About the Author: Bradley Merrill Thompson is a member of the firm at Epstein Becker & Green, P.C. There, he counsels medical device, drug and combination product companies on a wide range of FDA regulatory, reimbursement and clinical trial issues. The opinions in this piece are Thompson's and don't necessarily reflect the opinions of MobiHealthNews or HIMSS.
Many appreciate that telemedicine is more than just using Skype so that a doctor can look a patient in the eyes. For telemedicine to be truly useful, the patient must be able to collect and transmit a variety of data the healthcare professional needs in order to assess the patient’s health. Indeed, state regulators have historically been skeptical of telemedicine precisely because they fear that the doctor-patient relationship in that context is too thin, with doctors being forced to make judgments based on too little available information.
Artificial intelligence can help. It can help with data collection by instructing patients how to use medical technology that collects data. It can help physicians sort through and analyze the data they do receive. It can even help deliver therapy.
In the face of COVID-19 with its attendant greater need for medical services while achieving social distancing, is FDA now ready to support the use of AI in telemedicine? I think they are.
Technology Trends in Collecting Telemedicine Data
Current telemedicine is already able to collect data in many ways, including the use of weight scales, blood pressure cuffs, heart monitors, blood glucose meters, pulse oximeters and peek flow meters and thermometers, among many others. While quite useful, all those are fairly basic. The devices have existed for years, and the innovation over the last several years primarily was simply adding connectivity and data management.
But technology is moving well beyond those vital sign monitors. For example, it’s been amply reported that ultrasound can now be done with a probe attached to a smart phone. ECG machines and other technologies also are likewise achieving small scales that allow for mobility.
Presently, in many cases like ultrasound, these new technologies are still limited to administration by licensed healthcare professionals because of their complexity, the risk associated with improper use and the difficulty in obtaining a high-quality image. But the next wave of innovation after creating cheaper and more mobile hardware will be using AI to help guide untrained users in how to administer these tests.
In February of this year, FDA authorized the marketing of AI that would guide cardiac ultrasound use. In its first FDA authorization, this guidance system is limited to use by healthcare professionals, but fundamentally the technology now exists to use AI to guide the use of historically complex diagnostic tools. Before this new guidance system, such technology would only be administered by a trained sonographer, not by other healthcare professionals.
Assessing FDA’s Current Views
In this analysis, I’m not going to reference FDA guidance documents much even though that’s the natural place to look. Unfortunately, this is so new that for the most part FDA has not kept its guidance documents up to date to reflect the agency’s current thinking.
Instead I’m going to look at what FDA actually does. The only real exception is in late February, FDA did have a public meeting to discuss the agency’s approach specifically to the use of AI in radiology. The agency’s comments there were very important more generally though. As those who observe FDA understand, FDA deals with new technologies like AI in whichever clinical context is first for innovation, and the principles worked out in that clinical context then form the basis for FDA policy with regard to technologies that follow in other areas of clinical practice.
The easiest way to assess the regulatory environment for AI in telemedicine is to distinguish between those technologies on the patient side of telemedicine, versus those on the professional side.
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