Physicians rely on high-quality information to make crucial decisions in patient care. Throughout the healthcare system, technology empowers medical professionals to collect, analyze, and share data. Modern technology has never been more powerful and capable. Yet, some medical providers continue to rely on archaic legacy healthcare software systems designed 30 years ago or more.
Frequently, medical professionals depend upon multiple studies from multiple sites which use different systems. To be usable, the different systems must distill their data down to the lowest common denominator.
“The biggest impact is on your clinical information because legacy systems give you one line of history,” says R. Kent Huston, MD, CPE, a Colorado-based neuroradiologist with Radiology Partners. “The radiologist is getting one line that’s being sent from the ordering physician, and there’s a whole electronic medical record on the back end that we can’t get access to.”
Legacy Healthcare System Data Quality Over Quantity
That’s not to say that all medical professionals need every single record ever created. Some regional health information networks comprised of aggregate EMR data do make it possible for patients to carry their entire medical record from doctor to doctor. On the other hand, a similar program for radiologists would result in information overload and would likely not be particularly effective.
Clinical information systems often fall short of being able to extract relevant patient information. “They were just designed to be data capture engines,” notes Dr. Huston, pointing out legacy healthcare systems were not designed to determine how information can be used to deliver better care.
Artificially Intelligent and Highly Relevant
Artificial intelligence (AI) presents a powerful opportunity to produce useful, highly-relevant information cultivated from broad sets of data. An AI-powered interface that distills data down to the most relevant information for each specific study could guide clinicians through an actionable, reliable report.
“I don’t need to spend my time doing data-entry,” says Dr. Huston, who believes an AI-generated one-page summary of relevant patient information would help provide better care. “I want to be able to walk into the exam room and in 30 seconds get a sense of who this person is, why they’re here, and what their concerns are. I can just focus on having a conversation with them and exploring some of those things that they’ve reported to me.”
In summary, implementing AI across the healthcare IT landscape won’t happen overnight. We know that data stored in disparate legacy healthcare software systems will continue to produce inefficiencies in patient care. However, AI stands out as a powerful possibility to greatly improve on the quality and effectiveness of patient care.
Did you find this article helpful? Be sure to read our other MD interviews in the MD Voices section of our MD Clarity blog. Want to learn about our modern-day, time-saving software and solutions? Request a demo!