Current Diabetes Reports

, Volume 13, Issue 2, pp 205–212 | Cite as

Personalized Decision Support in Type 2 Diabetes Mellitus: Current Evidence and Future Directions

  • Michael J. Wilkinson
  • Aviva G. Nathan
  • Elbert S. Huang
Health Care Delivery Systems in Diabetes (D Wexler, Section Editor)


The management of type 2 diabetes comprises a complex series of medical decisions regarding goals of care, self-care behaviors, and medical treatments. The quality of these medical decisions is critical to determining whether an individual diabetes patient is treated appropriately, overtreated, or undertreated. It is hypothesized that the quality of these medical decisions can be enhanced by personalized decision support tools that summarize patient clinical characteristics, treatment preferences, and ancillary data at the point of care. We describe the current state of personalized diabetes decision support on the basis of 13 recently described tools. Three tools provided support for personalized decisions based on preferences, while the remaining 10 provided support for treatment decisions designed to achieve standard diabetes goals. For the tools that supported personalized decisions, patient participation in medical decisions improved. Future decision support tools must be designed to account for both clinical characteristics and patient preferences.


Type 2 diabetes mellitus Decision support Decision support tool Decision aid Personalized decision support 



Conflicts of interest: M. J. Wilkinson, none; A. G. Nathan has received grant support from Retirement Research Foundation and the American Diabetes Association; E.S. Huang has received grant support from Retirement Research Foundation, the American Diabetes Association (Clinical Research Award), and the NIDDK (NIDDK P30 DK092949-01).


Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. 1.
    Inzucchi SE, Bergenstal RM, Buse JB, et al. Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2012;35:1364–79.PubMedCrossRefGoogle Scholar
  2. 2.
    Ismail-Beigi F, Moghissi E, Tiktin M, et al. Individualizing glycemic targets in type 2 diabetes mellitus: implications of recent clinical trials. Ann Intern Med. 2011;154:554–9.PubMedGoogle Scholar
  3. 3.
    American Diabetes Association. Executive summary: standards of medical care in diabetes--2012. Diabetes Care. 2012;35 Suppl 1:S4–S10.Google Scholar
  4. 4.
    UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352:837–53.CrossRefGoogle Scholar
  5. 5.
    Holman RR, Paul SK, Bethel MA, et al. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359:1577–89.PubMedCrossRefGoogle Scholar
  6. 6.
    The ADVANCE Collaborative Group. Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. N Engl J Med. 2008;358:2560–72.CrossRefGoogle Scholar
  7. 7.
    Duckworth W, Abraira C, Moritz T, et al. Glucose control and vascular complications in veterans with type 2 diabetes. N Engl J Med. 2009;360:129–39.PubMedCrossRefGoogle Scholar
  8. 8.
    The Action to Control Cardiovascular Risk in Diabetes Study Group. Effects of intesive glucose lowering in type 2 diabetes. N Engl J Med. 2008;358:2545–59.CrossRefGoogle Scholar
  9. 9.
    Stacey D, Bennett CL, Barry MJ, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2011;CD001431.Google Scholar
  10. 10.
    Corser W, Holmes-Rovner M, Lein C, Gossain V. A shared decision-making primary care intervention for type 2 diabetes. Diabetes Educ. 2007;33:700–8.PubMedCrossRefGoogle Scholar
  11. 11.
    •• Mullan RJ, Montori VM, Shah ND, et al. The diabetes mellitus medication choice decision aid. Arch Intern Med. 2009;169:1560–8. This article describes use of a personalized decision support tool that considered patient preferences in treatment decisions. Its use increased patient involvement, as well as aspects of knowledge and acceptability.PubMedCrossRefGoogle Scholar
  12. 12.
    Weymiller AJ, Montori VM, Jones LA, et al. Helping patients with type 2 diabetes mellitus make treatment decisions. Arch Intern Med. 2007;167:1076–82.PubMedCrossRefGoogle Scholar
  13. 13.
    Nannenga MR, Montori VM, Weymiller AJ, et al. A treatment decision aid may increase patient trust in the diabetes specialist. The Statin Choice randomized trial. Health Expect. 2009;12:38–44.PubMedCrossRefGoogle Scholar
  14. 14.
    Abadie R, Weymiller AJ, Tilburt J, et al. Clinician's use of the Statin Choice decision aid in patients with diabetes: a videographic study nested in a randomized trial. J Eval Clin Pract. 2009;15:492–7.PubMedCrossRefGoogle Scholar
  15. 15.
    •• Mann DM, Ponieman D, Montori VM, et al. The Statin Choice decision aid in primary care: a randomized trial. Patient Educ Couns. 2010;80:138–40. This article describes recent use of the Statin Choice tool, an important example of a personalized decision support tool that considers patient preferences in treatment decisions.PubMedCrossRefGoogle Scholar
  16. 16.
    Cleveringa FG, Gorter KJ, van den Donk M, Rutten GE. Combined task delegation, computerized decision support, and feedback improve cardiovascular risk for type 2 diabetic patients. Diabetes Care. 2008;31:2273–5.PubMedCrossRefGoogle Scholar
  17. 17.
    Holbrook A, Thabane L, Keshavjee K, et al. Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial. CMAJ. 2009;181:37–44.PubMedGoogle Scholar
  18. 18.
    Hunt JS, Siemienczuk J, Gillanders W, et al. The impact of a physician-directed health information technology system on diabetes outcomes in primary care: a pre- and post-implementation study. Informat Prim Care. 2009;17:165–74.Google Scholar
  19. 19.
    Maclean CD, Gagnon M, Callas P, Littenberg B. The Vermont diabetes information system: a cluster randomized trial of a population based decision support system. J Gen Intern Med. 2009;24:1303–10.PubMedCrossRefGoogle Scholar
  20. 20.
    Augstein P, Vogt L, Kohnert KD, et al. Translation of personalized decision support into routine diabetes care. J Diabetes Sci Technol. 2010;4:1532–9.PubMedGoogle Scholar
  21. 21.
    O'Connor PJ, Sperl-Hillen JM, Rush WA, et al. Impact of electronic health record clinical decision support on diabetes care: a randomized trial. Ann Fam Med. 2011;9:12–21.PubMedCrossRefGoogle Scholar
  22. 22.
    Quinn CC, Shardell MD, Terrin ML, et al. Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care. 2011;34:1934–42.PubMedCrossRefGoogle Scholar
  23. 23.
    Saenz A, Brito M, Moron I, et al. Development and validation of a computer application to aid the physician's decision-making process at the start of and during treatment with insulin in type 2 diabetes: a randomized and controlled trial. J Diabetes Sci Technol. 2012;6:581–8.PubMedGoogle Scholar
  24. 24.
    Leal J, Gray AM, Clarke PM. Development of life-expectancy tables for people with type 2 diabetes. Eur Heart J. 2009;30:834–9.PubMedCrossRefGoogle Scholar
  25. 25.
    • Rodbard D, Vigersky RA. Design of a decision support system to help clinicians manage glycemia in patients with type 2 diabetes mellitus. J Diabetes Sci Technol. 2011;5:402–11. From the perspective of personalization, this article is important because the tool allows physicians to set hemoglobin A1c and other glycemia goals. This introduces the potential for personalization, if physicians using the tool set glycemic goals on the basis of a consideration of patient clinical factors or preferences.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Michael J. Wilkinson
    • 1
  • Aviva G. Nathan
    • 1
  • Elbert S. Huang
    • 1
  1. 1.University of ChicagoChicagoUSA

Personalised recommendations