods: </b>We simulated type 1 diabetes progression with a Markov model in 5-year-old patients over a 20-year, 50-year, and age 100 horizon. We tracked diabetic ketoacidosis (DKA), severe hypoglycemia (SH), and seven chronic complications: retinopathy, neuropathy, nephropathy, cardiovascular disease, end-stage renal disease, lower-extremity amputation, and blindness. We compared three interventions: SMBG, CGM, and CGM with RPM. Efficacy estimates were derived from meta-analyses of pediatric CGM studies and the results of the Teamwork, Targets, Technology, and Tight Glycemia Study (4T Study 1). We evaluated quality-adjusted life years (QALYs) and healthcare costs (2022 U.S. dollars) discounted at 3% annually. We performed extensive sensitivity analyses.</p><p dir="ltr"><b>Results: </b>Compared to SMBG, CGM increased QALYs by 0.09 and costs by $8,900 over 20 years; CGM with RPM increased QALYs by 0.37 and costs by $10,300 CGM with RPM yielded more QALYs at a lower incremental cost-effectiveness ratio compared to CGM ($27,400/QALY vs $103,700/QALY, respectively). Results were robust across sensitivity analyses and time horizons. CGM with RPM remained cost-effective when achieving at least 30% of 4T’s clinical efficacy.</p><p dir="ltr"><b>Conclusions: </b>CGM with RPM delivers superior health outcomes compared to SMBG and CGM and is likely cost-effective for patients with newly diagnosed type 1 diabetes. Despite higher intervention costs, CGM with RPM can reduce complications costs and generate net healthcare savings.</p>

  PublisherDOI

• Diabetes Technology and Therapy in the Pediatric Age Group

  Diabetes Technology & Therapeutics · 2026-03-01

  article1st authorCorresponding
  PublisherDOI

• Cost-Effectiveness of Continuous Glucose Monitoring With Remote Patient Monitoring in Pediatric Patients With Newly Diagnosed Type 1 Diabetes in the U.S.

  Diabetes Care · 2026-03-25

  articleOpen access

  OBJECTIVE: The use of continuous glucose monitoring (CGM) with remote patient monitoring (RPM) continues to grow. We evaluated the cost-effectiveness of CGM with RPM compared with self-monitoring of blood glucose (SMBG) and CGM alone. RESEARCH DESIGN AND METHODS: We simulated type 1 diabetes progression with a Markov model in 5-year-old patients over a 20-year, 50-year, and lifetime horizon. We tracked diabetic ketoacidosis (DKA), severe hypoglycemia (SH), and seven chronic complications: retinopathy, neuropathy, nephropathy, cardiovascular disease, end-stage renal disease, lower-extremity amputation, and blindness. We compared three interventions: SMBG, CGM, and CGM with RPM. Efficacy estimates were derived from meta-analyses of pediatric CGM studies and the results of the Teamwork, Targets, Technology, and Tight Glycemia Study (4T Study 1). We evaluated quality-adjusted life years (QALYs) and health care costs (2022 U.S. dollars) discounted at 3% annually. We performed extensive sensitivity analyses. RESULTS: Compared with SMBG, CGM increased QALYs by 0.09 and costs by $8,900 over 20 years; CGM with RPM increased QALYs by 0.37, and costs by $10,300. CGM with RPM yielded more QALYs at a lower incremental cost-effectiveness ratio compared with CGM ($27,400/QALY vs. $103,700/QALY, respectively). Results were robust across sensitivity analyses and time horizons. CGM with RPM remained cost-effective when achieving at least 30% of 4T's clinical efficacy. CONCLUSIONS: CGM with RPM delivers superior health outcomes compared with SMBG and CGM and is likely cost-effective for patients with newly diagnosed type 1 diabetes. Despite higher intervention costs, CGM with RPM can reduce complications costs and generate net health care savings.

  PublisherOA PDFDOI

• Diabetes technology: an update

  The Journal of Clinical Endocrinology & Metabolism · 2026-04-13

  articleSenior author

  Diabetes is one of the most prevalent chronic diseases worldwide, with rates that continue to increase. Over 30 years ago, the Diabetes Control and Complications Trial demonstrated that intensive glucose management decreased long term vascular complications. Unfortunately, many people with diabetes still struggle to meet glycemic goals. In this mini-review, we highlight advances in diabetes technology that are associated with improvements in glycemic management. Continuous glucose monitoring (CGM) and automated insulin delivery systems are associated with significant improvements in HbA1c, time-in-range (70-180 mg/dL), and decreases in severe hypoglycemia and diabetic ketoacidosis in people with both type 1 and type 2 diabetes. Recent data shows that these technologies improve outcomes early in the course of type 1 diabetes. CGM is also being explored as a tool to monitor progression through early-stage type 1 diabetes (2 antibodies positive) to identify individuals who may benefit from disease-modifying therapies as well as to prevent the onset of diabetic ketoacidosis at onset of stage 3 (insulin requiring) type 1 diabetes. Adjunctive pharmacologic therapies and artificial intelligence may further expand and improve therapies, offering potential synergistic benefits. However, there continue to be significant disparities in access to diabetes technologies and access to insulin worldwide. This mini-review summarizes recently published data, highlights emerging applications, and underscores the need to pair technological innovation with strategies that promote equitable access and support for diabetes care to improve outcomes for all people with diabetes.

