Lehigh and the Mayo Clinic are collaborating to make medical care more affordable and accessible. Researchers are focusing their attention on medical systems engineering, integrated devices and monitoring, and emerging biomedical materials.
The politics of healthcare may be impossible to predict, but one trend in medicine seems certain to gain momentum in the 21st century: Engineers working with biologists and physicians will develop new therapies, new devices and new diagnostic tools that improve the quality of life while giving people more control over their medical choices.
Indeed, says Anand Jagota, considering the potential benefits, engineers are compelled to expand the role they play in medicine.
“The huge expense of healthcare in the United States is unsustainable and is a drag on the economy,” says Jagota, a professor of chemical engineering who directs Lehigh’s bioengineering program. “This is due partly to the system and partly to tremendous inefficiencies in healthcare delivery itself.
“Engineers cannot necessarily reform the system, but we can help make the delivery of healthcare cheaper, simpler and much more efficient, and we have an obligation to try to do so.”
Jagota is taking the lead in a collaboration between Lehigh and the Mayo Clinic in Rochester, Minn., whose goal is bold if not breathtaking: To help bring about a revolution in medical care that parallels the metamorphosis of agriculture and manufacturing in the 20th century.
|Glass bone (bottom left) and other new materials, combined with computer-generated image analysis (top left, right) and wireless technology, exemplify how engineering influences medicine.|
The research and educational partnership counts more than three dozen participants. Key players at Mayo include Gary Sieck, vice dean for research and chair of the physiology and biomedical engineering department, and Michael Yaszemski, chair of the division of spine surgery in the orthopedic surgery department. The team at Lehigh includes Mayuresh Kothare, professor of chemical engineering, and Filbert Bartoli, department chair of electrical and computer engineering.
During the last century, say the researchers, agriculture and manufacturing evolved from “diverse, small-scale and independent entities to coordinated and efficient integrated systems” producing many times more goods and services with a small fraction of the previous work force. Medical care today is ripe for a similar transformation in accessibility, affordability and efficiency – if engineering principles and technological advances are applied systematically across modern medicine’s broad and diverse landscape.
A three-pronged approach
Researchers from Lehigh and Mayo are working on projects in three categories: medical systems engineering, integrated devices and monitoring, and emerging medical materials. Advances in these areas, the researchers say, promise to have a significant impact on several aspects of future medical care.
Imagine, for example, taking cell phones and other wireless mobile gadgets and fitting them with biocompatible sensors and optical attachments that monitor the body’s vital signals as people work, play and sleep. These new devices will alert users, and the healthcare providers in a user’s network, when a trip to the hospital or clinic is in order. They will also house medical histories and records. In the process, they will decentralize medical care, says the Lehigh-Mayo team, by extending diagnosis and treatment beyond hospitals and clinics into aspects of a patient’s daily life.
On another front, new devices and software will enable patients to “self-administer” many of the monitoring, therapeutic and drug-delivery functions that specialists now do, again cutting costs. Advances in understanding the human genome will allow doctors to personalize treatment. Microfluidic devices will enable “point-of-care” diagnoses that eliminate the need for samples to be sent to labs. Intuition born of professional experience will still be critical, but more and more medical decisions will be assisted by precise measurements interpreted by computers that learn from vast medical information databases.