The foundation of our clinical rigor
Proven science drives everything we do. Through rigorous research, we demonstrate how our health technology delivers real results: better patient outcomes, greater value for healthcare systems, and more advanced AI capabilities. Key areas include:
Our AI transforms complex health data into personalized insights and guidance when individuals need it most.
We convert continuous glucose data into personalized guidance that elevates traditional diabetes care standards.
We address interconnected health conditions, turning digital engagement into measurable clinical improvements.
We offer FDA-cleared solutions for T1 and T2 diabetes that simplify treatment while addressing daily health challenges.
The Impact of a Mobile Diabetes Health Intervention on Diabetes Distress and Depression Among Adults: Secondary Analysis of a Cluster Randomized Controlled Trial
Charlene C Quinn, Krystal K Swasey, J Christopher F Crabbe, Michelle D Shardell, Michael L Terrin, Erik A Barr, Ann L Gruber-Baldini
Technology-Enabled Diabetes Self-Management Education & Support
Malinda Peeples, MS, RN, CDE, FAADE, Deborah Greenwood, PhD, RN, BC-ADM, CDE, FAADE, Perry M Gee, PhD, RN
Measures derived from patient-generated health data provide insights on glycemic control beyond A1C for people with type 2 diabetes
The proposed metrics provide insight to user blood glucose (BG) data that go beyond measures of average. Digital health tools are capable of calculating these metrics and making them available for provider clinical decision support.
Mansur Shomali, MD, CM
A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support
Since the introduction of web-enabled mobile devices, technology has been increasingly used to enable diabetes self-management education and support. This timely systematic review summarizes how currently available technology-enabled diabetes self-management solutions impact outcomes for people living with diabetes.
Deborah A. Greenwood, PhD, RN, BC-ADM, CDE, FAADE, Perry M. Gee, PhD, RN, Kathy J. Fatkin, PhD, AHIP, RN, and Malinda Peeples, MS, RN, CDE
Are You Ready to Be an eEducator?
Health technology tools are redesigning clinical care and diabetes self-management education. In the article entitled, "Are You Ready to Be an eEducator?," the co-authors focus on the need for diabetes educators to move towards the implementation of digital health as a key delivery platform for diabetes education and care.
Janice MacLeod, MA, RDE, CDE and Malinda M. Peeples, MS, RN, CDE
Population Health Diabetes Education: The Role of Digital Health & Patient Generated Health Data
Digital health tools have recently made available a tremendous amount of patient-generated health data (PGHD). If summarized and presented properly, these data may facilitate population health management. Diabetes educators care coordinators, and health coaches may be able to deploy targeted, protocol-driven interventions to the patients who need them. As shown here, PGHD may also enhance clinical decision-making for the provider at the time of or in between patient visits. Given the prevalence and complexity of diabetes and the limited time providers have with patients, digital health tools and PGHD will be critical in improving care, supporting practice efficiency, and impacting the cost burden.
Malinda Peeples, Janice Macleod, Shelley Taylor, Mansur Shomali
Case Study: The IoT and Big Data in Healthcare Unleashing the Next Generation of Value Creation
Book chapter
Anand Iyer, PhD
eHealth-Assisted Lay Health Coaching for Diabetes Self-Management Support
Gillings Innovation Laboratory award at the UNC Gillings School of Global Public Health, tested the feasibility and reach of integrating a telephone-based lay health coach with an eHealth intervention for diabetes self-management support in a Patient-Centered Medical Home practice in New Jersey.
Patrick Y. Tang, MPH; Malinda Peeples, RN, MS, CDE; Janet Duni, BSN, RN, MPA, CCM; Steven Peskin, MD, MBA, FACP; Janice Macleod, MA, RDN, LDN, CDE; Satah Kowitt, MPH; Edwin B. Fisher, PhD
Combining the High Tech with the Soft Touch: Population Health Management Using eHealth and Peer Support
Kowitt ang, Peeples, Duni, Peskin, Fisher
Evidence-Based mHealth Chronic Disease Mobile App Intervention Design: Development of a Framework
Calvin C Wilhide III, PhD; Malinda M Peeples, RN, MS, CDE; Robin C Anthony Kouyaté, PhD
Transform Your DSME/S Program: Leverage the Value of Mobile Health
Malinda Peeples, Robert Melfi, Diana O’Keefe, Janice MacLeod
Educators: Go Mobile & Join the Digital Revolution!