  PublisherDOI

• Cost-effectiveness of continuous glucose monitoring with remote patient monitoring in pediatric patients with newly diagnosed type 1 diabetes in the United States

  2026-03-25

  article

  <p dir="ltr"><b>Objective: </b>The use of continuous glucose monitoring (CGM) with remote patient monitoring (RPM) continues to grow. We evaluated the cost-effectiveness of CGM with RPM compared to self-monitoring of blood glucose (SMBG) and CGM alone.</p><p dir="ltr"><b>Research design and methods: </b>We simulated type 1 diabetes progression with a Markov model in 5-year-old patients over a 20-year, 50-year, and age 100 horizon. We tracked diabetic ketoacidosis (DKA), severe hypoglycemia (SH), and seven chronic complications: retinopathy, neuropathy, nephropathy, cardiovascular disease, end-stage renal disease, lower-extremity amputation, and blindness. We compared three interventions: SMBG, CGM, and CGM with RPM. Efficacy estimates were derived from meta-analyses of pediatric CGM studies and the results of the Teamwork, Targets, Technology, and Tight Glycemia Study (4T Study 1). We evaluated quality-adjusted life years (QALYs) and healthcare costs (2022 U.S. dollars) discounted at 3% annually. We performed extensive sensitivity analyses.</p><p dir="ltr"><b>Results: </b>Compared to SMBG, CGM increased QALYs by 0.09 and costs by $8,900 over 20 years; CGM with RPM increased QALYs by 0.37 and costs by $10,300 CGM with RPM yielded more QALYs at a lower incremental cost-effectiveness ratio compared to CGM ($27,400/QALY vs $103,700/QALY, respectively). Results were robust across sensitivity analyses and time horizons. CGM with RPM remained cost-effective when achieving at least 30% of 4T’s clinical efficacy.</p><p dir="ltr"><b>Conclusions: </b>CGM with RPM delivers superior health outcomes compared to SMBG and CGM and is likely cost-effective for patients with newly diagnosed type 1 diabetes. Despite higher intervention costs, CGM with RPM can reduce complications costs and generate net healthcare savings.</p>

  PublisherDOI

• Micro-randomization trial design under operational constraints

  Contemporary Clinical Trials · 2026-05-01

  article
  PublisherDOI

• A High Protein Diet Is Associated with Improved Glycemic Control Following Exercise among Adolescents with Type 1 Diabetes

  UNC Libraries · 2025-09-27

  articleOpen access

  Nutritional strategies are needed to aid people with type 1 diabetes (T1D) in managing glycemia following exercise. Secondary analyses were conducted from a randomized trial of an adaptive behavioral intervention to assess the relationship between post-exercise and daily protein (g/kg) intake on glycemia following moderate-to-vigorous physical activity (MVPA) among adolescents with T1D. Adolescents (<em>n</em> = 112) with T1D, 14.5 (13.8, 15.7) years of age, and 36.6% overweight or obese, provided measures of glycemia using continuous glucose monitoring (percent time above range [TAR, &gt;180 mg/dL], time-in-range [TIR, 70-180 mg/dL], time-below-range [TBR, &lt;70 mg/dL]), self-reported physical activity (previous day physical activity recalls), and 24 h dietary recall data at baseline and 6 months post-intervention. Mixed effects regression models adjusted for design (randomization assignment, study site), demographic, clinical, anthropometric, dietary, physical activity, and timing covariates estimated the association between post-exercise and daily protein intake on TAR, TIR, and TBR from the cessation of MVPA bouts until the following morning. Daily protein intakes of &ge;1.2 g/kg/day were associated with 6.9% (<em>p</em> = 0.03) greater TIR and -8.0% (<em>p</em> = 0.02) less TAR following exercise, however, no association was observed between post-exercise protein intake and post-exercise glycemia. Following current sports nutrition guidelines for daily protein intake may promote improved glycemia following exercise among adolescents with T1D.

  PublisherDOI

Recent grants

• NIH Grant DP3DK11335801

  NIH · $1.9M · 2022

• NIH Grant R01DK102188

  NIH · $1.0M · 2018

• Training Research Leaders in Type 1 Diabetes

  NIH · $2.1M · 2019–2026

• Diabetes, Endocrinology and Metabolism Training Grant

  NIH · $8.9M · 1976–2028

• NIH Grant K23DK075360

  NIH · $663k · 2013

Frequent coauthors

• Sarah J. Hanes

  Stanford University

  204 shared

• Robert Slover

  175 shared

• Stéphanie Woerner

  174 shared

• Melinda Zgorski

  174 shared

• Cari Berget

  172 shared

• Robert Janicek

  171 shared

• Samantha Lange

  171 shared

• Deanna Gabrielson

  171 shared