In the early 1980’s, NASA developed an early version of tele-I.C.U. for the “Freedom” Space Station. The idea was that it was a medical system that could be used by astronauts in orbit. When it comes to tele-medicine, technology has improved substantially since then–both in terms of hardware AND software (not to mention the internet and wi-fi connectivity). As we have come a long way, it is time for us to map what was originally intended for just a space station to all of society–that is: from an isolated solution to a global solution
Recently, the Dutch tech company, Philips rolled out a state-of-the-art tele-I.C.U. at Dartmouth-Hitchcock medical center. Their system runs predictive algorithms to make prognoses. What makes this latest innovation ground-breaking (and so much better) is that it is powered by AI.
We have come a long way, but there’s still a long way to go. As recently as 2018, tele-Health accounted for only 0.1% of all medical claims. However, in the advent of the corona-virus pandemic of 2020, people are starting to come around. More and more professionals are realizing that AI-powered tele-medicine enables them to do things that they never would have dreamed of before; making their job much easier while saving everyone time and money.
Tele-health capitalizes on the availability of information technology to deliver medical services (diagnostics, support, and education) expediently and cheaply to those who would otherwise have limited access to vital resources. Capabilities are augmented wherever AI applications are available to supplement new remote healthcare systems. The synergy of AI and tele-medicine is exemplified by Google AI, which has been used to remotely analyze and treat diabetic retinopathy. Since clinical telemetry technology is available remotely, AI-driven software can filter through the massive data-sets faster than ever before, quickly identifying medical issues before they become severe.
When remote checking is merged with AI, better diagnostics quicker, and for less cost. By availing themselves of this new technology, clinicians will be able to analyze, screen, and treat diabetic retinopathy remotely by means of this new technology. Hence the L.A. county Department of Health Services was able to drastically reduce visits to specialty care professionals by implementing tele-medicine screenings for diabetic retinopathy at its net facilities. Wait times were significantly diminished; and with EPR / EHR (electronic patient / health records), red tape was also eliminated.
Moreover, predictive analytics will help track down the appropriate medical professionals much quicker. It can do this by matching their profile with specialists available in the network, then establishing the appropriate links. All inquiries can be automatically directed to the specialist with the best results for a patient’s symptoms rather than simply sending them to the first doctor available.
AI-powered tele-health is no longer limited to the laboratory. They are integral to our endeavor to improve healthcare services.
AI in the tele-medicine field is supplementing innovations in tele-medicine (including e-diagnosis, tele-radiology, tele-pathology, tele-dermatology, and tele-psychiatry); and companies like “Ro” are taking the lead.
Ro was launched in 2017 by Zachariah Reitano, Saman Rahmanian and Rob Schutz. The company began as a digital health clinic called “Roman”, which was focused primarily on treating male medical conditions by way of virtual doctor visits. Its direct-to-consumer tele-medicine service now operates in four arenas. Today, Ro’s digital health clinics include: “Roman” for men’s health, “Rory” for women’s health, “Zero” for smoking cessation, and “Plenity” for weight management. All of this is being done using the most cutting edge tele-medicine tech.
The average doctor’s visit is only about 12 minutes, and patients spend about 15 to 20 minutes on the Ro platform answering those questions. What it allows the physician to do is dive in very quickly to the nuance of that patient and engage with the patient from afar, instantly, and in a personal manner. Thus patients are fully informed, and are given the prerogative to decide whether they want to accept the physician-recommended treatments. This saves time and money. It not only makes the process easier for everyone, it makes it far more effective.
Using Ro’s system, patients can consult doctors online and receive personalized treatment plans that include prescriptions from Ro’s online pharmacy. This means people are given an end-to-end care experience, a process that maximized efficiency. The network is simple: Patients pay doctors directly for the consultation, and doctors pay to use Ro’s digital doctor’s office software.
With new internet and video technologies, remote patient monitoring will be able to emulate eye-to-eye interactions among doctors and patients. And as AI is incorporated into existing systems, the opportunities for remotely checking a patient’s status will become easier and more accurate. Even better, the decreased need for up-close interaction means that healthcare workers did not need to risk exposure to patients–and can conduct diagnostics and follow-ups quickly and safely, on demand, by doing so remotely.
Doctors interact with patients via messaging, phone, or video chat. If the physician thinks the patient’s symptoms indicate an underlying condition, he / she can recommend the optimal course of action; and subsequently help patients through the next best steps. This approach is about initiating and facilitating dialogue–an engagement known as “patient-led healthcare”. The system can cull third-party data about each patient, and that information may then be analyzed, synthesized, and presented to that physician.
Suki.ai offers an innovative AI-powered software solution that assists doctors as they make voice notes during the course of a busy day. Using the power of AI to learn over time, Suki’s system can adapt to users with repeated use, so the solution becomes ever more of a time saver and efficiency booster for physicians and healthcare workers. Suki is delivered with COVID-19 data and templates to speed this critically important process.
The success of AI applications in tele-medicine depends on how soon the industry adopts a comprehensive digital platform–a system that involves the participation of government regulators, patients, doctors, nurses, vendors, and the other participants in the healthcare ecosystem.
This systemic transition will involve the widespread adoption of EHRs / EPRs. That will depend on the automated aggregation of patient information, something that can only be accomplished through a well-orchestrated, universal deployment of healthcare information technology. The availability of massive data-sets combined with the rapid evolution of machine-learning will provide opportunities for drastically improving key elements in healthcare–from monitoring and diagnostics to education and clinical decision-making.