Types of Telehealth: Modalities
Both eHealth and AI have huge potential in efficient and desired medical outcomes in telehealth. Each have a long list of benefits, but more research might be needed to better understand how these emerging modalities can be maximized for telehealth.
Read below for more information on each.
eHealth may not have a clear and exact definition, but a study defined it as (Eysenbach, 2001):
“an emerging field in the intersection of medical informatics, public health and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve health care locally, regionally, and worldwide by using information and communication technology.”
From this definition, it only shows that ehealth is way beyond technology and includes a larger scope. In addition, the “e” in ehealth not only means “electronic,” it stands for many e’s that best describe the scope of ehealth. The same study also mentioned 10 essential meanings of the “e” in ehealth, which are:
In terms of e-health’s potential in enhancing health care, HealthIT.gov published a research article about using ehealth tools for patient and caregiver engagement. It explains how the tools can help manage engagement and provide essential functions to make interaction efficient, which include:
Considering these helpful functions of ehealth tools, medical practices and patient satisfaction can significantly be improved. In addition, the study also discussed the benefits that both caregivers and patients can get from using the ehealth tools, such as:
AI can provide a few key functions to help improve medical practices through telehealth. A study showed that AI can assist in telemonitoring, tele-interactions, telediagnosis, and tele-assessment (Kuziemsky et al., 2019). Tele-monitoring, for example, involves primarily patient data. With AI applied, coordination and incorporation of data become more accurate and the transmission of the information is faster.
For tele-interactions, medical practitioners can easily answer patients’ health-related questions and provide educational guidance on people’s conditions with the help of AI. In terms of telediagnosis, AI can significantly help in storing and managing large datasets of various disease populations that make diagnosis easier and more accurate. Also, the contribution of ultrasound imaging or MRI makes tele-assessment easier, primarily because the data from these machines can be quickly transferred and collected with advanced technology.
References:
https://pubmed.ncbi.nlm.nih.gov/16356311/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1761894/
https://www.healthit.gov/sites/default/files/nlc_using_e-healthtools.pdf
