Internet of things technology in the management of chronic kidney disease_West China Medical Journal

Authors：

YING Zhiye ^1,2 , LI Chunyang ^1,2 ,  ZENG Xiaoxi ^1,2,3 , FU Ping ^2,3

1. West China Biomedical Big Data Center, West China School of Medicine / West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Medical Big Data Center, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
3. Department of Nephrology / Kidney Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

ZENG Xiaoxi, Email: zengxiaoxi@wchscu.cn

Keywords：

Internet of things; Chronic kidney disease; Chronic disease management

DOI：

10.7507/1002-0179.201907022

Video：

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Chronic kidney disease (CKD) has become a global public health problem because of its high prevalence, low awareness, poor prognosis, and high medical costs. Effective follow-up management can facilitate timely adjustment of the treatment of the CKD patients and delay the disease progression. The application of internet of things (IoT) technology in dynamic monitoring and telemedicine is helpful for the self-management of patients with chronic diseases, and can provide convenient, intelligent, and humanized medical and health services. In the future, with the rapid growth of demands of CKD management and innovations in information technology, new medical IoT industry will accelerate the intelligent development of CKD management. Multi-disciplinary and multi-industrial collaboration should be promoted to solve current challenges, such as evaluation of actual effectiveness, the system design and construction, and the accessibility of intelligent healthcare services, to ensure that IoT products can improve clinical outcomes, reduce medical expenditure, and lower disease burden.

Citation： YING Zhiye, LI Chunyang, ZENG Xiaoxi, FU Ping. Internet of things technology in the management of chronic kidney disease. West China Medical Journal, 2019, 34(7): 827-831. doi: 10.7507/1002-0179.201907022 Copy

