Reviewing U.S. connected diabetes care: the newest member of the team
Open accessAbstract
Recent years have brought about an explosion in the number of companies offering connected diabetes care products, defined as digital diabetes management systems based around (1) smartphone apps, (2) devices with built-in connectivity, and (3) remote human and automated coaching and support. These nascent models aim to provide more continuous and on-demand care, aligning with the 24/7 demands of chronic disease. It has been enabled by multiple factors, including the rising use of connected devices and apps to help people manage their chronic conditions, growing appreciation for the importance of outcomes beyond A1c, and the lofty and growing cost of health care. Despite the potential of these programs to improve the outcomes and well-being of people with diabetes and reduce the burdens on health care providers and systems, awareness and use of these programs and approaches remain low in the medical community. In this article, we present a snapshot of this dynamic field, including a taxonomy of various connected diabetes care products available to employers, health plans, health systems, and people with diabetes in the United States, and we identify meaningful distinctions among them: (1) health conditions managed, (2) peer support interactions, (3) prescribing providers on the care team, (4) provision of connected medical devices and/or continuous glucose monitors, (5) degree of treatment personalization, and (6) clinical and real-world evidence. We also discuss broad trends in connected diabetes care. Given the urgency and scale of the diabetes epidemic, it is vital that a range of medical and clinical communities find meaningful ways to scale individualized, timely care under reimbursement models that better align incentives for various stakeholders, particularly health care providers themselves. This would not only address deficiencies in care but could also make diabetes care more attractive to future clinicians.
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Other online programs assist in improving diabetes outcomes by remotely monitoring clinical data and providing feedback and coaching.
“Others assist in improving diabetes outcomes by remotely monitoring clinical data (for instance, wireless monitoring of glucose levels, weight, or blood pressure) and providing feedback and coaching (266-271).”
From 7. Diabetes Technology: Standards of Care in Diabetes—2025 (2025) · cites this paper as [271]
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Cites
Economic Costs of Diabetes in the U.S. in 2017
American Diabetes Association (2018) · Diabetes Care · doi:10.2337/dci18-0007 · Cited by 2,528 · see citing works
Epidemiology of depression and diabetes: a systematic review
Roy, T., & Lloyd, C. E. (2012) · Journal of Affective Disorders · doi:10.1016/s0165-0327(12)70004-6 · Cited by 1,229 · see citing works
Depression and Diabetes Treatment Nonadherence: A Meta-Analysis
Gonzalez, J. S., Peyrot, M., McCarl, L. A., Collins, E. M., Serpa, L., Mimiaga, M. J., & Safren, S. A. (2008) · Diabetes Care · doi:10.2337/dc08-1341 · Cited by 1,060 · see citing works
Quinn, C. C., Shardell, M. D., Terrin, M. L., Barr, E. A., Ballew, S. H., & Gruber-Baldini, A. L. (2011) · Diabetes Care · doi:10.2337/dc11-0366 · Cited by 650 · see citing works
The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading
Beck, R. W., Connor, C. G., Mullen, D. M., Wesley, D. M., & Bergenstal, R. M. (2017) · Diabetes Care · doi:10.2337/dc17-0636 · Cited by 477 · see citing works
Quinn, C. C., Clough, S. S., Minor, J. M., Lender, D., Okafor, M. C., & Gruber-Baldini, A. (2008) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0283 · Cited by 406 · see citing works
Projection of the future diabetes burden in the United States through 2060
Lin, J., Thompson, T. J., Cheng, Y. J., Zhuo, X., Zhang, P., Gregg, E. W., & Rolka, D. B. (2018) · Population Health Metrics · doi:10.1186/s12963-018-0166-4 · Cited by 335 · see citing works
