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A chat-bot in rheumatoid arthritis treatment control
- Authors: Prokofeva Y.A.1, Zheleznykh E.A.1, Menshikova I.V.1
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Affiliations:
- I.M. Sechenov First Moscow State Medical University
- Issue: Vol 4, No 1S (2023)
- Pages: 108-110
- Section: Conference proceedings
- URL: https://jdigitaldiagnostics.com/DD/article/view/430361
- DOI: https://doi.org/10.17816/DD430361
- ID: 430361
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Abstract
BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune rheumatic disease with joint damage and systemic manifestations, which worsens the quality of life and life expectancy, leading to disability in the absence of effective therapy at a young age. The goal of RA treatment is to achieve remission/low disease activity. Frequent monitoring of the disease is needed (every 1–3 months until the goal is reached, then every 3–6 months), which is not always possible due to remoteness of residence, financial capabilities of patients, and epidemic situation. Remote monitoring appears to be a possible solution to the problem; however, the effectiveness of telemedical technologies in the treatment of patients with RA is not sufficiently studied.
AIM: To investigate the effectiveness of remote-control treatment of patients with RA of high and moderate activity using a chat-bot.
METHODS: An algorithm for remote monitoring and communication with RA patients was developed. The chat-bot performs a survey every month and out-of-schedule when the patient’s condition worsens and provides the data to the doctor in a convenient form. Regular assessments of RA activity, functional impairment, and quality of life and correction of recommendations if necessary are made. All participants are coded, with only the doctor having access to personal data. In remote (60 patients) and traditional (30 patients) control groups, the time to remission/low disease activity will be compared. Adherence to the chat-bot and cost-effectiveness analysis will be studied.
RESULTS: Twenty patients were trained on how to use the chat-bot and have been using the program for 2 months. The condition is monitored and online counseling is provided if necessary. Nineteen patients had no difficulties when working with the chat-bot. One patient needed a second consultation on how to use the chat-bot. Half of the patients were over 60 years old. Most patients prefer remote counseling to a face-to-face appointment. Patients report an improved understanding of the disease, treatment principles, and methods of self-assessment of the joint condition. Remote monitoring is planned to achieve stable control of RA activity by timely detection of exacerbations and therapy correction and assessment of the need for hospitalization, which will help to reduce the period of remission/low RA activity. The economic cost of treating RA is expected to be reduced.
CONCLUSIONS: Remote monitoring using a chat-bot to improve the effectiveness of RA treatment is an important aspect of current rheumatology and a potential method for increasing the availability of medical care. The results may serve as a basis for further research on telemedical technologies and the development and application of personalized algorithms for monitoring, prevention, and treatment of patients with rheumatic diseases.
Full Text
BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune rheumatic disease with joint damage and systemic manifestations, which worsens the quality of life and life expectancy, leading to disability in the absence of effective therapy at a young age. The goal of RA treatment is to achieve remission/low disease activity. Frequent monitoring of the disease is needed (every 1–3 months until the goal is reached, then every 3–6 months), which is not always possible due to remoteness of residence, financial capabilities of patients, and epidemic situation. Remote monitoring appears to be a possible solution to the problem; however, the effectiveness of telemedical technologies in the treatment of patients with RA is not sufficiently studied.
AIM: To investigate the effectiveness of remote-control treatment of patients with RA of high and moderate activity using a chat-bot.
METHODS: An algorithm for remote monitoring and communication with RA patients was developed. The chat-bot performs a survey every month and out-of-schedule when the patient’s condition worsens and provides the data to the doctor in a convenient form. Regular assessments of RA activity, functional impairment, and quality of life and correction of recommendations if necessary are made. All participants are coded, with only the doctor having access to personal data. In remote (60 patients) and traditional (30 patients) control groups, the time to remission/low disease activity will be compared. Adherence to the chat-bot and cost-effectiveness analysis will be studied.
RESULTS: Twenty patients were trained on how to use the chat-bot and have been using the program for 2 months. The condition is monitored and online counseling is provided if necessary. Nineteen patients had no difficulties when working with the chat-bot. One patient needed a second consultation on how to use the chat-bot. Half of the patients were over 60 years old. Most patients prefer remote counseling to a face-to-face appointment. Patients report an improved understanding of the disease, treatment principles, and methods of self-assessment of the joint condition. Remote monitoring is planned to achieve stable control of RA activity by timely detection of exacerbations and therapy correction and assessment of the need for hospitalization, which will help to reduce the period of remission/low RA activity. The economic cost of treating RA is expected to be reduced.
CONCLUSIONS: Remote monitoring using a chat-bot to improve the effectiveness of RA treatment is an important aspect of current rheumatology and a potential method for increasing the availability of medical care. The results may serve as a basis for further research on telemedical technologies and the development and application of personalized algorithms for monitoring, prevention, and treatment of patients with rheumatic diseases.
About the authors
Yuliya A. Prokofeva
I.M. Sechenov First Moscow State Medical University
Author for correspondence.
Email: ulyaprokofeva@gmail.com
ORCID iD: 0000-0001-8658-3435
Russian Federation, Moscow
Elena A. Zheleznykh
I.M. Sechenov First Moscow State Medical University
Email: elenavlvp@gmail.com
ORCID iD: 0000-0002-2596-192X
Russian Federation, Moscow
Irina V. Menshikova
I.M. Sechenov First Moscow State Medical University
Email: ivmenshikova@mail.ru
ORCID iD: 0000-0003-3181-5272
Russian Federation, Moscow
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