1.	Zhang L, Wang F, Wang L, et al. Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet, 2012, 379(9818): 815-822.
2.	赵德龙. 维持性血液透析患者流行病学调查及生存预后相关性分析. 北京: 中国人民解放军医学院, 2016.
3.	Levey AS, Eckardt KU, Tsukamoto Y, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int, 2005, 67(6): 2089-2100.
4.	Hwang SJ, Tsai JC, Chen HC. Epidemiology, impact and preventive care of chronic kidney disease in Taiwan. Nephrology, 2010, 15(Suppl 2): 3-9.
5.	Liu ZH. Nephrology in China. Nat Rev Nephrol, 2013, 9(9): 523-528.
6.	刘锦林, 何荣鑫, 王雪, 等. 职工基本医保肾透析患者医疗服务利用研究—基于六省六市的调查. 中国卫生事业管理, 2016, 33(8): 585-587, 594.
7.	Levey AS, Schoolwerth AC, Burrows NR, et al. Comprehensive public health strategies for preventing the development, progression, and complications of CKD: report of an expert panel convened by the Centers for Disease Control and Prevention. Am J Kidney Dis, 2009, 53(3): 522-535.
8.	Qian Y, Wu D, Bao W, et al. The internet of things for smart cities: technologies and applications. IEEE Netw, 2019, 33(2): 4-5.
9.	王智彪, 冉鹏, 陈巧. 物联网技术在医疗服务领域的应用与发展现状. 物联网学报, 2018, 2(3): 1-10.
10.	许俊杰, 陈军. 基于物联网的智慧医疗系统及其发展应用. 中国医疗设备, 2017, 32(10): 118-121, 131.
11.	Lew SQ, Sikka N, Thompson C, et al. Impact of remote biometric monitoring on cost and hospitalization outcomes in peritoneal dialysis. J Telemed Telecare, 2018.
12.	Lew SQ, Sikka N, Thompson C, et al. Adoption of telehealth: remote biometric monitoring among peritoneal dialysis patients in the United States. Perit Dial Int, 2017, 37(5): 576-578.
13.	Berman SJ, Wada C, Minatodani D, et al. Home-based preventative care in high-risk dialysis patients:a pilot study. Telemed J E Health, 2011, 17(4): 283-287.
14.	赖汝楠, 刘洪英, 王泽义, 等. 基于网络的智能腹膜透析系统设计. 传感器与微系统, 2018, 37(3): 78-80.
15.	张宝露, 孙子科技木, 鞠梅, 等. 基于物联网云计算技术的远程医疗在老年慢性病管理中的研究进展. 中国老年学杂志, 2017, 37(11): 2835-2838.
16.	吕慧梅, 石贞仙. 慢性肾脏病患者管理发展现状. 山西医药杂志, 2018, 47(3): 274-276.
17.	Sicotte C, Moqadem K, Vasilevsky MA, et al. Use of telemedicine for haemodialysis in very remote areas: the Canadian First Nations. J Telemed Telecare, 2011, 17(3): 146-149.
18.	Gallar P, Vigil A, Rodríguez I, et al. Two-year experience with telemedicine in the follow-up of patients in home peritoneal dialysis. J Telemed Telecare, 2007, 13(6): 288-292.
19.	Campbell M, Akbari A, Amos S, et al. Feasibility of providing nephrology services to remote communities with videoconferencing. J Telemed Telecare, 2012, 18(1): 13-16.
20.	Thilly N, Chanliau J, Frimat L, et al. Cost-effectiveness of home telemonitoring in chronic kidney disease patients at different stages by a pragmatic randomized controlled trial (eNephro): rationale and study design. BMC Nephrol, 2017, 18(1): 126.
21.	陈梓曦, 黄刊迪. 移动医疗在医疗信息化建设中的应用综述. 科技视界, 2016(5): 272-273.
22.	Hayashi A, Yamaguchi S, Waki K, et al. Testing the feasibility and usability of a novel smartphone-based self-management support system for dialysis patients: a pilot study. JMIR Res Protoc, 2017, 6(4): e63.
23.	崔建英, 贾依娜. 基于微信公众号构建腹膜透析病人交互式随访平台的应用效果. 护理研究, 2016, 30(5): 1889-1891.
24.	李雨昕, 杨茜, 李娜, 等. 微信在中青年慢性肾病患者延续性护理中的应用研究. 泸州医学院学报, 2016, 39(2): 166-169.
25.	Murali S, Arab L, Vargas R, et al. Internet-based tools to assess diet and provide feedback in chronic kidney disease stage IV: a pilot study. J Ren Nutr, 2013, 23(2): e33-e42.
26.	Xu Y, Wang LM, He J, et al. Prevalence and control of diabetes in Chinese adults. JAMA, 2013, 310(9): 948-958.
27.	Wang J, Zhang L, Wang F, et al. Prevalence, awareness, treatment, and control of hypertension in China: results from a national survey. Am J Hypertens, 2014, 27(11): 1355-1361.
28.	Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet, 2014, 384(9945): 766-781.
29.	Zhang LX, Wang HY. Chronic kidney disease epidemic: cost and health care implications in China. Semin Nephrol, 2009, 29(5): 483-486.
30.	Klag MJ, Whelton PK, Randall BL, et al. Blood pressure and end-stage renal disease in men. N Engl J Med, 1996, 334(1): 13-18.
31.	Tozawa M, Iseki K, Iseki C, et al. Blood pressure predicts risk of developing end-stage renal disease in men and women. Hypertension, 2003, 41(6): 1341-1345.
32.	尤贺, 崔展铭. 5G 移动通信技术下的物联网时代. 中国科技信息, 2017(7): 26-27.
33.	Ishani A, Christopher J, Palmer D, et al. Telehealth by an interprofessional team in patients with CKD: a randomized controlled trial. Am J Kidney Dis, 2016, 68(1): 41-49.
34.	Wallace EL, Rosner MH, Alscher MD, et al. Remote patient management for home dialysis patients. Kidney Int Rep, 2017, 2(6): 1009-1017.
35.	Bonner A, Gillespie K, Campbell KL, et al. Evaluating the prevalence and opportunity for technology use in chronic kidney disease patients: a cross-sectional study. BMC Nephrol, 2018, 19(1): 28.
36.	Becker S, Kribben A, Meister S, et al. User profiles of a smartphone application to support drug adherence--experiences from the iNephro project. PLoS One, 2013, 8(10): e78547.

