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Does NP + AI = MD?

Artificial intelligence (AI) is causing a paradigm shift in the education, business, and legal professions. But AI is also poised to irreversibly change the way medicine is practiced. Jobs that traditionally relied on extensive training by memorization may be able to be performed as well (or better) by AI than by humans. Jobs that have relied on image analysis or sound pattern analysis are also at risk of being displaced by AI.

Let me give you an example from my hobby of birdwatching. In the past, bird species identification relied on comparing a bird that you saw in a tree to a drawing or photograph in a bird identification book. To become an expert birder, you needed thousands of hours of birding to identify birds by their calls and by their seasonal plumage. But now, we have the Merlin app. When birding, I can turn on my phone’s microphone and Merlin will identify bird species by bird calls. I can take a photograph of a bird, upload it to the app, and Merlin will tell me what bird I saw. With Merlin, even a novice birder like me can identify birds like a seasoned expert.

So, what if we have the Merlin app equivalent to identify heart sounds by auscultation? Or diagnose a rash by a photograph? Or interpret CT scan images? Or read cytology specimens on microscopic slides? Like it or not, artificial intelligence is coming to medicine and it will make many skills traditionally requiring hundreds of hours of training, obsolete.

Artificial intelligence and advance practice providers

To become a primary care physician (general internist, general pediatrician, or family physician) requires 11 years of education and training after high school. To become a nurse practitioner (NP) or physician assistant (PA) only requires 6 years of training after high school. As a result, it is far less expensive to become an NP or PA than to become a primary care physician but the trade-off is that NPs and PAs generally have a  lower annual income than physicians. However, if the salary of an NP and a primary care physician was the same, most hospitals would prefer to hire the physician under the presumption that additional 5 years of training to be a primary care physician would translate to greater skill and knowledge than the NP or PA. On the other hand, if the skillset and knowledge of an NP or PA was the same as that of a primary care physician, most hospitals would prefer to hire the NP or PA because they are cheaper.

Artificial intelligence now offers the possibility of eliminating the need to acquire many of the skills and much of the knowledge currently required to become a physician. This offers a future where an NP armed with a few AI apps may be able to perform many of the tasks currently relegated to physicians.

Need to diagnose a child with a fever and a rash? There’s going to be an app for that. Need to decide the best blood pressure medication to prescribe for a patient with newly diagnosed hypertension? There’s going to be an app for that. Need to recommend follow-up of a pulmonary nodule given a patient’s age and smoking history? There’s going to be an app for that.

The FDA and medical devices

At first glance, it would seem logical to embed artificial intelligence into electronic medical record (EMR) software programs. After all, the EMR is the database of all information about a patient – their blood pressure, their family history, their medication list, etc. However, a barrier to incorporating AI into the electronic medical record is that the U.S. Food and Drug Administration considers AI to be a medical device whereas the electronic medical record is just considered a documentation tool. Medical devices are regulated differently than documentation tools. Medical devices require extensive clinical trials and then FDA approval; documentation tools do not. Clinical trials and FDA regulation are very expensive and can pose a barrier to regular EMR software upgrades. For these reasons, the major electronic medical record companies have been reluctant to incorporate artificial intelligence algorithms into their EMR programs.

For the most part, this makes sense. You don’t want to have an artificial intelligence program to recommend a chemotherapy regimen for advanced lung cancer unless it has been shown in clinical trials to be accurate and has been approved by the FDA. The fear of the electronic medical record companies is that if their EMRs become classified as medical devices, then they will have to get FDA approval every time they want to change the font size in their blood chemistry test results in the EMR. So, at least for now, the electronic medical record and artificial intelligence programs will need to be separated, and that means that there will have to be a human to do a history and physical examination and then to interface between the EMR and the AI. But in many situations, that human can be an NP or a PA, rather than a physician.

Artificial intelligence and primary care

Much of primary care is based on clinical practice guidelines. The U.S. Preventative Services Taskforce has guidelines for everything from colon cancer screening to pre-exposure prophylaxis to prevent HIV. The American College of Cardiology has a hypertension diagnosis and management guideline. The Advisory Committee on Immunization Practices has guidelines for childhood and adult vaccination schedules. And the American Diabetes Association has a guideline for the prevention, diagnosis, and treatment of diabetes. If you roll all of these clinical practice guidelines into one artificial intelligence program, then you have the majority of primary care medicine routine visits covered.

As a medical student, I spent hours memorizing vaccination schedules, hypertension treatment algorithms, diabetes medication drug interactions, and the staging systems for various cancers. And guess what? An artificial intelligence program can do all of these things better than my memory allows me to do. In other words, AI eliminates the need for much of the education and training that we currently require in medical school and residency. Artificial intelligence will allow a practitioner with lesser training (such as an NP or PA) to be just as good as a physician when it comes to preventative care medicine and algorithm-based management of most common medical conditions.