Athinarayanan, S. J., Adams, R. N., Hallberg, S. J., McKenzie, A. L., Bhanpuri, N. H., Campbell, W. W., Volek, J. S., Phinney, S. D., & McCarter, J. P. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00348 · Cited by 324 · see citing works
Vigersky, R. A., Fonda, S. J., Chellappa, M., Walker, M. S., & Ehrhardt, N. M. (2011) · Diabetes Care · doi:10.2337/dc11-1438 · Cited by 304 · see citing works
Rabi, D. M., Edwards, A. L., Southern, D. A., Svenson, L. W., Sargious, P. M., Norton, P., Larsen, E. T., & Ghali, W. A. (2006) · BMC Health Services Research · doi:10.1186/1472-6963-6-124 · Cited by 262 · see citing works
Evaluation of the Cascade of Diabetes Care in the United States, 2005-2016
Kazemian, P., Shebl, F. M., McCann, N., Walensky, R. P., & Wexler, D. J. (2019) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2019.2396 · Cited by 252 · see citing works
The Clinical Endocrinology Workforce: Current Status and Future Projections of Supply and Demand
Vigersky, R. A., Fish, L., Hogan, P., Stewart, A., Kutler, S., Ladenson, P. W., McDermott, M., & Hupart, K. H. (2014) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2014-2257 · Cited by 238 · see citing works
Stein, N., & Brooks, K. (2017) · JMIR Diabetes · doi:10.2196/diabetes.8590 · Cited by 191 · see citing works
Chin, S. O., Keum, C., Woo, J., Park, J., Choi, H. J., Woo, J., & Rhee, S. Y. (2016) · Scientific Reports · doi:10.1038/srep34563 · Cited by 138 · see citing works
Engagement and outcomes in a digital Diabetes Prevention Program: 3-year update
Sepah, S. C., Jiang, L., Ellis, R. J., McDermott, K., & Peters, A. L. (2017) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2017-000422 · Cited by 122 · see citing works
Peer Support Interventions for Adults With Diabetes: A Meta-Analysis of Hemoglobin A1c Outcomes
Patil, S. J., Ruppar, T. M., Koopman, R. J., Lindbloom, E. J., Elliott, S. G., Mehr, D. R., & Conn, V. S. (2016) · The Annals of Family Medicine · doi:10.1370/afm.1982 · Cited by 86 · see citing works
Bollyky, J. B., Bravata, D., Yang, J., Williamson, M., & Schneider, J. (2018) · Journal of Diabetes Research · doi:10.1155/2018/3961730 · Cited by 85 · see citing works
Mao, A. Y., Chen, C., Magana, C., Caballero Barajas, K., & Olayiwola, J. N. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.7591 · Cited by 77 · see citing works
Kumar, S., Moseson, H., Uppal, J., & Juusola, J. L. (2018) · The Diabetes Educator · doi:10.1177/0145721718765650 · Cited by 68 · see citing works
Whaley, C. M., Bollyky, J. B., Lu, W., Painter, S., Schneider, J., Zhao, Z., He, X., Johnson, J., & Meadows, E. S. (2019) · Journal of Medical Economics · doi:10.1080/13696998.2019.1609483 · Cited by 49 · cited 1× · see citing works
“A recent Livongo article suggested that only 28% of members check their blood glucose on at least 24 days in the month, whereas 20% check < 3 days per month 32 ; this testing rate is presumably in line with that in other programs.”
Turner, R. M., Ma, Q., Lorig, K., Greenberg, J., & DeVries, A. R. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9225 · Cited by 39 · see citing works
American Diabetes Association 78th Scientific Sessions
Kurian, M. J., Carracher, A. M., & Close, K. L. (2018) · Journal of Diabetes · doi:10.1111/1753-0407.12830 · Cited by 9 · see citing works
Self-citationSociety of Behavioral Medicine 2019 Annual Meeting Abstracts
Karekla, M., Vasiliou, V. S., Constantinidou, F., et al. (2019) · Annals of Behavioral Medicine · doi:10.1093/abm/kaz007 · Cited by 5 · see citing works
Shomali, M. E., Iyer, A. K., Griffin, B. T., et al. (2018) · Diabetes · doi:10.2337/db18-1317-p · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- Dixon RF, Miller DP, Evans KL, et al.: Real-world Gly- cemic Control Data from the Initial Launch of the Onduo Virtual Diabetes Clinic. American Diabetes Association Symposium on the Use of Real-World Data to Improve the Prevention and Care of Diabetes-Related Outcomes, Wa- shington, D.C, 2018.
- Osborn CY, Hirsch A, Heyman M, et al.: One drop im- proves A1c among people with type 2 diabetes. Ann Behav Med 2019;53:S1-S842.
