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Management engineering

Michael Carter Snippet A

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Abstract
Michael Carter describes his passion for improving the healthcare system, primarily in Ontario. In 1989, he was asked to investigate how nurses' experiences in hospitals could be improved, and he developed scheduling algorithms for operations to minimize the number of post-operative patients in hospitals on weekends. This evolved into a passion to use systems engineering to improve the healthcare system. He recognized the need to have a "small army of engineers" working in hospitals: he now knows of 180 former engineering students who work in healthcare in Toronto.

Michael Carter Full Interview

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Video
Abstract
Dr. Michael Carter is an industrial engineer who, after completing degrees in mathematics, started as a professor at the University of Toronto in 1981. He defines industrial engineering as "the applications of mathematics, computers, and psychology to developing and building human systems". Dr. Carter's initial interest was optimization and scheduling, and he developed an algorithm for scheduling university examinations that was implemented at Waterloo, Western, Toronto, Carleton, the London School of Economics, Limerick (Ireland) and Otago (New Zealand). In 1989, he was asked to investigate how nurses' experiences in hospitals could be improved, and he developed scheduling algorithms for operations to minimize the number of post-operative patients in hospitals on weekends. This evolved into a passion to use systems engineering to improve the healthcare system: he now knows of 180 former engineering students who work in healthcare in Toronto. He created the Centre for Healthcare Engineering at U of T in 1989 that now has a dozen industrial engineering faculty doing healthcare research. He describes how initially, the National Sciences and Engineering Research Council and the Medical Research Council thought his field was outside their purview, but now they have joint programs to support this research. He recalls his efforts to learn how to use Artificial Intelligence in his work – "just keeping up is a challenge, but it's fun" – and the need for massive quantities of comprehensive data to facilitate effective machine learning. He advises high-school students to consider engineering careers if they are interested in the applications of science and mathematics. He looks forward to "several more years of pushing students into the deep end of healthcare".