Effectiveness and Practicality of eKTANG as a Digital Treatment for Diabetes and Relevant Influence Factors
-
Xiaohua Lu
,
Dalong Guo
,
Lie Feng
,
Yan Zhou
,
Chuangbiao Zhang
,
Jiaying Li
,
Yin Jiang
Abstract
Background: This work explored the effect of eKTANG, a new healthcare mode for diabetes patients, on diabetes management.
Methods: Allowing general utilization of medical service and health management based on Internet, eKTANG obtained the precise data like blood glucose and blood pressure examined by an intelligent glucometer, from which doctors and the nursing team will promptly analyze the data and return feedback to the patients. In our study, overall 204 patients receiving eKTANG management over 3 months in First Affiliated Hospital of Jinan University from May 2019 to Aug 2020 were enrolled as the research objects, with data collected from patient records.
Results: Through the biochemical test on relevant indexes of blood glucose, it was observed that FBG, PBG, HbA1c, TG, TC, LDL levels after management were lower than before whereas HDL expression after were lower than before. Contrasted with substandard group, standard group performed younger age, lower proportion of the married, decreased proportion of microvascular and macrovascular complications, longer course of disease, more frequent glucose monitoring, declined time of hyperglycemia and time of alarms, elevated time of euglycemia, increased proportion of diet control, more amount of exercise and higher compliance, as the number of patients choosing oral medicine in standard group was more than substandard group. The course of disease and time of hyperglycemia were risk factors of HbA1c standard reaching whereas frequency of glucose monitoring (≥1 time/week) and time of euglycemia were protective factors.
Conclusion: eKTANG effectively improved diabetes management.
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24. Whaley CM, Bollyky JB, Lu W, et al (2019). Reduced medical spending associated with increased use of a remote diabetes management program and lower mean blood glucose values. J Med Econ, 22(9): 869-877.
25. Yu JS, Xu T, James RA, Lu W, Hoffman JE (2020). Relationship Between Diabetes, Stress, and Self-Management to Inform Chronic Disease Product Development: Retrospective Cross-Sectional Study. JMIR Diabetes, 5(4): e20888.
26. Bollyky JB, Bravata D, Yang J, Williamson M, Schneider J (2018). Remote Lifestyle Coaching Plus a Connected Glucose Meter with Certified Diabetes Educator Support Improves Glucose and Weight Loss for People with Type 2 Diabetes. J Diabetes Res, 2018: 3961730.
27. Downing J, Bollyky J, Schneider J (2017). Use of a Connected Glucose Meter and Certified Diabetes Educator Coaching to Decrease the Likelihood of Abnormal Blood Glucose Excursions: The Livongo for Diabetes Program. J Med Internet Res, 19(7): e234.
28. Ji L, Hu D, Pan C, et al (2013). Primacy of the 3B approach to control risk factors for cardiovascular disease in type 2 diabetes patients. Am J Med, 126(10): 925.e11-22.
29. Cho JH, Kwon HS, Kim HS, Oh JA, Yoon KH (2011). Effects on diabetes management of a health-care provider mediated, remote coaching system via a PDA-type glucometer and the Internet. J Telemed Telecare, 17(7): 365-370.
30. Carallo C, Scavelli FB, Cipolla M, et al (2015). Management of Type 2 Diabetes Mellitus through Telemedicine. PloS One, 10(5): e0126858.
31. Yoo HJ, Park MS, Kim TN, et al (2009). A Ubiquitous Chronic Disease Care system using cellular phones and the internet. Diabet Med, 26(6): 628-635.
2. Wang Z, Li X, Chen M (2018). Socioeconomic Factors and Inequality in the Prevalence and Treatment of Diabetes among Middle-Aged and Elderly Adults in China. J Diabetes Res, 2018: 1471808.
3. Cheng C, Xin G, Xiaoli W, et al (2019). Evaluation of the implementation and effect of the healthcare cloud information platform for diabetes self-management: A case study in Shanghai. Int J Health Plann Manage, 34(3): 986-997.
4. Leger T, He B, Azarnoush K, et al (2019). Dietary EPA Increases Rat Mortality in Diabetes Mellitus, A Phenomenon Which Is Compensated by Green Tea Extract. Antioxidants (Basel), 8(11): 526.
5. AlShwaimi E, Idrees M, Berri Z, El-Sakka H, Kujan O (2019). Association between Diabetes Mellitus and Periodontal Diseases: A Survey of the Opinions of Dental Professionals. Med Princ Pract, 28(2): 141-149.
6. Xu Y, Wang L, He J, et al (2013). Prevalence and control of diabetes in Chinese adults. JAMA, 310(9): 948-959.
7. India State-Level Disease Burden Initiative Diabetes Collaborators (2018). The increasing burden of diabetes and variations among the states of India: the Global Burden of Disease Study 1990-2016. Lancet Glob Health, 6(12): e1352-e62.
8. Bilal U, Hill-Briggs F, Sánchez-Perruca L, Del Cura-González I, Franco M (2018). Association of neighbourhood socioeconomic status and diabetes burden using electronic health records in Madrid (Spain): the HeartHealthyHoods study. BMJ Open, 8(9): e021143.
9. Foos V, Wang K, McEwan P, et al (2019). Assessing the Burden of Type 2 Diabetes in China Considering the Current Status-Quo Management and Implications of Improved Management Using a Modeling Approach. Value Health Reg Issues, 18: 36-46.
