Willingness to use remote patient monitoring among cardiovascular patients in a resource-limited setting: a cross-sectional study

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Abstract

Introduction: Currently, mortality by non-communicable diseases is increasing alarmingly. They account for approximately 35 million deaths each year, of which 14% are due to cardiovascular disease and 9.2% occur in Africa. Patients do not have access to healthcare services outside the healthcare setting, resulting in missed follow-ups and appointments and adverse outcomes. This study aimed to assess the willingness to use remote monitoring among cardiovascular patients in a resource-limited setting in Ethiopia. Method: An institution-based cross-sectional study was conducted from April to June 2021 among cardiovascular patients at referral hospitals in Ethiopia. A structured interview questionnaire was used to collect the data. A systematic random sampling technique was used to select 397 study participants. Binary and multivariable logistic regression analyses were employed and a 95% confidence level with a p-value <0.05 was used to determine the level of association between variables. Result: In total, 81.61% of the study participants were willing to use remote patient monitoring [95% confidence interval (CI) = 77.4%–85.1%]. Age [adjusted odds ratio (AOR) = 0.94; 95% CI: 0.90–0.98], having a mobile phone (AOR = 5.70; 95% CI: 1.86–17.22), and perceived usefulness (AOR = 1.50; 95% CI: 1.18–1.82) were significantly associated with willingness to use remote patient monitoring among cardiovascular patients. Conclusion: Cardiovascular patients had a high willingness to use remote patient monitoring. Age, perceived usefulness of remote patient monitoring, and having a mobile phone were significantly associated with a willingness to use remote patient monitoring.

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APA

Kassaw, M., Amare, G., Shitu, K., Tilahun, B., & Assaye, B. T. (2024). Willingness to use remote patient monitoring among cardiovascular patients in a resource-limited setting: a cross-sectional study. Frontiers in Digital Health, 6. https://doi.org/10.3389/fdgth.2024.1437134

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