1. Zhang L, Wang F, Wang L, et al. Prevalence of chronic kidney disease in China: a cross-sectional survey. Lancet, 2012, 379(9818): 815-822.
2. 赵德龙. 维持性血液透析患者流行病学调查及生存预后相关性分析. 北京: 中国人民解放军医学院, 2016.
3. Levey AS, Eckardt KU, Tsukamoto Y, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int, 2005, 67(6): 2089-2100.
4. Hwang SJ, Tsai JC, Chen HC. Epidemiology, impact and preventive care of chronic kidney disease in Taiwan. Nephrology, 2010, 15(Suppl 2): 3-9.
5. Liu ZH. Nephrology in China. Nat Rev Nephrol, 2013, 9(9): 523-528.
6. 刘锦林, 何荣鑫, 王雪, 等. 职工基本医保肾透析患者医疗服务利用研究—基于六省六市的调查. 中国卫生事业管理, 2016, 33(8): 585-587, 594.
7. Levey AS, Schoolwerth AC, Burrows NR, et al. Comprehensive public health strategies for preventing the development, progression, and complications of CKD: report of an expert panel convened by the Centers for Disease Control and Prevention. Am J Kidney Dis, 2009, 53(3): 522-535.
8. Qian Y, Wu D, Bao W, et al. The internet of things for smart cities: technologies and applications. IEEE Netw, 2019, 33(2): 4-5.
9. 王智彪, 冉鹏, 陈巧. 物联网技术在医疗服务领域的应用与发展现状. 物联网学报, 2018, 2(3): 1-10.
10. 许俊杰, 陈军. 基于物联网的智慧医疗系统及其发展应用. 中国医疗设备, 2017, 32(10): 118-121, 131.
11. Lew SQ, Sikka N, Thompson C, et al. Impact of remote biometric monitoring on cost and hospitalization outcomes in peritoneal dialysis. J Telemed Telecare, 2018.
12. Lew SQ, Sikka N, Thompson C, et al. Adoption of telehealth: remote biometric monitoring among peritoneal dialysis patients in the United States. Perit Dial Int, 2017, 37(5): 576-578.
13. Berman SJ, Wada C, Minatodani D, et al. Home-based preventative care in high-risk dialysis patients:a pilot study. Telemed J E Health, 2011, 17(4): 283-287.
14. 赖汝楠, 刘洪英, 王泽义, 等. 基于网络的智能腹膜透析系统设计. 传感器与微系统, 2018, 37(3): 78-80.
15. 张宝露, 孙子科技木, 鞠梅, 等. 基于物联网云计算技术的远程医疗在老年慢性病管理中的研究进展. 中国老年学杂志, 2017, 37(11): 2835-2838.
16. 吕慧梅, 石贞仙. 慢性肾脏病患者管理发展现状. 山西医药杂志, 2018, 47(3): 274-276.
17. Sicotte C, Moqadem K, Vasilevsky MA, et al. Use of telemedicine for haemodialysis in very remote areas: the Canadian First Nations. J Telemed Telecare, 2011, 17(3): 146-149.
18. Gallar P, Vigil A, Rodríguez I, et al. Two-year experience with telemedicine in the follow-up of patients in home peritoneal dialysis. J Telemed Telecare, 2007, 13(6): 288-292.
19. Campbell M, Akbari A, Amos S, et al. Feasibility of providing nephrology services to remote communities with videoconferencing. J Telemed Telecare, 2012, 18(1): 13-16.
20. Thilly N, Chanliau J, Frimat L, et al. Cost-effectiveness of home telemonitoring in chronic kidney disease patients at different stages by a pragmatic randomized controlled trial (eNephro): rationale and study design. BMC Nephrol, 2017, 18(1): 126.
21. 陈梓曦, 黄刊迪. 移动医疗在医疗信息化建设中的应用综述. 科技视界, 2016(5): 272-273.
22. Hayashi A, Yamaguchi S, Waki K, et al. Testing the feasibility and usability of a novel smartphone-based self-management support system for dialysis patients: a pilot study. JMIR Res Protoc, 2017, 6(4): e63.
23. 崔建英, 贾依娜. 基于微信公众号构建腹膜透析病人交互式随访平台的应用效果. 护理研究, 2016, 30(5): 1889-1891.
24. 李雨昕, 杨茜, 李娜, 等. 微信在中青年慢性肾病患者延续性护理中的应用研究. 泸州医学院学报, 2016, 39(2): 166-169.
25. Murali S, Arab L, Vargas R, et al. Internet-based tools to assess diet and provide feedback in chronic kidney disease stage IV: a pilot study. J Ren Nutr, 2013, 23(2): e33-e42.
26. Xu Y, Wang LM, He J, et al. Prevalence and control of diabetes in Chinese adults. JAMA, 2013, 310(9): 948-958.
27. Wang J, Zhang L, Wang F, et al. Prevalence, awareness, treatment, and control of hypertension in China: results from a national survey. Am J Hypertens, 2014, 27(11): 1355-1361.
28. Ng M, Fleming T, Robinson M, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet, 2014, 384(9945): 766-781.
29. Zhang LX, Wang HY. Chronic kidney disease epidemic: cost and health care implications in China. Semin Nephrol, 2009, 29(5): 483-486.
30. Klag MJ, Whelton PK, Randall BL, et al. Blood pressure and end-stage renal disease in men. N Engl J Med, 1996, 334(1): 13-18.
31. Tozawa M, Iseki K, Iseki C, et al. Blood pressure predicts risk of developing end-stage renal disease in men and women. Hypertension, 2003, 41(6): 1341-1345.
32. 尤贺, 崔展铭. 5G 移动通信技术下的物联网时代. 中国科技信息, 2017(7): 26-27.
33. Ishani A, Christopher J, Palmer D, et al. Telehealth by an interprofessional team in patients with CKD: a randomized controlled trial. Am J Kidney Dis, 2016, 68(1): 41-49.
34. Wallace EL, Rosner MH, Alscher MD, et al. Remote patient management for home dialysis patients. Kidney Int Rep, 2017, 2(6): 1009-1017.
35. Bonner A, Gillespie K, Campbell KL, et al. Evaluating the prevalence and opportunity for technology use in chronic kidney disease patients: a cross-sectional study. BMC Nephrol, 2018, 19(1): 28.
36. Becker S, Kribben A, Meister S, et al. User profiles of a smartphone application to support drug adherence--experiences from the iNephro project. PLoS One, 2013, 8(10): e78547.

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