Janice MacLeod, Lauren Bronich-Hall, Michelle Livingston, Malinda Peeples
Mobile Prescription Therapy: The Potential for Patient Engagement to Enhance Outcomes
Malinda Peeples, Anand K. Iyer
Enhancing Diabetes and Hypertension Self-Management: A Randomized Trial of a Mobile Phone Strategy
Richard J Katz MD, Samir Patel MD, Joshua L Cohen M.D., Karen Barr NP, Heather Young PhD
Older Adult Self-Efficacy Study of Mobile Phone Diabetes Management
The purpose of this study was to evaluate participant self-efficacy and use of a mobile phone diabetes health intervention for older adults during a 4-week period. Participants included seven adults (mean age, 70.3 years) with type 2 diabetes cared for by community-based primary care physicians. Participants entered blood glucose data into a mobile phone and personalized patient Internet Web portal. Based on blood glucose values, participants received automatic messages and educational information to self-manage their diabetes. Study measures included prior mobile phone/Internet use, the Stanford Self-Efficacy for Diabetes Scale, the Stanford Energy/Fatigue Scale, the Short Form-36, the Patient Health Questionnaire-9 (depression), the Patient Reported Diabetes Symptom Scale, the Diabetes Stages of Change measure, and a summary of mobile system use. Participants had high self-efficacy and high readiness and confidence in their ability to monitor changes to control their diabetes. Participants demonstrated ability to use the mobile intervention and communicate with diabetes educators.
Charlene C Quinn, Bilal Khokhar, Kelly Weed, Erik Barr, Ann L Gruber-Baldini
A Data Science Framework for Mobile Health–Engagement and Outcomes
Mansur Shomali MD, CM; Malinda Peeples, MS, RN, CDE; Joseph Isenberg, MS; Anand Iyer, PhD
Hypoglycemia prediction using machine learning models for patients with type 2 diabetes
Our machine learning models can predict hypoglycemia events with a high degree of sensitivity and specificity. These models-which have been validated retrospectively and if implemented in real time-could be useful tools for reducing hypoglycemia in vulnerable patients.
Bharath Sudharsan, Malinda Peeples, Mansur Shomali
Mobile Diabetes Intervention for Glycemic Control in 45- to 64-Year-Old Persons With Type 2 Diabetes
The purpose of this study was to assess effects of a mobile coaching system on glycated hemoglobin (HbA1c) levels in younger versus older patients over 1 year. Participants (n = 118) included adult patients with Type 2 diabetes cared for by community physicians. Intervention patients received mobile phone coaching and individualized web portal. Control patients received usual care. Patients were stratified into two age groups: younger (<55 years) and older (≥ 55 years). The intervention resulted in greater 12-month declines in HbA1c, compared with usual care, for patients in both age groups (p < .0001). Among older patients, HbA1c changed by -1.8% (95% confidence interval [CI] = [-2.4, -1.1]) in the intervention group and -0.3% (95% CI = [-0.9, +0.3]) in the control group. Among younger patients, HbA1c changed by -2.0% (95% CI = [-2.5, -1.5]) in the intervention group and -1.0% (95% CI = [-1.6, -0.4]) in the control group. The mobile health intervention was as effective at managing Type 2 diabetes in older adults as younger persons.
Charlene C Quinn, Michelle D Shardell, Michael L Terrin, Erik A Barr 2, DoHwan Park, Faraz Shaikh, Jack M Guralnik, Ann L Gruber-Baldini
Mobile Messaging: It’s More Than Texting. A Mobile Message Taxonomy that Utilizes the Capacity of Mobile Technology
Robin C. Anthony Kouyaté, PhD, Malinda Peeples, RN, MS, CDE, Calvin C. Wilhide, PhD
Mobile Diabetes Intervention for Glycemic Control: Impact on Physician Prescribing
Our results suggest mobile diabetes interventions can encourage physicians to modify and intensify antihyperglycemic medications in patients with type 2 diabetes. Differences in physician prescribing behavior were modest, and do not appear to be large enough to explain a 1.2% decrease in HbA1c.
Charlene C Quinn, Patricia L Sareh, Michelle L Shardell, Michael L Terrin, Erik A Barr, Ann L Gruber-Baldini
Type 2 Diabetes Hypoglycemia Prediction: Using SMBG Data & Probabilistic Methods
Bharath Sudharsan, MS; Malinda Peeples, RN, MS, CDE; Mansur Shomali, MD, CM
Integration of a mobile-integrated therapy with electronic health records: lessons learned.
Malinda M Peeples, Anand K Iyer, Joshua L Cohen
Lessons From a Community-Based mHealth Diabetes Self-Management Program: “It’s Not Just About the Cell Phone”
Richard Katz, Tsega Mesfin, Karen Barr
Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control
The combination of behavioral mobile coaching with blood glucose data, lifestyle behaviors, and patient self-management data individually analyzed and presented with evidence-based guidelines to providers substantially reduced glycated hemoglobin levels over 1 year. The mean declines in glycated hemoglobin were 1.9% in the maximal treatment group and 0.7% in the usual care group, a difference of 1.2% (P = 0.001) [corrected] over 12 months. Appreciable differences were not observed between groups for patient-reported diabetes distress, depression, diabetes symptoms, or blood pressure and lipid levels (all P > 0.05).
Charlene C Quinn, Michelle D Shardell, Michael L Terrin, Erik A Barr, Shoshana H Ballew, Ann L Gruber-Baldini
Connecting Patients and Diabetes Educators via a Mobile Phone and Web-based Technology System: Content Analysis of Portal Messages
H Cole-Lewis, S Clough, L Bronich-Hall, M Peeples
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