Opinion | Are Engineering and Medicine Good Bedfellows?

Ever since William Osler introduced bedside clinical training for medical students, medicine has continued to grow and evolve into a field that uses numerous technologies, all designed to improve the care of patients and the delivery of health services. These include medical devices like pacemakers, which have been used for over 60 years, and artificial limbs or prostheses. Electric health records have moved patient charts from filing cabinets to the cloud. Possibilities for 3D printing, gene therapy, and other once unthinkable medical advances have thrust medicine into a new age of hope for numerous conditions that were once untreatable.

At the fulcrum of much of this technology is engineering (and by extension, computer science), a field that translates science into usable and practical artifacts. You need not look very far to see that engineering principles are ubiquitous. Indeed, collaboration between medical scientists, medical practitioners, and engineers is advancing diagnostics and treatments that were unheard of just a few years ago. Now, with computer science, artificial intelligence (AI) is permitting clinicians to improve their assessment of disease, define treatment plans that optimize patient outcomes, and facilitate personalized medicine. AI systems deliver such results by allowing physicians to tap into a deeper pool of knowledge and experience. Both the National Institutes of Health and the National Science Foundation are making substantial investments to accelerate such advances, all designed to improve patient and population health at a lower cost.

However, such collaborations have historically come in the form of science and medical experts consulting with outside experts in the field of engineering. We believe there are benefits to breaking down such silos. It’s time for a greater effort from medical schools to recruit and train physicians with engineering backgrounds. This has the potential to foster an environment that accelerates enhanced outcomes in devices, procedures, and healthcare processes.

A Case Study

In any good collaboration, diverse viewpoints with ample bridges to facilitate communication are key. Back in 1995, a chance encounter at an engineering professional meeting in Atlanta led to a research collaboration that lasted nearly 2 decades. Scientists at the CDC were concerned about how to stock pediatric combination vaccines, which provided protection against multiple diseases in a single injection. Vaccine manufacturers were developing such products, and they needed guidance on how they could be optimally used to satisfy the pediatric immunization schedule.

The problem the CDC faced required combinatorics and algorithms, skills that the CDC were mostly short on but exactly what our research group possessed. The CDC, of course, had the domain knowledge that we lacked. The solution was for our team to acquire sufficient domain knowledge from the CDC to use our skills and provide a solution.

It worked!

After co-authoring and publishing several papers in peer-reviewed engineering and medical journals, the models and algorithms we introduced provided insights into how certain pediatric combination vaccines can be optimally deployed and priced.

The biggest takeaway from this experience is that our role as engineers and computer scientists was to take a deep dive into the medical domain and translate our technical expertise in a manner that the medical personnel could appreciate. They did not need to do the heavy lifting in our domain; we had to learn their domain.

But wouldn’t this all have been easier if one of the CDC scientists or physicians already had a background in engineering? If they had acquired their undergraduate degree in engineering, computer science, mathematics, or perhaps economics, this would have been sufficient.

Translating the Takeaway Into Action

What this experience suggests to us is that if medical schools step out of their traditional pre-med requirements when recruiting their students, and take the leap-of-faith that well-trained engineering, computer science, or mathematics undergraduates take they could learn the finer details of medicine (perhaps filling in the pre-med gaps with a year of study or a post-bacc), the end product would be budding physicians equipped to meet the technological advances that define the future of medicine. This would effectively grow the pool of qualified medical student applicants in the country, at a time when we’re facing dire physician shortages. Moreover, by showcasing this new direction for medical student recruitment, it opens the door for more physicians who can support our nation’s healthcare needs as our population ages.

Creating a technologically literate population of future physicians benefits everyone. But first and foremost, they must be excellent physicians, with all the skills, smarts, and humanism to take a medical history, diagnose disease, and provide care. These are hard constraints that cannot be compromised.

Recruiting medical students with backgrounds in engineering, computer science, or mathematics may appear risky. In reality, it is the safest way to ensure that future physicians can embrace and use the technologies that are certain to be developed in the future that will change the practice of medicine. This is precisely what the patients of the future will need, and perhaps, may come to expect.

Sheldon H. Jacobson, PhD, is a data scientist and a founder professor in computer science in the Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign. Janet A. Jokela, MD, MPH, is the senior associate dean of engagement in the Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign.