From electronic visits to electronic billing, technology is changing the face of healthcare. The move to automate everything from delivering services, prescribing medications, submitting and paying insurance claims, and the like seems like an alluring timesaver. But who is it really serving? And is it doing the job intended?
With the explosive interest in ChatGPT and other language model programs, many AI evangelists are touting their use as a diagnostic tool in healthcare—or even broadly declaring it to be the future of medicine. As with many high-tech innovations, proclamations like this can often overshadow small but crucial applications that are immediately in our grasp.
A Personal Story
A company where I was a programmer won a contract to automate medication processes at a major US hospital. When the project went live, we got a bug report from a very angry doctor complaining that the system wouldn’t let him prescribe sufficient doses of a particular drug. We investigated and found his scripts were for a few milligrams, when the safe maximum, as enforced by our software, was 20 micrograms, or about 100x less. It turned out he’d been doing this for decades—no one ever had the courage to correct him and the nurses just kept silently fixing his erroneous paper prescriptions. Sounds like a good catch and electronic prescribing caught a possibly dangerous practice.
On The Other Hand
When you add AI to the mix, you are liable to face some complicated challenges.
Just as humans make mistakes, so too can software. There are many reports of Electronic Patient Record (EPR) systems “forgetting” to send important patient notifications, obscuring critical treatment information, and causing harm and even death to those we’re trying to care for. The problem, as described by British health leader Joe McDonald, but not unique to Great Britain, is that with paper, “when you make a mistake you make them one at a time,” but EPR “gives you the opportunity, unfortunately, to make the same mistake thousands of times.”
Dr. ChatGPT
ChatGPT recently passed the U.S. Medical Licensing Exam, but using it for a real-world medical diagnosis could quickly turn deadly. As Dr. Josh Tamayo-Sarver, who works clinically in the emergency department of his local community discovered, ChatGPT works fairly well as a diagnostic assistant—but only if you feed it perfect information, and the actual patient has a classic presentation, which is rarely the case. Feeding detailed medical narrative of 35-40 patients’ medical history and the symptoms that brought them to the emergency department, he found that for roughly half, ChatGPT suggested six possible diagnoses, and the “right” diagnosis—or at least the diagnosis that he believed to be right after complete evaluation and testing—was among the six that ChatGPT suggested.
Doesn’t sound so bad. But a 50% success rate in the context of an emergency room is also not good. What his experiment illustrated was how the vast majority of any medical encounter is figuring out the correct patient narrative. For example, if someone comes into the ER saying their wrist hurts, but not due to any recent accident, it could be a psychosomatic reaction after the patient’s grandson fell down, or it could be due to a sexually transmitted disease, or something else entirely. The art of medicine is extracting all the necessary information required to create the right narrative. And that requires a human.
The Privacy Issue
An additional consideration is patient privacy. Currently, anything entered into ChatGPT is essentially published to the web. To be in line with HIPAA, any factors that would enable linkage to a specific patient would have to be removed or altered.
Personalized Care
Personalized care refers to the creation of tailored treatment plans for individual patients. In practice, this is increasingly being done with technology and data. The most advanced applications are in genomics, where AI is being used to analyse patients’ DNA to diagnose and treat diseases and to create medicines that are personalized to specific people down to the molecular level (sometimes called precision medicine). Many researchers believe that a personalized approach to healthcare leads to better patient outcomes and more efficient use of medical resources and will play an increasingly important role in addressing the healthcare challenges of the future.
IoT-Powered Virtual Hospitals And Telemedicine 2.0
This trend includes both telemedicine and wearable devices connected to the global network known as the Internet of Things (IoT). By using connected devices to remotely monitor patients and provide communication channels for healthcare professionals, more elements of care can be delivered remotely. We call this “telemedicine 2.0” because it goes beyond the simple delivery of remote care, such as remote consultations, to a holistic approach to remote patient care and treatment. Virtual hospital wards are an example of this trend in action in 2024 – where a central location acts as a hub for monitoring multiple patients in their own homes.
Is AI Serving Or Stifling Healthcare?
The answer seems to be a little bit of both. Technology can look like a panacea—and in some instances it may be—but it’s foolish to assume computers are infallible. For now, it is wise to keep humans in the loop and consider simple, low-tech tactics first. Perhaps instead of rushing to a centralised, robotic records solution, we should stick with some manual, offline methods for a little while yet. After all, that’s how we handle elections, where the worst result of voting machine error is goofy results—which we can check with good old reliable paper.
Author Bio
Douglas Squirrel has been coding for forty years and has led software teams for twenty. He uses the power of conversations to create dramatic productivity gains in technology organizations of all sizes. His experience includes growing software teams as a CTO in startups from fintech to biotech to music, and everything in between; consulting on product improvement at over 200 organizations in the UK, US, Australia, Africa, and Europe; and coaching a wide variety of leaders in improving their conversations, aligning to business goals, and creating productive conflict. He lives in Frogholt, England, in a timber-framed cottage built in the year 1450. He is the author of Squirrel’s Tech Radar, Decoding Tech Talk, and Agile Conversations: Transform Your Conversations, Transform Your Culture, co-authored with Jeffrey Fredrick. Learn more at douglassquirrel and squirrelsquadron.
