Expanded use of Electronic Health Records (EHRs) is an integral component of the ongoing modernization of the U.S. health care system through digitalization. Among the anticipated advantages of using EHRs are improvements in patient care (e.g., through faster access to relevant information and consequently improved care coordination), increased patient engagement, as well as reduction of medical errors and cost savings. On the other hand, implementing EHRs in a sustainable and legally compliant way requires upfront investment in hardware, software, training, workflow restructuring, as well as management of risks unique to electronic records, such as vulnerability to malicious interference. When EHRs are combined with mobile platforms, the cybersecurity risks multiply. Addressing this latest challenge can be daunting, both for medical practices and EHR product providers.
Artificial Intelligence (AI) can be employed in a health care setting for a variety of tasks, from managing electronic health records at a hospital, to market research at a benefits management organization, to optimizing manufacturing operations at a pharmaceutical company. The level of regulatory scrutiny of such systems depends on their intended use and associated risks.
In the U.S., for medical devices using AI, one of the key regulatory bodies is the Food and Drug Administration (FDA), especially its Center for Devices and Radiological Health (CDRH). CDRH has long followed a risk-based approach in its regulatory policies, and has officially recognized ISO Standard 14971 “Application of Risk Management to Medical Devices.” That standard is over 10 years old now, and therefore is currently undergoing revisions – some of which are meant to address challenges posed by AI and other digital tools that are flooding the medical-devices arena.