What Is the Evidence Supporting the Use of Mobile Health Technologies in Palliative Care?

Karin Porter-Williamson,Christian T. Sinclair

Elsevier eBooks(2023)

引用 0|浏览1
暂无评分
摘要
There has been explosive growth in mobile technologies for health care over the past decade, accompanied by exponential growth of cellular technology worldwide. The evidence base for such applications and their impact on patient outcomes is young, however. The commercial market has advanced more rapidly than the research sector, revealing a need for standardization, regulation, and outcome study to guide best practice. There is increasing evidence that these applications improve the quality of and access to care, access to health information, and promotion of behaviors impacting health outcomes. These benefits are particularly important for people isolated geographically, socioeconomically, or functionally from the burden of illness. As such, the ability of mobile health (mHealth) strategies to improve palliative care practice is extremely promising. The strongest evidence for mHealth strategies is in diabetes management, pulmonary rehab, and cardiac disease. Use of activity trackers among the public, either wearable devices or embedded smartphone monitors, may provide more accurate data on patient function than clinician assessment. Studies of mHealth solutions in cancer care target patient-reported outcomes for pain, fatigue, self-management support, and quality of life. Studies also show improved survival, treatment adherence, and patient–provider communication, and decreased hospitalization. For the fields of hospice and palliative care, quality mHealth applications should combine evidence-based intervention and functional software design for user accessibility, seamlessly integrated into clinical workflows to improve patient care. Examples showing the power of these tools are emerging rapidly, across all aspects of hospice and palliative care service delivery from home to ICU settings.
更多
查看译文
关键词
mobile health technologies,palliative care
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要