- Uchida T, Takahashi H, Ban M, et al.: A Robot Counseling System-What Kinds of Topics Do we Prefer to Disclose to Robots? 26th IEEE International Symposium on Robot and Human Interactive Communication. Lisbon: IEEE, 2017. Address correspondence to:
Cited by
Sorted by citations
7. Diabetes Technology: Standards of Care in Diabetes—2025
American Diabetes Association Professional Practice Committee, ElSayed, N. A., McCoy, R. G., Aleppo, G., Balapattabi, K., Beverly, E. A., Briggs Early, K., Bruemmer, D., Echouffo-Tcheugui, J. B., Ekhlaspour, L., et al. (2025) · Diabetes Care · doi:10.2337/dc25-s007 · Cited by 348 · see citing works
7. Diabetes Technology: <i>Standards of Care in Diabetes</i> — <i>2023</i>
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s007 · Cited by 301 · see citing works
Self-citation7. Diabetes Technology: <i>Standards of Care in Diabetes—2024</i>
American Diabetes Association Professional Practice Committee, ElSayed, N. A., Aleppo, G., Bannuru, R. R., Bruemmer, D., Collins, B. S., Ekhlaspour, L., Hilliard, M. E., Johnson, E. L., Khunti, K., et al. (2024) · Diabetes Care · doi:10.2337/dc24-s007 · Cited by 281 · see citing works
Self-citation7. Diabetes Technology: <i>Standards of Medical Care in Diabetes—2022</i>
American Diabetes Association Professional Practice Committee (2022) · Diabetes Care · doi:10.2337/dc22-s007 · Cited by 358 · see citing works
7. Diabetes Technology: <i>Standards of Medical Care in Diabetes—2021</i>
American Diabetes Association (2021) · Diabetes Care · doi:10.2337/dc21-s007 · Cited by 202 · see citing works
Wright, E. E., Kerr, M. S. D., Reyes, I. J., Nabutovsky, Y., & Miller, E. (2021) · Diabetes Spectrum · doi:10.2337/ds20-0069 · Cited by 115 · see citing works
Missed and Mistimed Insulin Doses in People with Diabetes: A Systematic Literature Review
Robinson, S., Newson, R. S., Liao, B., Kennedy-Martin, T., & Battelino, T. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0164 · Cited by 73 · see citing works
Weight loss in a digital app-based diabetes prevention program powered by artificial intelligence.
Graham, S. A., Pitter, V., Hori, J. H., Stein, N., & Branch, O. H. (2022) · DIGITAL HEALTH · doi:10.1177/20552076221130619 · Cited by 43 · see citing works
Greenwood, D. A., Litchman, M. L., Isaacs, D., Blanchette, J. E., Dickinson, J. K., Hughes, A., Colicchio, V. D., Ye, J., Yehl, K., Todd, A., et al. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211036430 · Cited by 31 · see citing works
Kumbara, A. B., Iyer, A. K., Green, C. R., Jepson, L. H., Leone, K., Layne, J. E., & Shomali, M. (2023) · JMIR Diabetes · doi:10.2196/47638 · Cited by 29 · see citing works
Complementarity of Digital Health and Peer Support: “This Is What’s Coming”
Tang, P. Y., Duni, J., Peeples, M. M., Kowitt, S. D., Bhushan, N. L., Sokol, R. L., & Fisher, E. B. (2021) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2021.646963 · Cited by 11 · see citing works
The critical elements of digital health in diabetes and cardiometabolic care
Shomali, M., Mora, P., Aleppo, G., Peeples, M., Kumbara, A., MacLeod, J., & Iyer, A. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1469471 · Cited by 10 · see citing works
Zakaria, H., Alshehhi, S., Caccelli, M., Ozkan, C., Kattan, J., Jafaar, Z., Laborte, R., Aleabova, S., Almarzooqi, N., Hashemi, A., et al. (2024) · Metabolism Open · doi:10.1016/j.metop.2024.100283 · Cited by 11 · see citing works
- Authors
- Levine, B. J., Close, K. L., & Gabbay, R. A.
- Affiliations
- Close Concerns (United States) (US)
- Joslin Diabetes Center (US)
- Corresponding author
- Gabbay, Robert A.
- Venue
- Diabetes Technology & Therapeutics
- Publisher
- SAGE Publications
- Published
- 2020-01
- Volume
- 22
- Issue
- 1
- Pages
- 1-9
- ISSN
- 1520-9156 (ISSN-L)
- 1557-8593
- OpenAlex
- W2971669292
- Cited by
- 66
- References
- 24
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 9 · 2023: 9 · 2022: 10 · 2021: 16 · 2020: 13
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Technology & Therapeutics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- digital health, mobile application, continuous glucose monitoring, peer support, remote coaching, chronic disease management, health care reimbursement, personalized treatment, employer health programs, health plans, health care system
- MeSH terms
- Wearable Electronic Devices, Blood Glucose, Diabetes Mellitus, Humans, Monitoring, Ambulatory, Disease Management, Mobile Applications
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