Emerging digital health approaches for the detection of undiagnosed type 2 diabetes mellitus in underserved populations: A scoping review
,
Abstract
Background & Aim: Undiagnosed type 2 diabetes mellitus continues to pose a major global health challenge, especially in underserved populations facing limited access to screening. Digital health technologies present scalable alternatives to improve early detection and prevent complications. This scoping review aims to map digital health approaches for detecting undiagnosed type 2 diabetes mellitus in underserved adult communities and analyze screening outcomes, feasibility, and key implementation factors.
Materials & Methods: The review followed the Arksey and O’Malley scoping framework and was reported using PRISMA-ScR guidelines. Systematic searches were performed in PubMed/MEDLINE, Scopus, Web of Science, and CINAHL for studies published in English from 2015 onward. Two reviewers independently screened articles, with conflicts resolved through consensus. Data were synthesized narratively to identify digital modalities, screening strategies, effectiveness indicators, and enablers or barriers.
Results: Nineteen studies were included, identifying five categories of digital interventions. Electronic health record–driven screening was reported in 5 of 19 studiesand was the most frequently reported modality, alongside mHealth applications, SMS-based detection support, telehealth platforms, and wearable tools. Digital risk-based screening integrated within community or primary care pathways demonstrated the widest reach and highest identification of undiagnosed dysglycemia. Simpler digital solutions showed greater acceptability and feasibility than complex systems, particularly in settings with limited digital literacy or connectivity.
Conclusion: Digital health technologies show strong potential to expand early detection of undiagnosed type 2 diabetes mellitus in underserved populations. System-integrated, low-burden, and equity-centered screening models are most promising. Strengthening linkage to care and improving digital accessibility remainpriorities for future research.
2. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Research and Clinical Practice. 2019 Nov;157:107843.
3. Bommer C, Heesemann E, Sagalova V, Manne-Goehler J, Atun R, Bärnighausen T, et al. The global economic burden of diabetes in adults aged 20–79 years: a cost-of-illness study. The Lancet Diabetes & Endocrinology . 2017 Jun;5(6):423–30.
4. Zheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nature Reviews Endocrinology. 2018 Feb;14(2):88–98.
5. American Diabetes Association. Standards of Care in Diabetes—2023. Diabetes Care. 2023;46(Suppl 1):S1–S291.
6. Butler AM. Social Determinants of Health and Racial/Ethnic Disparities in Type 2 Diabetes in Youth. Current Diabetes Reports. 2017 Aug;17(8):60.
7. Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social Determinants of Health and Diabetes: A Scientific Review. Diabetes Care. 2021 Jan 1;44(1):258–79.
8. Wharam JF, Lu CY, Zhang F, Callahan M, Xu X, Wallace J, et al. High-Deductible Insurance and Delay in Care for the Macrovascular Complications of Diabetes. Annals of Internal Medicine. 2018 Dec 18;169(12):845–54.
9. World Health Organization. Global Strategy on Digital Health 2020-2025. 1st ed. Geneva: World Health Organization; 2021. 1 p.
10. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine. 2019 Jan;25(1):44–56.
11. Kitsiou S, Paré G, Jaana M. Effects of Home Telemonitoring Interventions on Patients With Chronic Heart Failure: An Overview of Systematic Reviews. Journal of Medical Internet Research. 2015 Mar 12;17(3):e63.
12. Van Velthoven MH, Cordon C, Challagalla G. Digitization of healthcare organizations: The digital health landscape and information theory. International Journal of Medical Informatics. 2019 Apr;124:49–57.
13. Perrin Franck C, Babington-Ashaye A, Dietrich D, Bediang G, Veltsos P, Gupta PP, et al. iCHECK-DH: Guidelines and Checklist for the Reporting on Digital Health Implementations. Journal of Medical Internet Research. 2023 May 10;25:e46694.
14. Fagherazzi G. Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper. Journal of Medical Internet Research. 2020 Mar 3;22(3):e16770.
15. Greenwood DA, Gee PM, Fatkin KJ, Peeples M. A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support. Journal of Diabetes Science and Technology. 2017 Sept;11(5):1015–27.
