Robert H. Smith School of Business, University of Maryland, College Park, MD, United States.
Institute for Systems Research, University of Maryland, College Park, MD, United States.
JMIR Mhealth Uhealth. 2021 Apr 1;9(4):e24646. doi: 10.2196/24646.
Heart failure (HF) is associated with high mortality rates and high costs, and self-care is crucial in the management of the condition. Telehealth can promote patients' self-care while providing frequent feedback to their health care providers about the patient's compliance and symptoms. A number of technologies have been considered in the literature to facilitate telehealth in patients with HF. An important factor in the adoption of these technologies is their ease of use. Conversational agent technologies using a voice interface can be a good option because they use speech recognition to communicate with patients.
The aim of this paper is to study the engagement of patients with HF with voice interface technology. In particular, we investigate which patient characteristics are linked to increased technology use.
We used data from two separate HF patient groups that used different telehealth technologies over a 90-day period. Each group used a different type of voice interface; however, the scripts followed by the two technologies were identical. One technology was based on Amazon's Alexa (Alexa+), and in the other technology, patients used a tablet to interact with a visually animated and voice-enabled avatar (Avatar). Patient engagement was measured as the number of days on which the patients used the technology during the study period. We used multiple linear regression to model engagement with the technology based on patients' demographic and clinical characteristics and past technology use.
In both populations, the patients were predominantly male and Black, had an average age of 55 years, and had HF for an average of 7 years. The only patient characteristic that was statistically different (P=.008) between the two populations was the number of medications they took to manage HF, with a mean of 8.7 (SD 4.0) for Alexa+ and 5.8 (SD 3.4) for Avatar patients. The regression model on the combined population shows that older patients used the technology more frequently (an additional 1.19 days of use for each additional year of age; P=.004). The number of medications to manage HF was negatively associated with use (-5.49; P=.005), and Black patients used the technology less frequently than other patients with similar characteristics (-15.96; P=.08).
Older patients' higher engagement with telehealth is consistent with findings from previous studies, confirming the acceptability of technology in this subset of patients with HF. However, we also found that a higher number of HF medications, which may be correlated with a higher disease burden, is negatively associated with telehealth use. Finally, the lower engagement of Black patients highlights the need for further study to identify the reasons behind this lower engagement, including the possible role of social determinants of health, and potentially create technologies that are better tailored for this population.
心力衰竭（HF）与高死亡率和高成本相关，自我护理是管理该疾病的关键。远程医疗可以促进患者的自我护理，同时向医疗保健提供者提供有关患者依从性和症状的频繁反馈。文献中已经考虑了许多技术来促进 HF 患者的远程医疗。这些技术采用的一个重要因素是其易用性。使用语音接口的对话代理技术可能是一个不错的选择，因为它们使用语音识别与患者进行交流。
本文旨在研究 HF 患者对语音接口技术的参与度。特别是，我们调查了哪些患者特征与增加技术使用相关。
我们使用了两个单独的 HF 患者组的数据，这些患者在 90 天的时间内使用了不同的远程医疗技术。每个组都使用了不同类型的语音接口；然而，两种技术遵循的脚本是相同的。一种技术基于亚马逊的 Alexa（Alexa+），而在另一种技术中，患者使用平板电脑与视觉动画和语音启用的头像（Avatar）进行交互。患者参与度的衡量标准是在研究期间患者使用技术的天数。我们使用多元线性回归根据患者的人口统计学和临床特征以及过去的技术使用情况来建立对技术的参与度模型。
在两个群体中，患者主要是男性和黑人，平均年龄为 55 岁，平均 HF 病史为 7 年。两个群体之间唯一具有统计学差异的患者特征（P=.008）是他们用于管理 HF 的药物数量，Alexa+患者的平均值为 8.7（SD 4.0），Avatar 患者为 5.8（SD 3.4）。在合并人群的回归模型中，年龄较大的患者更频繁地使用该技术（每增加 1 岁，使用时间增加 1.19 天；P=.004）。用于管理 HF 的药物数量与使用呈负相关（-5.49；P=.005），并且黑人患者的使用频率低于具有相似特征的其他患者（-15.96；P=.08）。
HF 患者的远程医疗使用量较高，这与之前的研究结果一致，证实了该技术在 HF 患者这一亚组中的可接受性。然而，我们还发现，HF 药物数量的增加，这可能与疾病负担的增加有关，与远程医疗的使用呈负相关。最后，黑人患者的参与度较低突出表明需要进一步研究，以确定这种较低参与度的原因，包括健康的社会决定因素的可能作用，并可能为该人群创建更好地量身定制的技术。
