Identification of Motivational Determinants for Telemedicine Use Among Patients With Rheumatoid Arthritis in Germany: Secondary Analysis of Data From a Nationwide Cross-Sectional Survey Study
Authors: Muehlensiepen Felix , Petit Pascal , Knitza Johannes , Welcker Martin , Vuillerme Nicolas 
Published: June 2024

Background

Previous studies have demonstrated telemedicine to be an effective tool to complement rheumatology care and address workforce shortage. With the COVID-19 outbreak, telemedicine experienced a massive upswing. An earlier analysis revealed that the motivation of patients with rheumatic and musculoskeletal diseases to use telemedicine is closely connected to their disease. It remains unclear which factors are associated with patients’ motivation to use telemedicine in certain rheumatic and musculoskeletal diseases groups, such as rheumatoid arthritis (RA).

Objective

This study aims to identify factors that determine the willingness to try telemedicine among patients diagnosed with RA.

Methods

We conducted a secondary analysis of data from a German nationwide cross-sectional survey among patients with RA. Bayesian univariate logistic regression analysis was applied to the data to determine which factors were associated with willingness to try telemedicine. Predictor variables (covariates) studied individually included sociodemographic factors (eg, age, sex) and health characteristics (eg, health status). All the variables positively and negatively associated with willingness to try telemedicine in the univariate analyses were then considered for Bayesian model averaging analysis after a selection based on the variance inflation factor (≤ 2.5) to identify determinants of willingness to try telemedicine.

Results

Among 438 surveyed patients in the initial study, 210 were diagnosed with RA (47.9%). Among them, 146 (69.5%) answered either yes or no regarding willingness to try telemedicine and were included in the analysis. A total of 22 variables (22/55, 40%) were associated with willingness to try telemedicine (region of practical equivalence %≤5). A total of 9 determinant factors were identified using Bayesian model averaging analysis. Positive determinants included desiring telemedicine services provided by a rheumatologist (odds ratio [OR] 13.7, 95% CI 5.55-38.3), having prior knowledge of telemedicine (OR 2.91, 95% CI 1.46-6.28), residing in a town (OR 2.91, 95% CI 1.21-7.79) or city (OR 0.56, 95% CI 0.23-1.27), and perceiving one’s health status as moderate (OR 1.87, 95% CI 0.94-3.63). Negative determinants included the lack of an electronic device (OR 0.1, 95% CI 0.01-0.62), absence of home internet access (OR 0.1, 95% CI 0.02-0.39), self-assessment of health status as bad (OR 0.44, 95% CI 0.21-0.89) or very bad (OR 0.47, 95% CI 0.06-2.06), and being aged between 60 and 69 years (OR 0.48, 95% CI 0.22-1.04) or older than 70 years (OR 0.38, 95% CI 0.16-0.85).

Conclusions

The results suggest that some patients with RA will not have access to telemedicine without further support. Older patients, those not living in towns, those without adequate internet access, reporting a bad health status, and those not owning electronic devices might be excluded from the digital transformation in rheumatology and might not have access to adequate RA care. These patient groups certainly require support for the use of digital rheumatology care.