How telemedicine intersects with AI, social media, and precision medicine

Telemedicine will eventually become a more prominent part of our clinical practice, with the incorporation of artificial intelligence (AI) and social media and networks, and integration with precision medicine in electronic health records. As clinicians and scientists, we should be thinking about where and how these four innovative strategies intersect, so that we can continue to not only contribute to the conversation and direction of these strategies, but also lead them.

Remote monitoring of physiology is an important component of telemedicine or telehealth. If we are to care for our patients remotely in telemedicine, then we must be able to have data on which to make decisions. Some of the data come from remote monitoring, while some may come from information we may already have in electronic health records, in addition to the current history during a consultation. The remote monitoring can also be at the time of the consultation, or monitoring can occur outside of the consultation in real-time continuously, or for a discrete portion of time. The remote monitoring may address different areas of physiology, such as blood pressure, blood sugar, heart rate and rhythm, and so on. With this information, the healthcare professional can potentially make adequate recommendations for prevention and management of disease.

Institutions should also embrace the role of AI in remote monitoring of physiology and use of this data in real-time for prediction of disease. Being able to foresee illness or dysfunction with predictive analytics and AI may provide us with the opportunity to preempt and prevent imminent decrease in quality or quantity of life (within the scope of individuals’ values and goals, of course). Cooperation between AI and mobile health (mHealth) or digital health can maximize potential in remote monitoring. AI algorithms can help guide the performance of echocardiograms, even in the hands of novices or amateurs. This could be particularly useful if an experienced sonographer or echocardiographer is not immediately physically available on site. An individual could have a telemedicine consultation with an experienced cardiologist, while a novice physically on-site with the patient could perform a brief, limited AI-assisted echocardiogram. ECG and other physiological data from smartwatches, smart T-shirts, smart shorts, patches, and other wearables and biosensors, in addition to the typical or routine equipment used for telemedicine, are also over time being coupled with machine learning to alert clinicians to current or future danger in patient health and wellness. The possibilities for the impact of this coupling on morbidity and mortality, particularly in cardiovascular diseases and other chronic conditions, is vast.

The contribution of social media to telehealth will take different forms. If properly integrated, patients could reach out to their health care professional teams via social media, with indirect or direct connection with or follow-up from vigilant team members assigned to telehealth and social media. Patients are already posting on social media and in social networks about their medical conditions, and are seeking information online to answer their medical questions. These patients often also are early adopters of wearables and mHealth. Perhaps social listening and informatics infrastructures could develop pipelines to streamline connection of patients sharing about medical problems and seeking answers on social media with their on-call health care provider team to optimize care. Physiological data from their wearables and mHealth platforms could be interrogated and provided for analysis and interpretation in real-time, along with the telehealth consultation. These data and consolidation should be included in the electronic health records, which will need to be enhanced to handle such disparate sources of data, clinical interaction, and documentation.

Physiological and analytical data from remote monitoring in mHealth or digital health, coupled with AI algorithms and pipelines from social media in telemedicine, can help personalize expedient and efficient care for patients. One cannot fully think about personalizing care without mentioning “personalized medicine” or “precision medicine,” which incorporates other tools such as genomics and a variety of other “omics.” These omics can include epigenomics or methylomics, along with other assessments of gene-environment interactions. Precision medicine is closely related to “systems medicine,” which studies the comprehensive response of the body or parts of the body as dynamic systems that can be perturbed by diverse stimuli, such as the response of the cardiovascular system to administration of therapies for a variety of cancers. Sooner or later, our partnerships in academia, industry, and other facets of society will lead to the creation and use of patient representations in digital systems that synthesize clinical information from patient surveys and visits with physiological, analytical, and precision medicine data.

These are only a small sample of a myriad of reasons why and examples of how telemedicine, remote monitoring, AI, mHealth, digital health, social media, and precision medicine, with integration in electronic health records, might be useful and may become more pervasive in our collaborative multidisciplinary practice of medicine and wellness.

This is indeed the future of medicine. We will ultimately need to decide whether we will be leading at the forefront or sitting in the back row of this new era of disruptive innovation.

Sherry-Ann Brown is a cardiologist.

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