Date of Award
2022
Publication Type
Thesis
Degree Name
M.A.Sc.
Department
Industrial and Manufacturing Systems Engineering
Keywords
Artificial intelligence, Healthcare, Human-machine collaboration, Robotics
Supervisor
W.El-Maraghy
Supervisor
D.Pusca
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
Almost every individual has visited a healthcare institute, whether for an annual checkup, surgery, or a nursing home. Ensuring healthcare institutes are using human-machine collaboration systems correctly can improve daily operations. A maturity assessment and an implementation plan have been developed to help healthcare institutes monitor the human-machine collaboration systems. A maturity model, the Smart Maturity Model for Health Care (SMMHC), is a tool designed for maturity assessment. A four-step implementation plan was also created in this research. The implementation plan views the maturity of the institute and develops a strategy on how to improve it. The research utilized Integrated Definition (IDEF), Zachman Framework, Strengths, Weaknesses, Opportunities, and Threat (SWOT) analysis, surveys, and Systematic Design to design the SMMHC. Use cases and case studies were utilized to create the implementation plan.
One use case and two case studies were conducted to validate and verify the SMMHC and the four-step implementation plan. The use case illustrated a hypothetical situation using the SMMHC and helped develop the implementation plan. The two case studies show how hospitals can utilize the SMMHC and the implementation plan. The first case study completed at Henry Ford Hospital (HFH) Detroit campus shows that the hospital is only operating at the third maturity level. The second case study shows that Erie Shores Hospital (ESH) only works at the first maturity level. Implementation strategies were given to the two hospitals in the case study on how to improve. This research shows how healthcare institutes can utilize these tools to improve operations and become more efficient with human-machine collaboration systems.
Recommended Citation
Fenton, Breeze, "Human-Machine Collaboration in Healthcare Innovation" (2022). Electronic Theses and Dissertations. 8913.
https://scholar.uwindsor.ca/etd/8913