However, artificial intelligence is not infallible

Artificial intelligence is actually not new in medicine. I’ve been using simple forms of AI for decades. Every EKG and pulmonary function test that I have ordered in the past 30 years that comes with a computer interpretation has incorporated rudimentary AI into those interpretations. These interpretations programs are fairly good at identifying normal but invariably come up with an incorrect diagnosis in a substantial percentage of those tests that are abnormal. So, before I am willing to allow an AI program to diagnosis breast cancer from a histopathology slide and before I am willing to allow an AI program to diagnose idiopathic pulmonary fibrosis from a chest CT scan, these programs are going to have to get very, very good. Until then, the use of artificial intelligence for more complex pathologic and radiologic diagnoses will supplement rather than replace a physician.

And then there is legal liability…

If a radiologist misses a lung cancer on a chest X-ray, the radiologist is named in a medical malpractice lawsuit. If a patient dies of sepsis when a hospitalist made an incorrect antibiotic choice for the patient’s pneumonia, the hospitalist is named in the malpractice suit. But if an artificial intelligence program misses the lung cancer or selects the wrong antibiotic, who gets named in the malpractice case? The company that created the AI program? The hospital that purchased the AI program? The FDA that approved the program? The physician who entered the patient’s clinical data into the program? All four of them?

Currently, a physician in primary care practice will pay about $12,000 per year in malpractice insurance premiums whereas a primary care nurse practitioner pays about $1,200. The reason for the 10-fold difference is that in most situations, a nurse practitioner is understood to be working under the supervision of a physician and that physician is ultimately responsible or at least shares responsibility for the management of patients seen by the nurse practitioner.  Artificial intelligence is likely to be similar – if it is considered to be a medical device then that device will need to be used by a licensed medical practitioner who will have the greater burden of malpractice liability. Clearly, laws will need to be written to clarify liability before artificial intelligence can be autonomously implemented in clinical practice.

Who will AI benefit the most – nurse practitioners or physicians?

A recent study from MIT researchers found that artificial intelligence has the greatest impact on the least skilled workers. Workers who were new or had low skills were helped more by AI than highly skilled workers. In other words, AI allows those with less training to be “upskilled” much more than those with advanced training.

Extrapolating from this study, it is likely that nurse practitioners and physician assistants will derive greater benefit from artificial intelligence than physicians. Artificial intelligence can make up for the fewer years of training that it takes to become an NP or PA.

Which physicians are most vulnerable to being displaced by artificial intelligence?

Although artificial intelligence has received a lot of press about its potential in radiology, I would argue that primary care physicians are most vulnerable to being displaced by artificial intelligence. Notice that I used the word “displaced” rather than “replaced”. That is because artificial intelligence is likely to be used to supplement a practitioner rather than become a practitioner, at least in the foreseeable future. In this regard, an NP or PA using an artificial intelligence program can replicate much of the skillset of a primary care practitioner. Thus the combination of an NP or PA plus an artificial intelligence program will together displace the primary care physician.

Physicians who are the least vulnerable are those who perform procedures such as surgeons and interventional cardiologists. Although this could change in the future, for now, no AI program or nurse practitioner is capable of independently performing a hip replacement surgery or a coronary artery stent placement. In primary care practice, the office procedures are far less complex – cerumen removal, IUD placement, and laceration suturing can be performed by an NP or PA and do not require a physician.

Also less vulnerable are physicians who are highly specialized. For example, an artificial intelligence program for brain MRI imaging will need to be used under the supervision of a practitioner who can confirm or contradict the AI’s findings. This will require a practitioner who is already an expert in brain MRI image interpretation, in other words, a physician specializing in neuroradiology. Artificial intelligence can still benefit the neuroradiologist, however, by serving in a capacity similar to that of a radiology resident who performs a preliminary read of the MRI that is then over-read and confirmed by the attending neuroradiogist.

“I’m a medical student, should artificial intelligence affect my career choice?”

The answer is… maybe. Fully implemented artificial intelligence in medicine is still a long way off. There will have to be significant improvements in software, significant legal liability questions resolved, and supervision requirements defined. However, if AI can replace certain medical specialists at a lower cost, then economic theory indicates that it eventually will. General internists, general pediatricians, and family physicians may be more vulnerable to displacement than other specialties, especially if the field of medical artificial intelligence matures coincident with an increase in the number of nurse practitioners and physician assistants. However, when it comes to cajoling a cardiologist to add in a patient with chest pain to their already full Friday afternoon schedule, an AI program simply cannot replace a persuasive family physician. The primary care physician may become more of a manager: coordinating care and overseeing a group of nurse practitioners who each have access to the artificial intelligence program.

Things are about to get interesting…

Change in medicine is inevitable but initial resistance to change is also inevitable. When electronic medical records were initially implemented, physicians universally hated them and many refused to use them. Now, no physician in his or her right mind would want to return to an era of paper records kept in manila folders. Ten years ago, the idea of driverless vehicles was met with skepticism but today, you can order a driverless Waymo taxi in San Francisco and you can buy a driverless John Deere tractor to plow your farm.

Artificial intelligence is coming in medicine and its widespread implementation is unavoidable. The question is whether it will augment physicians or displace physicians. I believe that it will do both, depending on the specialty.  From my vantage point, primary care physicians may be the most vulnerable to displacement. And employment opportunities for NPs and PAs are looking bright.

August 30, 2023

By James Allen, MD

I am a Professor Emeritus of Internal Medicine at the Ohio State University and former Medical Director of Ohio State University East Hospital