10. Jørgensen PG, Jensen MT, Biering-Sørensen T, et al (2018). Burden of Uncontrolled Metabolic Risk Factors and Left Ventricular Structure and Function in Patients With Type 2 Diabetes Mellitus. J Am Heart Assoc, 7(19): e008856.
11. Li YC, Liu XT, Hu N, Jiang Y, Zhao WH (2013). [Disease burden on diabetes in China, 2010]. Zhonghua Liu Xing Bing Xue Za Zhi, 34(1): 33-36.
12. Cheng X, Gao W, Dang Y, et al (2013). Both ERK/MAPK and TGF-Beta/Smad signaling pathways play a role in the kidney fibrosis of diabetic mice accelerated by blood glucose fluctuation. J Diabetes Res, 2013: 463740.
13. Crumby AS, Holmes ER, Rosenthal M (2018). Patient centered research to improve community involvement (PaRTICIpate) in diabetes self-management: a conference series for developing collaborations between researchers, stakeholders, and patients. J Patient Rep Outcomes, 2(1): 47.
14. Jia W, Weng J, Zhu D, et al (2019). Standards of medical care for type 2 diabetes in China 2019. Diabetes Metab Res Rev, 35(6): e3158.
15. Weng J (2016). Evolution in the Chinese Diabetes Society Standards of Care for Type 2 Diabetes. Diabetes Metab Res Rev, 32(5): 440-441.
16. Cheng L, Sit JWH, Choi KC, et al (2018). Effectiveness of a patient-centred, empowerment-based intervention programme among patients with poorly controlled type 2 diabetes: A randomised controlled trial. Int J Nurs Stud, 79: 43-51.
17. Cheng L, Sit JWH, Choi KC, et al (2021). The effects of an empowerment-based self-management intervention on empowerment level, psychological distress, and quality of life in patients with poorly controlled type 2 diabetes: A randomized controlled trial. Int J Nurs Stud, 116: 103407.
18. Li X, Li Z, Liu C, et al (2017). Evaluation of the three-in-one team-based care model on hierarchical diagnosis and treatment patterns among patients with diabetes: a retrospective cohort study using Xiamen's regional electronic health records. BMC Health Serv Res, 17(1): 779.
19. Wang G, Zhang Z, Feng Y, et al (2017). Telemedicine in the Management of Type 2 Diabetes Mellitus. Am J Med Sci, 353(1): 1-5.
20. Wang L, Gao P, Zhang M, et al (2017). Prevalence and Ethnic Pattern of Diabetes and Prediabetes in China in 2013. JAMA, 317(24): 2515-2523.
21. Kwon HS, Cho JH, Kim HS, et al (2004). Establishment of blood glucose monitoring system using the internet. Diabetes Care, 27(2): 478-483.
22. Lim S, Kang SM, Shin H, et al (2011). Improved glycemic control without hypoglycemia in elderly diabetic patients using the ubiquitous healthcare service, a new medical information system. Diabetes Care, 34(2): 308-313.
23. Cho JH, Chang SA, Kwon HS, et al (2006). Long-term effect of the Internet-based glucose monitoring system on HbA1c reduction and glucose stability: a 30-month follow-up study for diabetes management with a ubiquitous medical care system. Diabetes Care, 29(12): 2625-2631.
24. Whaley CM, Bollyky JB, Lu W, et al (2019). Reduced medical spending associated with increased use of a remote diabetes management program and lower mean blood glucose values. J Med Econ, 22(9): 869-877.
25. Yu JS, Xu T, James RA, Lu W, Hoffman JE (2020). Relationship Between Diabetes, Stress, and Self-Management to Inform Chronic Disease Product Development: Retrospective Cross-Sectional Study. JMIR Diabetes, 5(4): e20888.
26. Bollyky JB, Bravata D, Yang J, Williamson M, Schneider J (2018). Remote Lifestyle Coaching Plus a Connected Glucose Meter with Certified Diabetes Educator Support Improves Glucose and Weight Loss for People with Type 2 Diabetes. J Diabetes Res, 2018: 3961730.
27. Downing J, Bollyky J, Schneider J (2017). Use of a Connected Glucose Meter and Certified Diabetes Educator Coaching to Decrease the Likelihood of Abnormal Blood Glucose Excursions: The Livongo for Diabetes Program. J Med Internet Res, 19(7): e234.
28. Ji L, Hu D, Pan C, et al (2013). Primacy of the 3B approach to control risk factors for cardiovascular disease in type 2 diabetes patients. Am J Med, 126(10): 925.e11-22.
29. Cho JH, Kwon HS, Kim HS, Oh JA, Yoon KH (2011). Effects on diabetes management of a health-care provider mediated, remote coaching system via a PDA-type glucometer and the Internet. J Telemed Telecare, 17(7): 365-370.
30. Carallo C, Scavelli FB, Cipolla M, et al (2015). Management of Type 2 Diabetes Mellitus through Telemedicine. PloS One, 10(5): e0126858.
31. Yoo HJ, Park MS, Kim TN, et al (2009). A Ubiquitous Chronic Disease Care system using cellular phones and the internet. Diabet Med, 26(6): 628-635.
| Files | ||
| Issue | Vol 51 No 1 (2022) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v51i1.8294 | |
| Keywords | ||
| Diabetes Effectiveness and precision Internet remote platform | ||
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
How to Cite
1.
Lu X, Guo D, Feng L, Zhou Y, Zhang C, Li J, Jiang Y. Effectiveness and Practicality of eKTANG as a Digital Treatment for Diabetes and Relevant Influence Factors. Iran J Public Health. 2022;51(1):67-78.
