Background. Remote follow-up of patients with chronic non-communicable diseases is an increasingly popular and one of the most fast-growing telemedicine branches, mainly due to COVID-19 pandemic. There are certain premises for a wider and more routine use of telemedicine, one of them being coverage of telemedical consultations by the government insurance program. Aim. To test a remote self-control program for patients with chronic non-infectious diseases who are followed-up by the doctors of the rheumatology department of the Moscow Regional Research Clinical Institute n.a. M.F. Vladimirsky , and to assess patient adherence to this program. Materials and methods. We enrolled 120 patients with rheumatic diseases. The type of telemedicine technology used was a remote self-control program, where patients keep track of the doctor’s prescriptions and recommendations, how they are feeling, and disease symptoms persistence. Results. The mean age of patients was 46.8±2.3 years; follow-up time ranged from 1 to 7 months with the mean of 96.2±9.3 days. Mean number of drug prescriptions per patient per day was 7.58 (max – 26 prescriptions, min -2 prescriptions). Patients adherence to the studied self-control program was 91.7%. Conclusion. Patients with chronic non-infectious diseases, requiring regular follow-up in outpatient settings, benefit from the use of telemedicine technology allowing for self-control, drug prescriptions tracking and motivating for self-education about the disease.
References
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23. Elbert NJ, van Os-Medendorp H, van Renselaar W, et al. Effectiveness and cost-effectiveness of ehealth interventions in somatic diseases: a systematic review of systematic reviews and meta-analyses. J Med Internet Res. 2014; 16(4): e110.
24. Pekmezaris R, Tortez L, Williams M, et al. Home Telemonitoring In Heart Failure: A Systematic Review And Meta-Analysis. Health Affairs. 2018; 37(12): 1983-1989.
25. Knitza J, Simon D, Lambrecht A, et al. Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study. JMIR MhealthUhealth. 2020; 8(8): e19661. doi : 10.2196/19661.
2. Cleland JGF. The Trans-European Network—Home-Care Management System (TEN-HMS) Study: An Investigation of the Effect of Telemedicine on Outcomes in Europe. Dis. Manag. Health Outcomes. 2006; 14(1): 23-28.
3. Chaudhry SI, Mattera JA, Curtis JP, et al. Telemonitoring in patients with heart failure. N. Engl. J. Med. 2010; 363: 2301-2309.
4. Powell LH, Calvin JE Jr, Richardson D, et al. HART Investigators. Self-management counseling in patients with heart failure: the heart failure adherence and retention randomized behavioral trial. JAMA. 2010; 304(12): 1331-8. doi : 10.1001/jama.2010.1362.
5. Koehler F, Winkler S, Schieber M, et al. Impact of remote telemedical management on mortality and hospitalizations in ambulatory patients with chronic heart failure: The telemedical interventional monitoring in heart failure study. Circulation. 2011; 123: 1873-1880.
6. Bokeriya OL, Ispiryan A. YU. Monitoring hronicheskoj serdechnoj nedostatochnosti na domu. Ann. aritm. 2012; 2 ; 14-22. ( In Russ.).
7. Ong MK, Romano PS, Edgington S, et al. Effectiveness of Remote Patient Monitoring After Discharge of Hospitalized Patients with Heart Failure — The Better Effectiveness After Transition-Heart Failure (BEAT-HF) Randomized Clinical Trial. JAMA Intern. Med. 2016; 176: 310-318.
8. Andrès E, Talha S, Zulfiqar AA, et al. Current Research and New Perspectives of Telemedicine in Chronic Heart Failure: Narrative Review and Points of Interest for the Clinician. J Clin Med. 2018; 7(12): 544. doi : 10.3390/jcm7120544.
9. McManus RJ, Mant J, Bray EP, et al. Telemonitoring and self-management in the control of hypertension (TASMINH2): a randomised controlled trial. Lancet. 2010; 376(9736): 163–72. doi : 10.1016/S0140-6736(10)60964-6.
10. Margolis KL, Kerby TJ, Asche SE, et al. Design and rationale for Home Blood Pressure Telemonitoring and Case Management to Control Hypertension ( HyperLink ): a cluster randomized trial. ContempClin Trials. 2012; 33(4): 794-803. doi : 10.1016/j.cct.2012.03.014.
