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BearingOn.Health Original Contribution
September 2023
by Janice MacLeod, MA, RD, CDCES, FADCES, Janice MacLeod Consulting
The evolution of health technologies coupled with education and clinical support can lead to improvements in self-management and the health of those with diabetes-cardiometabolic conditions (1). A growing suite of connected technologies gathering data, from glucose monitors, and fitness trackers, to heart rate monitors and wellness apps, present a golden opportunity to build a data-driven approach to diabetes-cardiometabolic care. This enables pivoting from episodic, reactive care to continuous, proactive care (2).
Artificial intelligence (AI) can make the gathered data meaningful and actionable whether providing automated, personalized coaching, supporting daily self-care, or clinical decision support informing timely care plan adjustments. In recent years we have witnessed the expansion of telehealth, remote patient monitoring and the emergence of virtual care and education clinics often coordinated by diabetes care and education specialists (DCESs). In addition to providing education and technology training, the DCES may use protocols to make care plan adjustments, guided by prescribing clinicians (3, 4, 5). An annual review article on diabetes digital health reports on research demonstrating the efficacy and potential application of these emerging technologies and care models (8).
Recognizing the incredibly high healthcare costs and the imbalance in the growing number of people with chronic conditions and available, skilled care providers (9), it is time to harness expanding digital health capabilities to build a continuous, data-informed, virtual care model linking individuals to expert care on-demand, 24/7, better matching the reality of living with relentless chronic conditions. AI-driven remote monitoring of population-level data can efficiently identify the timing and level of human touchpoint needed whether a brief coaching nudge or reminder, an adjustment in a therapy prescription or behavioral or social support. Person-level data then informs the care team interaction leading to meaningful connection and more timely care and self-management plan adjustments (10). These specialized virtual care and education clinics could be connected to local community resources to facilitate engagement and address social determinants of health (Figure Above).
What is the path forward? Barriers are complex but not insurmountable with engagement from industry, regulators, care providers and professional associations. It will be critical to address the technology divide so all have access to digital health and on-demand connection to the care team11. Digital health tools and virtual care platforms will need to be coordinated and data integrated. Also required is a further shift from transactional reimbursement to outcomes-focused, personalized population health.
Years ago healthcare executive and digital health expert, Chris Bergstrom observed, that what is needed is a “Jiffy Lube” for diabetes. With AI rapidly advancing and a health crisis looming, is it finally time for professional societies and thought leaders to unite in a call-to-action to make a diabetes-cardiometabolic “Jiffy Lube” type virtual specialty clinic a reality?
References:
ElSayed NA, et al. Diabetes Technology: Standards of Care in Diabetes-2023. Diabetes Care, 2023;46(Suppl. 1): S111-S127.
Harbison R, Hecht M, MacLeod J. Building a Data-Driven Multiple Daily Insulin Therapy Model Using Smart Insulin Pens. J Diabetes Sci Technol, 2022; 16(3):610-616. https://doi.org/10.1177/1932296820951225
Ahn DT. The COVID-19 Pandemic: A “Tech”-tonic Shift Toward Virtual Diabetes Care. J Diabetes Sci and Technol, 2020;14(4):708-709.
Cafazzo J. A Digital-First Model of Diabetes Care. DT&T, 2019;21(Supl 2):S2-52-S2-58.
Levine BJ, Close KL, Gabbay RA. Reviewing U.S. Connected Diabetes Care: The Newest Member of the Team. Diabetes Technol Ther, 2020;22(1) DOI:10,1089/dia.2019.0273.
MacLeod J, Head R, Smithson T. How Enterprising Educators Embrace the Golden Opportunity of Technology-Enabled Diabetes Services. AADE In Practice, 2019;7(3):12-19 https://doi.org/10.1177/2325160319839208
Greenwood D, Gee P, Fatkin KJ, Pepples M. A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support. J Diabetes Sci Technol. 2017;11(5):1015-1027. DOI: 10.1177/1932296817713506
Clements M, Kaufman N, Mel E. Using Digital Health Technology to Prevent and Treat Diabetes. Diabetes Technol Ther, 2023;25(Supl 1):S-90-S-108.
Phillip M, Bergenstal RM, Close KL, Danne T, Garg SK, Heinemann L, Hirsch IB, Kovatchev BP, Laffel LM, Mohan V, Parkin CG, Battelino T. The Digital/Virtual Diabetes Clinic: The Future Is Now-Recommendations from an International Panel on Diabetes Digital Technologies Introduction. Diabetes Technol Ther. 2021 Feb;23(2):146-154. doi: 10.1089/dia.2020.0375. Epub 2020 Sep 28. PMID: 32905711; PMCID: PMC8098767.
Lindsey M. Philpot, Sagar B. Dugani, Abhinav Singla, Meredith DeZutter, Jon O. Ebbert. (2023). Digital Care Horizon: A Framework for Extending Health Care Through Digital Transformation. Mayo Clinic Proceedings: Digital Health, 1(3), 210-216. DOI: 10.1016/j.mcpdig.2023.05.005
Rubin R. Internet Access as a Social Determinant of Health. JAMA. 2021;326(4):298. doi:10.1001/jama.2021.11733
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