16. Basu S, Phillips RS, Song Z, Landon BE, Bitton A. Effects of New Funding Models for Patient-Centered Medical Homes on Primary Care Practice Finances and Services: Results of a Microsimulation Model. Annals of Family Medicine. 2016 Sept 1;14(5):404–14.
17. Peek ME, Simons RA, Parker WF, Ansell DA, Rogers SO, Edmonds BT. COVID-19 Among African Americans: An Action Plan for Mitigating Disparities. American Journal of Public Health. 2021 Feb;111(2):286–92.
18. Van Veen T, Binz S, Muminovic M, Chaudhry K, Rose K, Calo S, et al. Potential of Mobile Health Technology to Reduce Health Disparities in Underserved Communities. Western Journal of Emergency Medicine [Internet]. 2019 Aug 6 [cited 2025 Dec 25];20(5). Available from: https://escholarship.org/uc/item/8vk7f65q
19. Shaw J, Jamieson T, Agarwal P, Griffin B, Wong I, Bhatia RS. Virtual care policy recommendations for patient-centred primary care: findings of a consensus policy dialogue using a nominal group technique. Journal of Telemedicine and Telecare. 2018 Oct;24(9):608–15.
20. Van Kessel R, Roman-Urrestarazu A, Anderson M, Kyriopoulos I, Field S, Monti G, et al. Mapping Factors That Affect the Uptake of Digital Therapeutics Within Health Systems: Scoping Review. Journal of Medical Internet Research. 2023 Jul 25;25:e48000.
21. Whitelaw S, Mamas MA, Topol E, Van Spall HGC. Applications of digital technology in COVID-19 pandemic planning and response. The Lancet Digit Health. 2020 Aug;2(8):e435–40.
22. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology . 2005 Feb;8(1):19–32.
23. Levac D, Colquhoun H, O’Brien KK. Scoping studies: advancing the methodology. Implementation Science. 2010 Dec;5(1):69.
24. Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Annals of Internal Medicine. 2018 Oct 2;169(7):467–73.
25. Liu J, Yi SS, Russo R, Mayer VL, Wen M, Li Y. Trends and disparities in diabetes and prediabetes among adults in the United States, 1999–2018. Public Health. 2023 Jan;214:163–70.
26. Ali MK, Bullard KM, Saaddine JB, Cowie CC, Imperatore G, Gregg EW. Achievement of Goals in U.S. Diabetes Care, 1999–2010. New England Journal of Medicine. 2013 Apr 25;368(17):1613–24.
27. Kho AN, Pacheco JA, Peissig PL, Rasmussen L, Newton KM, Weston N, et al. Electronic Medical Records for Genetic Research: Results of the eMERGE Consortium. Science Translational Medicine [Internet]. 2011 Apr 20 [cited 2025 Dec 25];3(79). Available from: https://www.science.org/doi/10.1126/scitranslmed.3001807
28. Agarwal S, LeFevre AE, Lee J, L’Engle K, Mehl G, Sinha C, et al. Guidelines for reporting of health interventions using mobile phones: mobile health (mHealth) evidence reporting and assessment (mERA) checklist. BMJ. 2016 Mar 17;i1174.
29. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science. 2009 Dec;4(1):50.
30. Jiang Q, Li JT, Sun P, Wang LL, Sun LZ, Pang SG. Effects of lifestyle interventions on glucose regulation and diabetes risk in adults with impaired glucose tolerance or prediabetes: a meta-analysis. Arch Endocrinol Metab [Internet]. 2022 Mar 16 [cited 2025 Dec 25]; Available from: https://www.aem-sbem.com/article/effects-of-lifestyle-interventions-on-glucose-regulation-and-diabetes-risk-in-adults-with-impaired-glucose-tolerance-or-prediabetes-a-meta-analysis/
31. Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. The Lancet. 2012 Jun;379(9833):2279–90.
32. Halimah N, Stang, Erika KA, Citrakesumasari, Suriah, Areni IS. Evaluation of digital health technology acceptance for breastfeeding support among perinatal women in rural areas: A scoping review. Nursing Practice Today. 2026;13(1):32–51.
| Issue | Articles in Press | |
| Section | Review Article(s) | |
| Keywords | ||
| diabetes mellitus, type early diagnosis mass screening telemedicine mobile applications medically underserved area health equity | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