11. McKinstry B, Hanley J, Wild S, et al. Telemonitoring based service redesign for the management of uncontrolled hypertension: multicentrerandomised controlled trial. Br Med J. 2013; 346: f3030. doi : 10.1136/ bmj.f 3030.
12. Hallberg I, Ranerup A, Kjellgren K. Supporting the self-management of hypertension: Patients’ experiences of using a mobile phone-based system. J Hum Hypertens. 2016; 30(2): 141-6. doi : 10.1038/jhh.2015.37.
13. Mills KT, Bundy JD, Kelly TN, et al. Global disparities of hypertension prevalence and control: a systematic analysis of population-based studies from 90 countries. Circulation. 2016; 134(6): 441-50. doi : 10.1161/CIRCULATIONAHA.115.018912.
14. Liu S, Brooks D, Thomas SG, Eysenbach G, Nolan RP. Effectiveness of user- and expert-driven web-based hypertension programs: an RCT. Am J Prev Med. 2018; 54(4): 576-83. doi : 10.1016/j.amepre.2018.01.009.
15. Dugelay G, Kivits J, Desse L, Boivin JM. Implementation of home blood pressure monitoring among French GPs: A long and winding road. PLoS One. 2019; 14(9): e0220460. doi : 10.1371/journal.pone.0220460.
16. Gorenkov RV, Yakushin MA, Safina DE, et al. The importance of the study of central hemodynamics using volumetric compression oscillometry in clinical practice: resolved and unresolved issues. Cardiometry. 2020; 16: 42-54.
17. Li R, Liang N, Bu F, Hesketh T. The Effectiveness of Self-Management of Hypertension in Adults Using Mobile Health: Systematic Review and Meta-Analysis. JMIR MhealthUhealth. 2020; 8(3): e17776. doi : 10.2196/17776.
18. Greenwood DA, Gee PM, Fatkin KJ, Peeples M. A systematic review of reviews evaluating technology-enabled diabetes self-management education and support. J Diabetes Sci Technol. 2017; 11(5): 1015-27. doi : 10.1177/1932296817713506.
19. Jeong JY, Jeon JH, Bae KH, et al. Smart Care Based on Telemonitoring and Telemedicine for Type 2 Diabetes Care: Multi-Center Randomized Controlled Trial. Telemed J E Health. 2018; 24(8): 604-613. doi : 10.1089/tmj.2017.0203. Epub 2018 Jan 17. PMID: 29341843.
20. Mao Y, Lin W, Wen J, Chen G. Impact and efficacy of mobile health intervention in the management of diabetes and hypertension: a systematic review and meta-analysis. BMJ Open Diabetes Res Care. 2020; 8(1): e001225. doi : 10.1136/bmjdrc-2020-001225.
21. Cross AJ, Elliott RA, Petrie K, Kuruvilla L, George J. Interventions for improving medication-taking ability and adherence in older adults prescribed multiple medications. Cochrane Database Syst Rev. 2020; 5(5): CD012419. doi : 10.1002/14651858.CD012419.pub2.
22. Yakushin M А , Gorenkov RV, Dvorina OG, Yarotsky SYu , Shukurlaeva G. Personal profile of systemic hemodynamics in solving global public health problems. Cardiometry. 2020; 16: 35-41.
23. Elbert NJ, van Os-Medendorp H, van Renselaar W, et al. Effectiveness and cost-effectiveness of ehealth interventions in somatic diseases: a systematic review of systematic reviews and meta-analyses. J Med Internet Res. 2014; 16(4): e110.
24. Pekmezaris R, Tortez L, Williams M, et al. Home Telemonitoring In Heart Failure: A Systematic Review And Meta-Analysis. Health Affairs. 2018; 37(12): 1983-1989.
25. Knitza J, Simon D, Lambrecht A, et al. Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study. JMIR MhealthUhealth. 2020; 8(8): e19661. doi : 10.2196/19661.
For citation
Gorenkov R.V., Ivanitskii L.V., Pozharov I.V., Kurbatova E.I., Obieedkov I.V., Cherniavskaia T.K., Kakorina E.P. Experience of remote monitoring in patients with chronic non-communicable diseases. Medical doctor and information technology. 2022; 1: 30-39. (In Russ.). doi : 1025881/18110193_2022_1_30
Keywords