"Engineering is a profession in which knowledge of the mathematical or physical sciences gained by study, experience and practice is applied with judgement to develop ways to utilize, economically, the materials and forces of nature for the benefit of mankind" (Accreditation Board of Engineering and Technology). While scientists focus on how things work, engineers focus on creating new and technologically innovative solutions to problems. For many years engineers and healthcare professionals spoke different languages, published in different journals, and rarely collaborated. In a hospital a "bioengineer" was the person you called when a piece of equipment needed to be fixed. That began to change in the last quarter of the 20th century, but the two fields began to move rapidly toward convergence in the last 25 years. Engineering and technology are influencing a great deal of healthcare. Some examples of convergence include the disciplines of 1) medical Imaging; 2) robotic surgery; 3) "smart" biomaterials; 4) printing of vessels and organs; 5) telemedicine and digital health; 6) biomedical devices and instrumentation; 7) healthcare informatics and data analytics; 8) organoids, organ on a chip, tissue engineering, regenerative medicine; and 9) artificial intelligence. Examples of accomplishments of the faculty of an Engineering in Medicine Division which was established at the Brigham and Women's Hospital at Harvard Medical School will be presented. This Division is unique in being embedded in a Department of Medicine.
We are currently in the "4th Industrial Revolution" characterized by digitization, cyber-physical systems, artificial intelligence and 5G telecommunications. In each component of this revolution, technology and engineering play a pivotal role. Digitization encompasses the internet of things, cloud computing, RFID technologies, advanced autonomous robotics, cyber security, digital manufacturing of medical devices, augmented reality, big data analytics, machine learning, simulation and modeling and smartphone mobile technologies with increasing amounts of efficiency and synthesis brought about by artificial intelligence (AI). There are a growing number of examples where AI has been shown to very effective in diagnosis, data synthesis and early screening. Obstacles are present, however, as they always are with new technologies. Factors holding back AI adoption include: 1) Inertia and resistance to change; 2) privacy and security concerns; 3) concerns about being replaced; 4) lack of transparency in algorithms with demonstrated examples of bias; 5) lack of trust; 6) reimbursement concerns; and 7) implementation barriers.
